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Staying productive and efficient has become more critical than ever. Whether managing a team, working on a solo project, or simply looking to streamline your daily tasks, the right tools can make all the difference. This article introduces 17 useful tools and web apps designed to boost your productivity and help you achieve more in less time. From advanced video editing and project management tools to innovative AI web applications, we will discover the best resources to enhance your workflow and stay ahead in today's competitive landscape. Each tool will include a direct link, a description, and an image preview. 1. Wondershare UniConverterWondershare UniConverter (Sponsored) Wondershare UniConverter simplifies video conversion, editing, and sharing, making it an essential addition to your productivity toolkit. Boost your productivity by quickly converting videos to multiple formats, compressing large files, and editing footage with ease: High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality.


Video Compression: Compress large video files to manageable sizes while retaining high resolution.


Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more.


Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities.


AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. Enhance your video workflow and maximize efficiency with Wondershare UniConverter features! Try it yourself today: Wondershare UniConverter 🔥 2. Jasper Jasper is an AI writing assistant that helps create high-quality content quickly and efficiently. It improves productivity by generating ideas, drafting content, and editing text, which saves time on writing tasks. 3. Firefly by Adobe Firefly is Adobe's AI-driven creative tool that enhances design and photo editing processes. It boosts productivity by automating repetitive design tasks and providing advanced features for faster and more efficient creative workflows. 4. Uizard Uizard is an AI design tool that converts hand-drawn sketches into digital designs and prototypes. It enhances productivity by streamlining the design process, enabling rapid prototyping and iteration without extensive design skills. 5. PlayHT PlayHT is a text-to-speech platform that converts written content into realistic voiceovers. It improves productivity by allowing users to quickly create audio versions of their content, which can be used for podcasts, audiobooks, and other multimedia projects. 6. Reclaim Reclaim is an AI-powered scheduling tool that helps manage and optimize calendar events and tasks. It boosts productivity by automatically prioritizing and scheduling tasks, ensuring that users stay focused on their most important work without manual calendar management. 7. Obsidian Obsidian is a powerful knowledge base tool that works on top of a local folder of plain text Markdown files. It improves productivity by allowing users to organize and link their notes efficiently, enhancing their ability to manage and retrieve information. 8. Lucidchart Lucidchart is a web-based diagramming tool that allows users to create flowcharts, mind maps, and organizational charts. It boosts productivity by simplifying the process of visualizing complex information and collaborating in real time with team members. 9. Fireflies Fireflies is an AI-powered meeting assistant that records, transcribes, and searches voice conversations. It enhances productivity by providing accurate meeting notes and allowing users to easily search through transcripts, reducing the need for manual note-taking. 10. Slidesgo Slidesgo offers AI-powered presentation templates and design tools to create professional presentations quickly. It improves productivity by providing ready-made templates and design suggestions, saving time when creating slides from scratch. 11. Miro Miro is an online collaborative whiteboard platform designed for team collaboration. It boosts productivity by enabling teams to brainstorm, plan, and manage workflows visually and interactively, facilitating better communication and idea sharing. 12. Namelix Namelix is an AI-powered business name generator that creates unique and catchy names for your business. It enhances productivity by quickly providing multiple naming options, saving time and effort in brainstorming. 13. Flair Flair is an AI-powered tool designed to create and enhance branding assets, including logos and social media content. It improves productivity by automating the design process, allowing users to generate professional-quality branding materials without design expertise. 14. Spark Spark is an email client designed to help users manage their emails more efficiently with features like smart inbox, email snoozing, and collaborative email writing. It boosts productivity by organizing emails intelligently, enabling faster and more effective communication. 15. Streaks Streaks is a habit-tracking app that helps users build good habits and break bad ones by tracking up to twelve tasks daily. It enhances productivity by encouraging consistency and providing motivation to complete daily tasks and goals. 16. Harvest Harvest is a time-tracking and invoicing tool that helps businesses track time spent on projects and manage billing. It improves productivity by offering insights into time management and simplifying the invoicing process, ensuring accurate and timely billing. 17. Freedom Freedom is a productivity app that blocks distracting websites and apps across all your devices. It boosts productivity by reducing digital distractions, allowing users to focus on their work without interruptions. Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter! Also, connect with me on Twitter, LinkedIn, and GitHub! Staying productive and efficient has become more critical than ever. Whether managing a team, working on a solo project, or simply looking to streamline your daily tasks, the right tools can make all the difference. This article introduces 17 useful tools and web apps designed to boost your productivity and help you achieve more in less time. From advanced video editing and project management tools to innovative AI web applications, we will discover the best resources to enhance your workflow and stay ahead in today's competitive landscape. Each tool will include a direct link, a description, and an image preview. 1. Wondershare UniConverter Wondershare UniConverter (Sponsored) Wondershare UniConverter Wondershare UniConverter Wondershare UniConverter simplifies video conversion, editing, and sharing, making it an essential addition to your productivity toolkit. Boost your productivity by quickly converting videos to multiple formats, compressing large files, and editing footage with ease: High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality. Video Compression: Compress large video files to manageable sizes while retaining high resolution. Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities. AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality. High-Speed Conversion : Convert videos to 1000+ formats at lightning speeds without compromising quality. High-Speed Conversion Video Compression: Compress large video files to manageable sizes while retaining high resolution. Video Compression : Compress large video files to manageable sizes while retaining high resolution. Video Compression Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Editing Suite : Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Editing Suite Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities. Batch Processing : Save time by converting multiple videos simultaneously with batch processing capabilities. Batch Processing AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. AI Video Enhancer : Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. AI Video Enhancer Enhance your video workflow and maximize efficiency with Wondershare UniConverter features! Try it yourself today: Wondershare UniConverter 🔥 Try it yourself today: Wondershare UniConverter Wondershare UniConverter 2. Jas per 2. Jas per Jasper is an AI writing assistant that helps create high-quality content quickly and efficiently. It improves productivity by generating ideas, drafting content, and editing text, which saves time on writing tasks. 3. Firefly by Adobe Firefly by Adobe Firefly is Adobe's AI-driven creative tool that enhances design and photo editing processes. It boosts productivity by automating repetitive design tasks and providing advanced features for faster and more efficient creative workflows. 4. Uizard Uizard Uizard is an AI design tool that converts hand-drawn sketches into digital designs and prototypes. It enhances productivity by streamlining the design process, enabling rapid prototyping and iteration without extensive design skills. 5. PlayHT PlayHT PlayHT is a text-to-speech platform that converts written content into realistic voiceovers. It improves productivity by allowing users to quickly create audio versions of their content, which can be used for podcasts, audiobooks, and other multimedia projects. 6. Reclaim Reclaim Reclaim is an AI-powered scheduling tool that helps manage and optimize calendar events and tasks. It boosts productivity by automatically prioritizing and scheduling tasks, ensuring that users stay focused on their most important work without manual calendar management. 7. Obsidian Obsidian Obsidian is a powerful knowledge base tool that works on top of a local folder of plain text Markdown files. It improves productivity by allowing users to organize and link their notes efficiently, enhancing their ability to manage and retrieve information. 8. Lucidchart Lucidchart Lucidchart is a web-based diagramming tool that allows users to create flowcharts, mind maps, and organizational charts. It boosts productivity by simplifying the process of visualizing complex information and collaborating in real time with team members. 9. Fireflies Fireflies Fireflies is an AI-powered meeting assistant that records, transcribes, and searches voice conversations. It enhances productivity by providing accurate meeting notes and allowing users to easily search through transcripts, reducing the need for manual note-taking. 10. Slidesgo Slidesgo Slidesgo offers AI-powered presentation templates and design tools to create professional presentations quickly. It improves productivity by providing ready-made templates and design suggestions, saving time when creating slides from scratch. 11. Miro Miro Miro is an online collaborative whiteboard platform designed for team collaboration. It boosts productivity by enabling teams to brainstorm, plan, and manage workflows visually and interactively, facilitating better communication and idea sharing. 12. Namelix Namelix Namelix is an AI-powered business name generator that creates unique and catchy names for your business. It enhances productivity by quickly providing multiple naming options, saving time and effort in brainstorming. 13. Flair Flair Flair is an AI-powered tool designed to create and enhance branding assets, including logos and social media content. It improves productivity by automating the design process, allowing users to generate professional-quality branding materials without design expertise. 14. Spark Spark Spark is an email client designed to help users manage their emails more efficiently with features like smart inbox, email snoozing, and collaborative email writing. It boosts productivity by organizing emails intelligently, enabling faster and more effective communication. 15. Streaks Streaks Streaks is a habit-tracking app that helps users build good habits and break bad ones by tracking up to twelve tasks daily. It enhances productivity by encouraging consistency and providing motivation to complete daily tasks and goals. 16. Harvest Harvest Harvest is a time-tracking and invoicing tool that helps businesses track time spent on projects and manage billing. It improves productivity by offering insights into time management and simplifying the invoicing process, ensuring accurate and timely billing. 17. Freedom Freedom Freedom is a productivity app that blocks distracting websites and apps across all your devices. It boosts productivity by reducing digital distractions, allowing users to focus on their work without interruptions. Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter ! my newsletter my newsletter Also, connect with me on Twitter , LinkedIn , and GitHub ! Twitter Twitter LinkedIn LinkedIn GitHub GitHub

Boost Your Productivity in 2024 With These 17 Tools & Web Apps🚀⚡

The Story Girl by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . AN OLD PROVERB WITH A NEW MEANING CHAPTER XIII. AN OLD PROVERB WITH A NEW MEANING It was half-past five when we boys got up the next morning. We were joined on the stairs by Felicity, yawning and rosy. “Oh, dear me, I overslept myself. Uncle Roger wanted breakfast at six. Well, I suppose the fire is on anyhow, for the Story Girl is up. I guess she got up early to knead the bread. She couldn’t sleep all night for worrying over it.” The fire was on, and a flushed and triumphant Story Girl was taking a loaf of bread from the oven. “Just look,” she said proudly. “I have every bit of the bread baked. I got up at three, and it was lovely and light, so I just gave it a right good kneading and popped it into the oven. And it’s all done and out of the way. But the loaves don’t seem quite as big as they should be,” she added doubtfully. “Sara Stanley!” Felicity flew across the kitchen. “Do you mean that you put the bread right into the oven after you kneaded it without leaving it to rise a second time?” The Story Girl turned quite pale. “Yes, I did,” she faltered. “Oh, Felicity, wasn’t it right?” “You’ve ruined the bread,” said Felicity flatly. “It’s as heavy as a stone. I declare, Sara Stanley, I’d rather have a little common sense than be a great story teller.” Bitter indeed was the poor Story Girl’s mortification. “Don’t tell Uncle Roger,” she implored humbly. “Oh, I won’t tell him,” promised Felicity amiably. “It’s lucky there’s enough old bread to do to-day. This will go to the hens. But it’s an awful waste of good flour.” The Story Girl crept out with Felix and me to the morning orchard, while Dan and Peter went to do the barn work. “It isn’t ANY use for me to try to learn to cook,” she said. “Never mind,” I said consolingly. “You can tell splendid stories.” “But what good would that do a hungry boy?” wailed the Story Girl. “Boys ain’t ALWAYS hungry,” said Felix gravely. “There’s times when they ain’t.” “I don’t believe it,” said the Story Girl drearily. “Besides,” added Felix in the tone of one who says while there is life there is yet hope, “you may learn to cook yet if you keep on trying.” “But Aunt Olivia won’t let me waste the stuff. My only hope was to learn this week. But I suppose Felicity is so disgusted with me now that she won’t give me any more lessons.” “I don’t care,” said Felix. “I like you better than Felicity, even if you can’t cook. There’s lots of folks can make bread. But there isn’t many who can tell a story like you.” “But it’s better to be useful than just interesting,” sighed the Story Girl bitterly. And Felicity, who was useful, would, in her secret soul, have given anything to be interesting. Which is the way of human nature. Company descended on us that afternoon. First came Aunt Janet’s sister, Mrs. Patterson, with a daughter of sixteen years and a son of two. They were followed by a buggy-load of Markdale people; and finally, Mrs. Elder Frewen and her sister from Vancouver, with two small daughters of the latter, arrived. “It never rains but it pours,” said Uncle Roger, as he went out to take their horse. But Felicity’s foot was on her native heath. She had been baking all the afternoon, and, with a pantry well stocked with biscuits, cookies, cakes, and pies, she cared not if all Carlisle came to tea. Cecily set the table, and the Story Girl waited on it and washed all the dishes afterwards. But all the blushing honours fell to Felicity, who received so many compliments that her airs were quite unbearable for the rest of the week. She presided at the head of the table with as much grace and dignity as if she had been five times twelve years old, and seemed to know by instinct just who took sugar and who took it not. She was flushed with excitement and pleasure, and was so pretty that I could hardly eat for looking at her—which is the highest compliment in a boy’s power to pay. The Story Girl, on the contrary, was under eclipse. She was pale and lustreless from her disturbed night and early rising; and no opportunity offered to tell a melting tale. Nobody took any notice of her. It was Felicity’s day. After tea Mrs. Frewen and her sister wished to visit their father’s grave in the Carlisle churchyard. It appeared that everybody wanted to go with them; but it was evident that somebody must stay home with Jimmy Patterson, who had just fallen sound asleep on the kitchen sofa. Dan finally volunteered to look after him. He had a new Henty book which he wanted to finish, and that, he said, was better fun than a walk to the graveyard. “I think we’ll be back before he wakes,” said Mrs. Patterson, “and anyhow he is very good and won’t be any trouble. Don’t let him go outside, though. He has a cold now.” We went away, leaving Dan sitting on the door-sill reading his book, and Jimmy P. snoozing blissfully on the sofa. When we returned—Felix and the girls and I were ahead of the others—Dan was still sitting in precisely the same place and attitude; but there was no Jimmy in sight. “Dan, where’s the baby?” cried Felicity. Dan looked around. His jaw fell in blank amazement. I never saw any one look as foolish as Dan at that moment. “Good gracious, I don’t know,” he said helplessly. “You’ve been so deep in that wretched book that he’s got out, and dear knows where he is,” cried Felicity distractedly. “I wasn’t,” cried Dan. “He MUST be in the house. I’ve been sitting right across the door ever since you left, and he couldn’t have got out unless he crawled right over me. He must be in the house.” “He isn’t in the kitchen,” said Felicity rushing about wildly, “and he couldn’t get into the other part of the house, for I shut the hall door tight, and no baby could open it—and it’s shut tight yet. So are all the windows. He MUST have gone out of that door, Dan King, and it’s your fault.” “He DIDN’T go out of this door,” reiterated Dan stubbornly. “I know that.” “Well, where is he, then? He isn’t here. Did he melt into air?” demanded Felicity. “Oh, come and look for him, all of you. Don’t stand round like ninnies. We MUST find him before his mother gets here. Dan King, you’re an idiot!” Dan was too frightened to resent this, at the time. However and wherever Jimmy had gone, he WAS gone, so much was certain. We tore about the house and yard like maniacs; we looked into every likely and unlikely place. But Jimmy we could not find, anymore than if he had indeed melted into air. Mrs. Patterson came, and we had not found him. Things were getting serious. Uncle Roger and Peter were summoned from the field. Mrs. Patterson became hysterical, and was taken into the spare room with such remedies as could be suggested. Everybody blamed poor Dan. Cecily asked him what he would feel like if Jimmy was never, never found. The Story Girl had a gruesome recollection of some baby at Markdale who had wandered away like that— “And they never found him till the next spring, and all they found was—HIS SKELETON, with the grass growing through it,” she whispered. “This beats me,” said Uncle Roger, when a fruitless hour had elapsed. “I do hope that baby hasn’t wandered down to the swamp. It seems impossible he could walk so far; but I must go and see. Felicity, hand me my high boots out from under the sofa, there’s a girl.” Felicity, pale and tearful, dropped on her knees and lifted the cretonne frill of the sofa. There, his head pillowed hardly on Uncle Roger’s boots, lay Jimmy Patterson, still sound asleep! “Well, I’ll be—jiggered!” said Uncle Roger. “I KNEW he never went out of the door,” cried Dan triumphantly. When the last buggy had driven away, Felicity set a batch of bread, and the rest of us sat around the back porch steps in the cat’s light and ate cherries, shooting the stones at each other. Cecily was in quest of information. “What does ‘it never rains but it pours’ mean?” “Oh, it means if anything happens something else is sure to happen,” said the Story Girl. “I’ll illustrate. There’s Mrs. Murphy. She never had a proposal in her life till she was forty, and then she had three in the one week, and she was so flustered she took the wrong one and has been sorry ever since. Do you see what it means now?” “Yes, I guess so,” said Cecily somewhat doubtfully. Later on we heard her imparting her newly acquired knowledge to Felicity in the pantry. “‘It never rains but it pours’ means that nobody wants to marry you for ever so long, and then lots of people do.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. L. M. Montgomery (2004). The Story Girl. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/5342/pg5342-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

AN OLD PROVERB WITH A NEW MEANING

April’s Lady

THE SISYPHUS: THE INSTINCT OF PATERNITY

The Glow-Worm and Other Beetles by Jean-Henri Fabre, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . THE CRIOCERES CHAPTER XVI. THE CRIOCERES I am a stubborn disciple of St. Thomas the Apostle and, before I agree to anything, I want to see and touch it, not once, but twice, thrice, an indefinite number of times, until my incredulity bows beneath the weight of evidence. Well, the Rhynchites1 have told us that the build does not determine the instincts, that the tools do not decide the trade. And now, yes, the Crioceres come and add their testimony. I question three of them, all common, too common, in my paddock. At the proper season, I have them before my eyes, without searching for them, whenever I want to ask them for information. 1 A genus of Weevils, the essays upon whom will appear in a later volume to be entitled The Life of Weevil.—Translator's Note. The first is the Crioceris of the Lily, or Lily-beetle. Since Latin words offend our modesty let us just once mention her scientific name, Crioceris merdigera, LIN., without translating it, or, above all, repeating it. Decency forbids. I have never been able to understand why natural history need inflict upon a lovely flower or an engaging animal an odious name. As a matter of fact, our Crioceris, so ill-treated by the nomenclators, is a sumptuous creature. She is nicely shaped, neither too large nor too small, and a beautiful coral red, with jet-black head and legs. Everybody knows her who in the spring has ever glanced at the lily, when its stem is beginning to show in the centre of the rosette of leaves. A Beetle, of less than the average size and coloured sealing-wax red, is perched up on the plant. Your hand goes out to seize her. Forthwith, paralysed with fright, she drops to the ground. Let us wait a few days and return to the lily, which is gradually growing taller and beginning to show its buds, gathered together in a bundle. The red insect is still there. Further, the leaves, which are seriously bitten into, are reduced to tatters and soiled with little heaps of greenish ordure. It looks as if some witchcraft had mashed up the leaves and then splashed the mess all over the place. Well, this filth moves, travels slowly along. Let us overcome our repugnance and poke the heaps with a straw. We uncover, indeed we unclothe an ugly, pot-bellied, pale-orange larva. It is the grub of the Crioceris. The origin of the garment of which we have just stripped it would be unmentionable, save in the world of the insect, that manufacturer devoid of shame. This doublet is, in fact, obtained from the creature's excretions. Instead of evacuating downwards, on the superannuated principle, the Crioceris' larva evacuates upwards and receives upon its back the waste products of the intestine, materials which move from back to front as each fresh pat is dabbed upon the others. Réaumur has complacently described how the quilt moves forward from the tail to the head by wriggling along inclined planes, making so many dips in the undulating back. There is no need to return to this stercoral mechanism after the master has done with it. We now know the reasons that procured the Lily-beetle an ignominious title, confined to the official records: the grub makes itself an overcoat of its excrements. Once the garment is completed so as to cover the whole of the creature's dorsal surface, the clothing-factory does not cease work on that score. At the back a fresh hem is added from moment to moment; but the overlapping superfluity in front drops off of its own weight at the same time. The coat of dung is under continual repair, being renovated and lengthened at one end as it wears and grows shorter at the other. Sometimes also the stuff is too thick and the heap capsizes. The denuded grub recks nothing of the lost overcoat; its obliging intestine repairs the disaster without delay. Whether by reason of the clipping that results from the excessive length of a piece which is always on the loom, or of accidents that cause a part or the whole of the load to fall off, the grub of the Crioceris leaves accumulations of dirt in its track, till the lily, the symbol of purity, becomes a very cess-pool. When the leaves have been browsed, the stem next loses its cuticle, thanks to the nibbling of the grub, and is reduced to a ragged distaff. The flowers even, which have opened by now, are not spared: their beautiful ivory chalices are changed into latrines. The perpetrator of the misdeed embarks on his career of defilement early. I wanted to see him start, to watch him lay the first course of his excremental masonry. Does he serve an apprenticeship? Does he work badly at first, then a little better and then well? I now know all about it: there is no noviciate, there are no clumsy attempts; the workmanship is perfect from the outset, the product ejected spreads over the hinder part. Let me tell you what I saw. The eggs are laid in May, on the under surface of the leaves, in short trails averaging from three to six. They are cylindrical, rounded at both ends, of a bright orange-red, glossy and varnished with a glutinous wash which makes them stick to the leaves throughout their length. The hatching takes ten days. The shell of the egg, now a little wrinkled, but still of a bright orange colour, retains its position, so that the group of eggs, apart from its slightly withered appearance, remains just as it was. The young larva measures a millimetre and a half2 in length. The head and legs are black, the rest of the body a dull amber-red. On the first segment of the thorax is a brown sash, interrupted in the middle; lastly, there is a small black speck on each side, behind the third segment. This is the initial costume. Presently orange-red will take the place of the pale amber. The tiny creature, which is exceedingly fat, sticks to the leaf with its short legs and also with its hind-quarters, which act as a lever and push the round belly forwards. The motion reminds you of a cripple sitting in a bowl. 2 .959 inch.—Translator's Note. The grubs emerging from any one group of eggs at once begin to browse, each beside the empty skin of its egg. Here, singly, they nibble and dig themselves a little pit in the thickness of the leaf, while sparing the cuticle of the opposite surface. This leaves a translucent floor, a support which enables them to consume the walls of the excavation without risking a fall. Seeking for better pasture, they move lazily on. I see them scattered at random; a few of them are grouped in the same trench; but I never see them browsing economically abreast as Réaumur relates. There is no order, no understanding between messmates, contemporaries though they be and all sprung from the same row of eggs. Nor is any heed paid to economy: the lily is so generous! Meanwhile, the paunch swells and the intestine labours. Here we are! I see the first bit of the overcoat evacuated. As is natural in extreme infancy, it is liquid and there is not much of it. The scanty flow is used all the same and is laid methodically, right at the far end of the back. Let the little grub be. In less than a day, piece by piece, it will have made itself a suit. The artist is a master from the first attempt. If its baby-flannel is so good to start with, what will the future ulster be, when the stuff, brought to perfection, is of much better quality? Let us proceed; we know what we want to know concerning the talents of this manufacturer of excremental broadcloth. What is the purpose of this nasty great-coat? Does the grub employ it to keep itself cool, to protect itself against the attacks of the sun? It is possible: a tender skin need not be afraid of blistering under such a soothing poultice. Is it the grub's object to disgust its enemies? This again is possible: who would venture to set tooth to such a heap of filth? Or can it be simply a caprice of fashion, an outlandish fancy? I will not say no. We have had the crinoline, that senseless bulwark of steel hoops; we still have the extravagant stove-pipe hat, which tries to mould our heads in its stiff sheath. Let us be indulgent to the evacuator nor disparage his eccentric wardrobe. We have eccentricities of our own. To feel our way a little in this delicate question, we will question the near kinsmen of the Lily-beetle. In my acre or two of pebbles I have planted a bed of asparagus. The crop, from the culinary point of view, will never repay me for my trouble: I am rewarded in another fashion. On the scanty shoots which I allow to display themselves freely in plumes of delicate green, two Crioceres abound in the spring: the field species (C. campestris, LIN.) and the twelve-spotted species (C. duodecimpunctata, LIN.). A splendid windfall, far better than any bundle of asparagus. The first has a tricolor costume which is not without merit. Blue wing-cases, braided with white on the outer edge and each adorned with three white dots; a red corselet, with a blue disk in the centre. Its eggs are olive-green and cylindrical and, instead of lying flat, grouped in short lines, after the manner of the lily-dweller's, occur singly and stand on end on the leaves of the asparagus-plant, on the twigs, on the flower-buds, more or less everywhere, without any fixed order. Though living in the open air on the leaves of its plant and thus exposed to all the various perils that may threaten the Lily-grub, the larva of the Field Crioceris knows nothing whatever of the art of sheltering itself beneath a layer of ordure. It goes through life naked and always perfectly clean. It is of a bright greenish yellow, fairly fat behind and thinner in front. Its principal organ of locomotion is the end of the intestine, which protrudes, curves like a flexible finger, clasps the twig and supports the creature while pushing it forward. The true legs, which are short and placed too far in front with regard to the length of the body, would find it very difficult by themselves to drag the heavy mass that comes after. Their assistant, the anal finger, is remarkably strong. With no support, the larva turns over, head downwards, and remains suspended when shifting from one sprig to another. This Jack-in-the-bowl is a rope-dancer, a consummate acrobat, performing its evolutions amid the slender sprigs without fear of a fall. Its attitude in repose is curious. The heavy stern rests on the two hind-legs and especially on the crooked finger, the end of the intestine. The fore-part is lifted in a graceful curve, the little black head is raised and the creature looks rather like the crouching Sphinx of antiquity. This pose is common at times of slumber and blissful digestion in the sun. An easy prey is this naked, plump, defenceless grub, snoozing in the heat of a blazing day. Various Gnats, of humble size, but very likely terribly treacherous, haunt the foliage of the asparagus. The larva of the Crioceris, motionless in its sphinx-like attitude, does not appear to be on its guard against them, even when they come buzzing above its rump. Can they be as harmless as their peaceful frolics seem to proclaim? It is extremely doubtful: the Fly rabble are not there merely to imbibe the scanty exudations of the plant. Experts in mischief, they have no doubt hastened hither with another object. And, in truth, on the greater number of the Crioceris-larvæ we find, adhering firmly to the skin, certain white specks, very small and of a china-white. Can these be the sowing of a bandit, the spawn of a Midge? I collect the grubs marked with these white specks and rear them in captivity. A month later, about the middle of June, they shrivel, wrinkle and turn brown. All that is left of them is a dry skin which tears from end to end, half uncovering a Fly-pupa. A few days later, the parasite emerges. It is a small, greyish Fly, fiercely bristling with sparse hairs, half the size of the House-fly, whom it resembles slightly. It belongs to the Tachina group, who, in their larval form, so often inhabit the bodies of caterpillars. The white spots sprinkled over the larva of the Crioceris were the eggs of the hateful Fly. The vermin born of those eggs have perforated the victim's paunch. By subtle wounds, which cause little pain and are almost immediately healed, they have penetrated the body, reaching the humours in which the entrails are bathed. At first the larva invaded is not aware of its danger; it continues to perform its rope-dancer's gymnastics, to fill its belly and to take its siestas in the sun, as though nothing serious had occurred. Reared in a glass tube and often examined under the lens, my parasite-ridden larvæ betray no uneasiness. The fact is that the Tachina's children display an infernal judgment in their first actions. Until the moment when they are ready for the transformation, their portion of game has to hold out, must be kept fresh and alive. They therefore gorge themselves with the reserves intended for future use, the fats, the savings which the Crioceris hoards in view of the remodelling whence the perfect insect will emerge; they consume what is not essential to the life of the moment and are very careful not to touch the organs which are indispensable at the present time. If these received a bite, the host would die and so would they. Towards the end of their growth, prudence and discretion being no longer essential, they make a complete clearance of the victim, leaving only the skin, which will serve them for a shelter. One satisfaction is vouchsafed me in these horrible orgies: I see that the Tachina in her turn is subjected to severe reductions. How many were there on the larva's back? Perhaps eight, ten or more. One Midge, never more than one, comes out of the victim's skin, for the morsel is too small to provide food for many. What has become of the others? Has there been an internecine battle inside the poor wretch's body? Have they eaten one another up, leaving only the strongest to survive, or the one most favoured by the chances of the fight? Or has one of them, earlier developed than the rest, found himself master of the stronghold and have the others preferred to die outside rather than enter a grub already occupied, where famine would be rife if the messmates numbered even two? I am all for mutual extermination. Kinsman's flesh or stranger's flesh must be all one to the fangs of the vermin swarming in the Crioceris' belly. Fierce though the competition is among these bandits, the Beetle's race does not threaten to die out. I review the innumerable troop on my asparagus-bed. A good half of them have Tachina-eggs plainly visible as tiny white specks on their green skins. The blemished larvæ tell me of a paunch already or on the point of being invaded. On the other hand, it is doubtful whether those which are unscathed will all remain in that condition. The malefactor is incessantly prowling around the green plumes, watching for a favourable opportunity. Many larvæ free from white spots to-day will show them to-morrow or some other day, so long as the Fly's season lasts. I estimate that the vast majority of the troop will end by being infested. My rearing-experiments tell me much on this point. If I do not make a careful selection when I am stocking my wire-gauze-covers, if I go to work at random in picking the branches colonized with larvæ, I obtain very few adult Crioceres; nearly all of them are resolved into a cloud of Midges. If it were possible for us to wage war effectually upon an insect, I should advise asparagus-growers to have recourse to the Tachina, though I should cherish no illusions touching the results of the expedient. The exclusive tastes of the insect auxiliary draw us into a vicious circle: the remedy allays the evil, but the evil is inseparable from the remedy. To rid ourselves of the ravages of the asparagus-beds, we should need a great many Tachinæ; and to obtain a great many Tachinæ we should first of all need a great many ravagers. Nature's equilibrium balances things as a whole. Whenever Crioceres abound, the Midges that reduce them arrive in numbers; when Crioceres become rare, the Midges decrease, but are always ready to return in masses and repress a surplus of the others during a return of prosperity. Under its thick mantle of ordure the grub of the Lily-beetle escapes the troubles so fatal to its cousin of the asparagus. Strip it of its overcoat: you will never find the terrible white specks upon its skin. The method of preservation is most effective. Would it not be possible to find a defensive system of equal value without resorting to detestable filth? Yes, of course: the insect need only house itself under a covering where there would be nothing to fear from the Fly's eggs. This is what the Twelve-spotted Crioceris does, occupying the same quarters as the Field Crioceris, from whom she differs in size, being rather larger, and still more in her costume, which is rusty red all over, with twelve black spots distributed symmetrically on the wing-cases. Her eggs, which are a deep olive-green and cylindrical, pointed at one pole and squared off at the other, closely resemble those of the Field Crioceris and, like these, usually stand up on the supporting surface, to which they are fastened by the square end. It would be easy to confuse the two if we had not the position which they occupy to guide us. The Field Crioceris fastens her eggs to the leaves and the thin sprays; the other plants them exclusively on the still green fruit of the asparagus, globules the size of a pea. The grubs have to open a tiny passage for themselves and to make their own way into the fruit, of which they eat the pulp. Each globule harbours one larva, no more, or the ration would be insufficient. Often, however, I see two, three or four eggs on the same fruit. The first grub hatched is the one favoured by luck. He becomes the owner of the pill, an intolerant owner capable of wringing the neck of any who should come and sit down at table beside him. Always and everywhere this pitiless competition! The grub of the Twelve-spotted Crioceris is a dull white, with an interrupted black scarf on the first segment of the thorax. This sedentary creature has none of the talents of the acrobat grazing on the swaying foliage of the asparagus; it cannot take a grip with its posterior, turned into a prehensile finger. What use would it have for such a prerogative, loving repose as it does and destined to put on fat in its cell, without roaming in quest of food? In the same group each species has its own gifts, according to the kind of life that awaits it. It is not long before the occupied fruit falls to the ground. Day by day, it loses its green colour as the pulp is consumed. It becomes, at last, a pretty, diaphanous opal sphere, while the berries which have not been injured ripen on the plant and acquire a rich scarlet hue. When there is nothing left to eat inside the skin of its pill, the grub makes a hole in it and goes underground. The Tachinæ have spared it. Its opal box, the hard rind of the berry, has ensured its safety just as well as a filthy overcoat would have done and perhaps even better. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jean-Henri Fabre (2009). The Glow-Worm and Other Beetles. Urbana, Illinois: Project Gutenberg. Retrieved October https://www.gutenberg.org/cache/epub/27868/pg27868-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

THE CRIOCERES

Fabre's Book of Insects by Jean-Henri Fabre, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . THE SISYPHUS CHAPTER XIII. THE SISYPHUS You are not tired, I hope, of hearing about the Scavenger Beetles with a talent for making balls. I have told you of the Sacred Beetle and of the Spanish Copris, and now I wish to say a few words of yet another of these creatures. In the insect world we meet with a great many model mothers: it is only fair, for once to draw attention to a good father. Now a good father is rarely seen except among the higher animals. The bird is excellent in this respect, and the furred folk perform their duties honourably. Lower in the scale of living creatures the father is generally indifferent to his family. Very few insects are exceptions to this rule. This heartlessness, which would be detestable in the higher ranks of the animal kingdom, where the weakness of the young demands prolonged care, is excusable among insect fathers. For the robustness of the new-born insect enables it to gather its food unaided, provided it be in a suitable place. When all that the Pieris need do for the safety of the race is to lay her eggs on the leaves of a cabbage, of what use would a father’s care be? The mother’s botanical [ ]instinct needs no assistance. At laying-time the other parent would be in the way. 199 Most insects adopt this simple method of upbringing. They merely choose a dining-room which will be the home of the family once it is hatched, or else a place that will allow the young ones to find suitable fare for themselves. There is no need for the father in such cases. He generally dies without lending the least assistance in the work of setting up his offspring in life. Things do not always happen, however, in quite such a primitive fashion. There are tribes that provide a dowry for their families, that prepare board and lodging for them in advance. The Bees and Wasps in particular are masters in the industry of making cellars, jars, and satchels, in which the ration of honey is hoarded: they are perfect in the art of creating burrows stocked with the game that forms the food of their grubs. Well, this enormous labour, which is one of building and provisioning combined, this toil in which the insect’s whole life is spent, is done by the mother alone. It wears her out; it utterly exhausts her. The father drunk with sunlight, stands idle at the edge of the workyard, watching his plucky helpmate at her job. Why does he not lend the mother a helping hand? It is now or never. Why does he not follow the example of the Swallow couple, both of whom bring their bit of straw, their blob of mortar to the building and their [ ]Midge to the young ones? He does nothing of the kind. Possibly he puts forward his comparative weakness as an excuse. It is a poor argument; for to cut a disk out of a leaf, to scrape some cotton from a downy plant, to collect a little bit of cement in muddy places would not overtax his strength. He could very easily help, at any rate as a labourer; he is quite fit to gather materials for the mother, with her greater intelligence, to fit in place. The real reason of his inactivity is sheer incapability. 200 It is strange that the most gifted of the industrial insects should know nothing of a father’s duties. One would expect the highest talents to be developed in him by the needs of the young; but he remains as dull-witted as a Butterfly, whose family is reared at so small a cost. We are baffled at every turn by the question: Why is a particular instinct given to one insect and denied to another? It baffles us so thoroughly that we are extremely surprised when we find in the scavenger the noble qualities that are denied to the honey-gatherer. Various Scavenger Beetles are accustomed to help in the burden of housekeeping, and know the value of working in double harness. The Geotrupes couple, for instance, prepare their larva’s food together: the father lends his mate the assistance of his powerful press in the manufacture of the tightly packed sausage-shaped ration. He is a splendid [ ]example of domestic habits, and one extremely surprising amid the general egoism. 201 To this example my constant studies of the subject have enabled me to add three others, all furnished by the Guild of Scavengers. One of them is the Sisyphus, the smallest and most zealous of all our pill-rollers. He is the liveliest and most agile of them all, and recks nothing of awkward somersaults and headlong falls on the impossible roads to which his obstinacy brings him back again and again. It was in reference to these wild gymnastics that Latreille gave him the name of Sisyphus. As you know, that unhappy wretch of classical fame had a terrible task. He was forced to roll a huge stone uphill; and each time he succeeded in toiling to the top of the mountain the stone slipped from his grasp and rolled to the bottom. I like this myth. It is the history of a good many of us. So far as I am concerned, for half a century and more I have painfully climbed the steep ascent, spending my strength recklessly in the struggle to hoist up to safety that crushing burden, my daily bread. Hardly is the loaf balanced when it slips off, slides down, and is lost in the abyss. The Sisyphus with whom we are now concerned knows none of these bitter trials. Untroubled by the steep slopes he gaily trundles his load, at one time bread for himself, at another bread for his children. He is very [ ]scarce in these parts; and I should never have managed to secure a suitable number of subjects for my studies had it not been for an assistant whom I have already mentioned more than once. 202 I speak of my little son Paul, aged seven. He is my enthusiastic companion on my hunting expeditions, and knows better than any one of his age the secrets of the Cicada, the Locust, the Cricket, and especially the Scavenger Beetle. Twenty paces away his sharp eyes will distinguish the real mound that marks a burrow from casual heaps of earth. His delicate ears catch the Grasshopper’s faint song, which is quite unheard by me. He lends me his sight and hearing; and I, in exchange, present him with ideas, which he receives attentively. Little Paul has his own insect-cages, in which the Sacred Beetle makes pears for him; his own little garden, no larger than a pocket-handkerchief, where he grows beans, often digging them up to see if the tiny roots are any longer; his forest plantation, in which stand four oaks a hand’s-breadth high, still furnished on one side with the acorn that feeds them. It all makes a welcome change from grammar, which gets on none the worse for it. When the month of May is near at hand Paul and I get up early one morning—so early that we start without our breakfast—and we explore, at the foot of the mountain, [ ]the meadows where the flocks have been. Here we find the Sisyphus. Paul is so zealous in his search that we soon have a sufficient number of couples. 203 All that is needed for their well-being is a wire-gauze cover, with a bed of sand and a supply of their food—to obtain which we too turn scavengers. These creatures are so small, hardly the size of a cherry-stone! And so curious in shape withal! A dumpy body, the hinder end of which is pointed, and very long legs, resembling a Spider’s when outspread. The hind-legs are of amazing length, and are curved, which is most useful for clasping and squeezing the pellet. Soon the time comes for establishing the family. With equal zeal father and mother alike take part in kneading, carting, and stowing away the provisions for the young ones. With the cleaver of the fore-legs a morsel of the right size is cut from the food placed at their disposal. The two insects work at the piece together, giving it little pats, pressing it, and shaping it into a ball as large as a big pea. As in the Sacred Beetle’s workshop, the accurately round shape is obtained without the mechanical trick of rolling the ball. The material is modelled into a sphere before it is moved, before it is even loosened from its support. Here, once more, we have an expert in geometry familiar with the best form for preserving food.[ ] 204 The ball is soon ready. It must now, by vigorous rolling, be given the crust which will protect the soft stuff within from becoming too dry. The mother, who can be recognised by her slightly larger size, harnesses herself in the place of honour, in front. With her long hind-legs on the ground and her fore-legs on the ball, she hauls it towards her, backwards. The father pushes behind in the reverse position, head downwards. It is precisely the same method as that of the Sacred Beetle when working in twos, but it has another object. The Sisyphus team conveys a store of food for the grubs, whereas the big pill-rollers trundle a banquet which they themselves will eat up underground. THE SISYPHUS The mother harnesses herself in the place of honour, in front. The father pushes behind in the reverse position, head downwards The couple start off along the ground. They have no definite goal, but walk in a direct line, without regard to the obstacles that lie in the way. In this backward march the obstacles could not be avoided; but even if they were seen the Sisyphus would not try to go round them. For she even makes obstinate attempts to climb the wire-work of my cage. This is an arduous and impossible task. Clawing the meshes of the gauze with her hind-legs the mother pulls the load towards her; then, putting her fore-legs round it, she holds it suspended in air. The father, finding nothing to stand upon, clings to the ball—encrusts himself in it, so to speak, thus adding his weight to that of the lump, and taking no further pains. The effort is too great to last. [ ]The ball and its rider, forming one mass, fall to the floor. The mother, from above, looks down for a moment in surprise, and then drops to recover the load and renew her impossible attempt to scale the side. After repeated falls the climb is abandoned. 205 Even on level ground the carting is not carried on without difficulty. At every moment the load swerves on some mound made by a bit of gravel; and the team topple over and kick about, upside down. This is a trifle, the merest trifle. These tumbles, which so often fling the Sisyphus on his back, cause him no concern; one would even think he liked them. After all, the ball has to be hardened and made of the right consistency. And this being the case, bumps falls, and jolts are all part of the programme. This mad steeple-chasing goes on for hours. At last the mother, regarding the work as completed, goes off a little way in search of a suitable spot. The father mounts guard, squatting on the treasure. If his companion’s absence be unduly long, he relieves his boredom by spinning the ball nimbly between his uplifted hind legs. He treats his precious pellet as a juggler treats his ball. He tests its perfect shape with his curved legs, the branches of his compasses. No one who sees him frisking in that jubilant attitude can doubt his lively satisfaction—the satisfaction of a father assured of his children’s future.[ ] 206 “It is I,” he seems to say, “I who kneaded this round loaf, I who made this bread for my sons!” And he lifts on high, for all to see, this magnificent testimony to his industry. Meanwhile the mother has chosen a site for the burrow. A shallow pit is made, a mere beginning of the work. The ball is rolled near it. The father, that vigilant guardian, does not let go, while the mother digs with her legs and forehead. Soon the hollow is big enough to hold the pellet. She insists on having it quite close to her; she must feel it bobbing up and down behind her, on her back, safe from parasites, before she decides to go farther. She is afraid of what might happen to it if it were left on the edge of the burrow until the home were completed. There are plenty of Midges and other such insects to grab it. One cannot be too careful. The ball therefore is inserted, half in and half out of the partly-formed basin. The mother, underneath, gets her legs round it and pulls: the father above, lets it down gently, and sees that the hole is not choked up with falling earth. All goes well. The digging is resumed and the descent continues, always with the same caution; one of the insects pulling the load, the other regulating the drop and clearing away anything that might hinder the operation. A few more efforts, and the ball disappears underground with the two miners. What [ ]follows for some time to come can only be a repetition of what has already been done. We must wait half a day or so. 207 If we keep careful watch we shall see the father come up again to the surface by himself, and crouch in the sand near the burrow. Detained below by duties in which her companion can be of no assistance to her, the mother usually postpones her appearance till the morrow. At last she shows herself. The father leaves the place where he was snoozing, and joins her. The reunited couple go back to the spot where their food-stuffs are to be found, and having refreshed themselves they gather up more materials. The two then set to work again. Once more they model, cart, and store the ball together. I am delighted with this constancy. That it is really the rule I dare not declare. There must, no doubt, be flighty, fickle Beetles. No matter: the little I have seen gives me a high opinion of the domestic habits of the Sisyphus. It is time to inspect the burrow. At no great depth we find a tiny niche, just large enough to allow the mother to move round her work. The smallness of the chamber tells us that the father cannot remain there for long. When the studio is ready, he must go away to leave the sculptress room to turn. The contents of the cellar consist of a single ball, a [ ]masterpiece of art. It is a copy of the Sacred Beetle’s pear on a very much reduced scale, its smallness making the polish of the surface and the elegance of the curves all the more striking. Its diameter, at the broadest point, measures one-half to three-quarters of an inch. 208 One more observation about the Sisyphus. Six couples under the wire-gauze cover gave me fifty-seven pears containing one egg each—an average of over nine grubs to each couple. The Sacred Beetle is far from reaching this figure. To what cause are we to attribute this large brood? I can see but one: the fact that the father works as well as the mother. Family burdens that would exceed the strength of one are not too heavy when there are two to bear them. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jean-Henri Fabre (2021). Fabre's Book of Insects. Urbana, Illinois: Project Gutenberg. Retrieved October https://www.gutenberg.org/cache/epub/67000/pg67000-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

THE SISYPHUS

1811 Dictionary in the Vulgar Tongue: Section S

1811 Dictionary in the Vulgar Tongue:  Section B

Oliver Twist: Chapter XIX

Moby-Dick; or The Whale, by Herman Melville is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here: [ ]. Chapter 40: Midnight, Forecastle LINK TO TABLE OF LINK CHAPTER 40. Midnight, Forecastle. HARPOONEERS AND SAILORS. (Foresail rises and discovers the watch standing, lounging, leaning, and lying in various attitudes, all singing in chorus.) 1ST NANTUCKET SAILOR. Oh, boys, don’t be sentimental; it’s bad for the digestion! Take a tonic, follow me! (Sings, and all follow.) MATE’S VOICE FROM THE QUARTER-DECK. Eight bells there, forward! 2ND NANTUCKET SAILOR. Avast the chorus! Eight bells there! d’ye hear, bell-boy? Strike the bell eight, thou Pip! thou blackling! and let me call the watch. I’ve the sort of mouth for that—the hogshead mouth. So, so, (thrusts his head down the scuttle,) Star-bo-l-e-e-n-s, a-h-o-y! Eight bells there below! Tumble up! DUTCH SAILOR. Grand snoozing to-night, maty; fat night for that. I mark this in our old Mogul’s wine; it’s quite as deadening to some as filliping to others. We sing; they sleep—aye, lie down there, like ground-tier butts. At ’em again! There, take this copper-pump, and hail ’em through it. Tell ’em to avast dreaming of their lasses. Tell ’em it’s the resurrection; they must kiss their last, and come to judgment. That’s the way—that’s it; thy throat ain’t spoiled with eating Amsterdam butter. FRENCH SAILOR. Hist, boys! let’s have a jig or two before we ride to anchor in Blanket Bay. What say ye? There comes the other watch. Stand by all legs! Pip! little Pip! hurrah with your tambourine! PIP. (Sulky and sleepy.) Don’t know where it is. FRENCH SAILOR. Beat thy belly, then, and wag thy ears. Jig it, men, I say; merry’s the word; hurrah! Damn me, won’t you dance? Form, now, Indian-file, and gallop into the double-shuffle? Throw yourselves! Legs! legs! ICELAND SAILOR. I don’t like your floor, maty; it’s too springy to my taste. I’m used to ice-floors. I’m sorry to throw cold water on the subject; but excuse me. MALTESE SAILOR. Me too; where’s your girls? Who but a fool would take his left hand by his right, and say to himself, how d’ye do? Partners! I must have partners! SICILIAN SAILOR. Aye; girls and a green!—then I’ll hop with ye; yea, turn grasshopper! LONG-ISLAND SAILOR. Well, well, ye sulkies, there’s plenty more of us. Hoe corn when you may, say I. All legs go to harvest soon. Ah! here comes the music; now for it! AZORE SAILOR. (Ascending, and pitching the tambourine up the scuttle.) Here you are, Pip; and there’s the windlass-bitts; up you mount! Now, boys! (The half of them dance to the tambourine; some go below; some sleep or lie among the coils of rigging. Oaths a-plenty.) AZORE SAILOR. (Dancing) Go it, Pip! Bang it, bell-boy! Rig it, dig it, stig it, quig it, bell-boy! Make fire-flies; break the jinglers! PIP. Jinglers, you say?—there goes another, dropped off; I pound it so. CHINA SAILOR. Rattle thy teeth, then, and pound away; make a pagoda of thyself. FRENCH SAILOR. Merry-mad! Hold up thy hoop, Pip, till I jump through it! Split jibs! tear yourselves! TASHTEGO. (Quietly smoking.) That’s a white man; he calls that fun: humph! I save my sweat. OLD MANX SAILOR. I wonder whether those jolly lads bethink them of what they are dancing over. I’ll dance over your grave, I will—that’s the bitterest threat of your night-women, that beat head-winds round corners. O Christ! to think of the green navies and the green-skulled crews! Well, well; belike the whole world’s a ball, as you scholars have it; and so ’tis right to make one ballroom of it. Dance on, lads, you’re young; I was once. 3D NANTUCKET SAILOR. Spell oh!—whew! this is worse than pulling after whales in a calm—give us a whiff, Tash. (They cease dancing, and gather in clusters. Meantime the sky darkens—the wind rises.) LASCAR SAILOR. By Brahma! boys, it’ll be douse sail soon. The sky-born, high-tide Ganges turned to wind! Thou showest thy black brow, Seeva! MALTESE SAILOR. (Reclining and shaking his cap.) It’s the waves—the snow’s caps turn to jig it now. They’ll shake their tassels soon. Now would all the waves were women, then I’d go drown, and chassee with them evermore! There’s naught so sweet on earth—heaven may not match it!—as those swift glances of warm, wild bosoms in the dance, when the over-arboring arms hide such ripe, bursting grapes. SICILIAN SAILOR. (Reclining.) Tell me not of it! Hark ye, lad—fleet interlacings of the limbs—lithe swayings—coyings—flutterings! lip! heart! hip! all graze: unceasing touch and go! not taste, observe ye, else come satiety. Eh, Pagan? (Nudging.) TAHITAN SAILOR. (Reclining on a mat.) Hail, holy nakedness of our dancing girls!—the Heeva-Heeva! Ah! low veiled, high palmed Tahiti! I still rest me on thy mat, but the soft soil has slid! I saw thee woven in the wood, my mat! green the first day I brought ye thence; now worn and wilted quite. Ah me!—not thou nor I can bear the change! How then, if so be transplanted to yon sky? Hear I the roaring streams from Pirohitee’s peak of spears, when they leap down the crags and drown the villages?—The blast! the blast! Up, spine, and meet it! (Leaps to his feet.) PORTUGUESE SAILOR. How the sea rolls swashing ’gainst the side! Stand by for reefing, hearties! the winds are just crossing swords, pell-mell they’ll go lunging presently. DANISH SAILOR. Crack, crack, old ship! so long as thou crackest, thou holdest! Well done! The mate there holds ye to it stiffly. He’s no more afraid than the isle fort at Cattegat, put there to fight the Baltic with storm-lashed guns, on which the sea-salt cakes! 4TH NANTUCKET SAILOR. He has his orders, mind ye that. I heard old Ahab tell him he must always kill a squall, something as they burst a waterspout with a pistol—fire your ship right into it! ENGLISH SAILOR. Blood! but that old man’s a grand old cove! We are the lads to hunt him up his whale! ALL. Aye! aye! OLD MANX SAILOR. How the three pines shake! Pines are the hardest sort of tree to live when shifted to any other soil, and here there’s none but the crew’s cursed clay. Steady, helmsman! steady. This is the sort of weather when brave hearts snap ashore, and keeled hulls split at sea. Our captain has his birthmark; look yonder, boys, there’s another in the sky—lurid-like, ye see, all else pitch black. DAGGOO. What of that? Who’s afraid of black’s afraid of me! I’m quarried out of it! SPANISH SAILOR. (Aside.) He wants to bully, ah!—the old grudge makes me touchy (Advancing.) Aye, harpooneer, thy race is the undeniable dark side of mankind—devilish dark at that. No offence. DAGGOO (grimly). None. ST. JAGO’S SAILOR. That Spaniard’s mad or drunk. But that can’t be, or else in his one case our old Mogul’s fire-waters are somewhat long in working. 5TH NANTUCKET SAILOR. What’s that I saw—lightning? Yes. SPANISH SAILOR. No; Daggoo showing his teeth. DAGGOO (springing). Swallow thine, mannikin! White skin, white liver! SPANISH SAILOR (meeting him). Knife thee heartily! big frame, small spirit! ALL. A row! a row! a row! TASHTEGO (with a whiff). A row a’low, and a row aloft—Gods and men—both brawlers! Humph! BELFAST SAILOR. A row! arrah a row! The Virgin be blessed, a row! Plunge in with ye! ENGLISH SAILOR. Fair play! Snatch the Spaniard’s knife! A ring, a ring! OLD MANX SAILOR. Ready formed. There! the ringed horizon. In that ring Cain struck Abel. Sweet work, right work! No? Why then, God, mad’st thou the ring? MATE’S VOICE FROM THE QUARTER-DECK. Hands by the halyards! in top-gallant sails! Stand by to reef topsails! ALL. The squall! the squall! jump, my jollies! (They scatter.) PIP (shrinking under the windlass). Jollies? Lord help such jollies! Crish, crash! there goes the jib-stay! Blang-whang! God! Duck lower, Pip, here comes the royal yard! It’s worse than being in the whirled woods, the last day of the year! Who’d go climbing after chestnuts now? But there they go, all cursing, and here I don’t. Fine prospects to ’em; they’re on the road to heaven. Hold on hard! Jimmini, what a squall! But those chaps there are worse yet—they are your white squalls, they. White squalls? white whale, shirr! shirr! Here have I heard all their chat just now, and the white whale—shirr! shirr!—but spoken of once! and only this evening—it makes me jingle all over like my tambourine—that anaconda of an old man swore ’em in to hunt him! Oh, thou big white God aloft there somewhere in yon darkness, have mercy on this small black boy down here; preserve him from all men that have no bowels to feel fear! About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Urbana, Illinois: Project Gutenberg. Retrieved April 2022 from Melville, Herman, 2001. Moby-Dick: or The Whale. https://www.gutenberg.org/files/2701/2701-h/2701-h.htm#link2HCH0040 This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

Moby-Dick; or The Whale: Chapter 40 - Midnight, Forecastle

We're talking about triaging bugs in software systems. So at a very simple level, this topic comes down to the question: Is your software working in the hands of your users? If your app, or your game, or your web service isn't working perfectly for every interaction, then it's time to think about bug triaging. For many systems, there are going to be some software bugs that are tolerable if they happen infrequently, while other bugs if they happen even once, are critical and need immediate action. So bug triage is all about making those judgment calls quickly and accurately. This video is the first in a three-part series on how to approach software bug triage. Part 1: Bug Triaging Principles Part 2: Tips for Effective + Efficient Bug Triage Part 3: Developing a Bug Triage Process with Your Team Transcript 0:15 okay so let's set the stage here 0:17 we're talking about triaging bugs in 0:19 software systems 0:20 so at a very simple level this topic 0:23 comes down to the question 0:24 is your software working in the hands of 0:27 your users 0:28 if your app or your game or your web 0:31 service 0:31 isn't working perfectly for every 0:33 interaction then it's time to think 0:35 about bug triaging 0:37 for many systems there are going to be 0:39 some software bugs that are tolerable if 0:41 they happen infrequently 0:43 while other bugs if they happen even 0:44 once are critical 0:46 and need immediate action so bug triage 0:49 is all about making those judgment calls 0:51 quickly and accurately 0:55 so it's useful to break bugstown into 0:57 three categories for our discussion 0:59 today 1:00 there are those bugs that need immediate 1:01 action these are things that require 1:03 some developer intervention maybe 1:05 rolling back a recent release or 1:07 flipping a feature flag to get the bug 1:09 out of the hands of users 1:10 and get back onto a stable version of 1:12 the software there are those bugs that 1:15 do not require immediate action now but 1:18 may require action in the future 1:20 if they become more impactful let's say 1:22 if they happen more frequently or affect 1:24 more users 1:26 and third there are those bugs that 1:28 regardless of their frequency 1:30 are safe to ignore of these three 1:33 categories it's really the first two 1:35 that are most interesting for our 1:36 purposes today 1:37 and those are the ones we're going to 1:38 focus on 1:42 so when it comes to determining which 1:44 category a given bug falls into 1:46 there are really two main workflows 1:49 there's what we call reactive triage 1:51 and what we call periodic triage 1:53 reactive triage 1:55 is the scenario where a bug occurs or 1:58 something changes with a bug's frequency 2:00 and it requires someone on your team to 2:02 drop what they're doing and go 2:03 investigate it immediately 2:05 so these tend to be bugs that are high 2:08 impact 2:09 or affect a critical area of your system 2:12 so some examples here might be a new bug 2:15 that the system has never seen before 2:17 it might be an issue involving a bug 2:19 that was previously occurring at some 2:22 safe steady state frequency but now bug 2:24 snag has detected an anomalous spike in 2:26 the frequency of that bug 2:29 could be a bug in a critical area of 2:31 each system a bug that you previously 2:33 fixed 2:33 that has come back now in a future 2:35 release of the software 2:37 or it could be something to do with a 2:39 stability score 2:40 being off target for your project these 2:43 are all concepts we'll talk about more 2:45 but the crucial point here is that a key 2:47 category of bug triaging 2:49 is all about reactively jumping into bug 2:53 snag 2:53 figuring out what's going on and making 2:55 sure that 2:57 some immediate action isn't needed to 3:00 get a bug 3:00 away from your users 3:04 so when you're thinking about reactive 3:05 triage in 3:07 your project and within your team it's 3:10 really important to think about 3:12 which subset of your errors are going to 3:14 rise to the level of importance that you 3:16 want someone on your team 3:18 to effectively drop what they're doing 3:19 and go triage that bug immediately 3:23 once you've made that determination you 3:24 can configure bug snag via 3:26 the alerting and workflow engine to 3:28 notify your team via 3:30 team chat or via on-call alerting system 3:32 whenever one of the bugs that meets your 3:34 custom defined criteria 3:36 occurs so it's worth pointing out that 3:39 the 3:40 alerting and workflow engine is is 3:42 highly configurable 3:43 you decide when bug snag notifies you 3:45 and through what means 3:47 some examples of how you can use this to 3:50 your team's advantage 3:52 let's say you have a spike in errors 3:54 affecting your vip customers 3:56 where you define what it means for a 3:58 customer to be a vip 4:00 bug snag can detect that and 4:02 automatically open a pager duty incident 4:04 for you 4:05 fitting into your team's existing 4:06 on-call rotation 4:08 and bug remediation process 4:11 or let's say you work in a monolithic 4:13 code base where 4:15 each team works out of a different slack 4:17 channel but ultimately you share the 4:18 same code 4:20 you can configure bug snag to notify 4:22 your slack channel 4:24 about bugs in your team's part of the 4:26 monolith 4:27 and the possibilities are really 4:30 infinite from there 4:33 so most teams aren't going to triage 4:35 every single error 4:36 using a purely reactive workflow they're 4:40 going to be those bugs that 4:42 aren't critical enough that require 4:44 people to drop what they're doing 4:46 and go triage them immediately of course 4:49 this varies from team to team but this 4:51 is generally true 4:53 all bugs affecting your system need to 4:55 be reviewed and prioritized regularly 4:56 though 4:57 so an initial target that we recommend 5:00 is to have your team 5:01 triage your for review errors once per 5:04 day 5:05 this is especially important to do first 5:07 thing in the workday or 5:08 after lunch any time where there may 5:10 have been a lapse in coverage 5:13 and new bugs may have crept in or 5:16 previously triage bugs may have come 5:18 back into the for review state 5:20 and we'll talk about all that in greater 5:22 detail in a moment 5:25 let's quickly review the workflow 5:28 actions available 5:29 in bug snag when a bug is first detected 5:32 by bug snag 5:33 it goes into the open and for review 5:36 workflow states 5:37 and we'll talk more about the four 5:39 review workflow state because that's 5:41 really 5:41 key to triaging so when an error 5:45 is in an open error state there are some 5:47 key workflow actions you can perform on 5:49 the error 5:50 and these map back to those three 5:52 categories of errors we talked about at 5:53 the beginning right 5:54 things you want to fix immediately 5:56 things you may want to fix in the future 5:58 and things you're safe to ignore 6:00 so starting from 6:05 top left to right here snoozing an error 6:08 is something you can do to conditionally 6:09 reopen an error in the future and this 6:11 is something you would do 6:13 if an error is in that category where 6:15 you want to 6:17 keep an eye on it but you're not going 6:18 to fix it right now and you're only 6:19 going to address it 6:20 if it becomes more impactful you can 6:24 create an issue 6:25 to track the work related to an imminent 6:27 fix of a bug 6:28 so for example if you're using jira 6:32 this would be equivalent to clicking a 6:34 button in bugsmag which will create a 6:35 jira ticket 6:37 which will then be used in your sprint 6:39 or other work 6:40 uh work planning process 6:43 to track the work of actually going in 6:45 and making the necessary code or 6:47 infrastructure changes to remove the bug 6:51 you can mark a bug as fixed and this is 6:53 typically what you would do 6:54 for those category one bugs that you've 6:57 decided to fix right now 6:59 when you've taken some action to 7:00 remediate the bug 7:02 and when you mark a bug as fixed it will 7:05 only return to the for 7:06 for review state if it's seen again in a 7:08 future version of the code 7:10 and lastly you can ignore an open error 7:14 which will signify that you're not 7:16 planning to take any action on it 7:18 regardless of how frequently it may 7:20 occur in the future 7:22 during error triage you're typically 7:24 going to be taking these workflow 7:26 actions 7:26 from a specific error details view 7:29 inside bug snag 7:30 you can also take these workflow actions 7:33 from the inbox view and bug snag 7:35 which also gives you the ability to take 7:37 workflow actions on 7:38 more than one error at once we'll look 7:41 at some examples of doing this in the 7:43 product in just a moment 7:46 a key tip for error triaging and bug 7:49 snag 7:49 is to start your triaging workflow with 7:52 four review filter 7:53 in the bug snack inbox so if we look at 7:56 the screenshot below you'll see that 7:58 we're viewing the bug snag inbox 8:00 and that it's currently filtered to four 8:02 review errors and you can see this in 8:04 two key places 8:05 in the filter bar it says status for 8:07 review and in the left hand 8:10 column it says for review with 18 in 8:13 parentheses and that has 8:15 an active ui state and this signifies 8:17 that we're currently filtering for four 8:19 review errors there are 18 8:20 errors that need to be reviewed and the 8:22 tooltip there is giving us a hint it 8:23 says open errors that are awaiting 8:25 triage 8:26 so what we need to do if we imagine that 8:29 we're on this 8:30 team that's responsible for the software 8:32 that's being monitored by this bug snag 8:34 project here what we need to do is look 8:36 at every one of these errors currently 8:38 affecting our users 8:39 and determine its impact and then we 8:41 need to determine which of these 8:43 workflow actions that we just discussed 8:45 fixing snoozing creating an issue 8:47 ignoring etc. 8:48 is most appropriate given the current 8:50 impact of the bug 8:52 and given the current work that is on 8:54 our team's plate 8:57 so let's take a look at a project in bug 8:59 snag 9:00 so we can see some of these things in 9:01 action 9:03 if we go to this photosnap android 9:06 project 9:07 and have a look at the inbox we can see 9:10 that this project has quite a few 9:12 open errors and notice we're filtered to 9:15 areas that have occurred only in the 9:16 past 30 days 9:18 so it's likely that there are even more 9:19 than the 38 open is currently affecting 9:21 this 9:22 project but let's as we said have a look 9:25 at the four review errors so we can see 9:27 in the last 30 days there are 24 9:29 errors that are for review so we might 9:31 start our triaging here 9:33 and again what we're going to do is 9:35 we're going to look at every one of 9:36 these errors 9:38 in the for review set and we're going to 9:40 figure out 9:41 what the appropriate next step is for 9:43 each of these errors 9:46 one thing you might want to consider 9:47 doing at this point is sorting 9:49 the inbox either by total number of 9:51 events per error 9:52 so you can see this is the error that 9:55 had 9:56 the most events in the past 30 days or 9:59 you could sort by users affected as well 10:01 and you can see this one affected 56 10:03 users 10:05 this happens to be an application not 10:07 responding error 10:09 which is pretty severe so let's go and 10:12 take a look at that 10:15 so here we are on the error details 10:17 screen 10:18 this gives us a overview of all of the 10:22 specific information to do with this one 10:24 particular 10:26 defect in the application so we can see 10:29 again this affected 10:31 56 users it happened a total of 80 times 10:33 in the past 30 days 10:34 we can go between these tabs and see 10:37 more information about 10:39 how those 80 occurrences are distributed 10:41 across 10:42 specific users we can see which releases 10:45 of the software the bug has occurred in 10:47 os versions of end user devices and so 10:50 on 10:50 and if you're new to bug snag it's worth 10:54 pointing out that 10:55 all of these we call these pivots all 10:58 the information in these pivots can be 10:59 used to 11:00 filter down the view of this error even 11:03 more 11:04 so if we're only looking at os version 7 11:07 1 1 it goes down to 28 11:11 events and 24 users affected the point 11:13 is 11:14 you can use all of this information that 11:16 bug site gives you about the 11:18 frequency of the error the specific 11:22 device context in which this error has 11:25 been seen 11:26 to determine the impact and to determine 11:28 the next step 11:29 once you've determined what makes sense 11:32 to do for this you'd come up here 11:34 these are the error actions that we 11:35 talked about so this is where you would 11:37 create an issue 11:38 this is where you could mark it as fixed 11:40 so where you would snooze it 11:42 ignore it so let's say that we've just 11:45 shipped a fix for this and we don't 11:47 expect to see it in a future version of 11:49 the software anymore 11:50 then the next step would be to mark this 11:53 as fixed 11:55 here it's prompting us to add a comment 11:57 about why we think this has been 11:59 fixed and we can say something to the 12:01 effect of 12:03 fixed in last release mark is fixed 12:07 there you go now you can see that it's 12:08 fixed 12:10 and if we go to the comment and activity 12:12 view we can see 12:14 that this was fixed and here's my 12:16 comment explaining why 12:19 so you start your triaging workflow with 12:21 your four review errors 12:23 now your goal should be to get that 12:25 total number of four review errors down 12:27 to zero 12:28 on a regular basis and what it means 12:30 when you do that when you achieve bug 12:32 snag inbox zero 12:33 it means that all of your critical bugs 12:35 have been addressed and for any lower 12:37 priority 12:38 bugs you've determined the criteria at 12:40 which point you will take further action 12:42 on them in the future 12:46 a common question we get at this point 12:48 is when will bugs 12:50 ever go back into the for review state 12:52 and there are a few 12:53 key situations where this will happen 12:56 the obvious one is 12:57 newly introduced bugs bugs that bug 12:59 snake has never seen before 13:01 will continue to go in the for review 13:02 state for you to triage 13:04 but also any previously snoozed 13:07 bugs that have exceeded their previous 13:09 news thresholds will also go back into 13:11 the for review state 13:13 and any bugs that you've marked as fixed 13:14 that have happened in a new version of 13:16 your software 13:17 will also return to the for review state 13:20 and the reason for this is that 13:21 even though you've looked at these bugs 13:23 in the past now 13:24 their context has changed they've begun 13:27 to happen more frequently 13:29 or they've happened in a version of your 13:31 software where you're not expecting them 13:32 to happen and so in all of these cases 13:35 these are things that you want to be 13:36 looking at to be determining their 13:37 current impact 13:38 and whether you need to take some new 13:40 action based on this new information 13:43 so why aim for bug snag inbox zero well 13:46 first and foremost if you're regularly 13:48 getting your inbox down to 13:50 around zero errors for review it means 13:52 that when new errors do come in 13:54 to be reviewed your team can be more 13:56 efficient with their attention 13:58 because if you consider the case where 14:00 you're not getting anywhere close to 14:01 inbox 14:02 hero when someone comes in to do 14:03 periodic review they may have to sift 14:05 through 14:06 several errors that have been given 14:08 varying degrees of review 14:10 already but that's not necessarily clear 14:13 because a workflow action hasn't been 14:14 taken on those errors appropriately 14:17 so if you are getting to inbox hero 14:18 regularly it means that 14:20 the errors that your team looks at 14:21 during the triaging workflow are only 14:23 those errors that need to be considered 14:25 in their current context 14:28 the other thing about getting close to 14:30 inbox zero or hitting inbox zero on a 14:32 daily basis 14:33 is that it increases the likelihood that 14:34 your team is going to be engaged 14:36 with the periodic triaging process 14:38 because the lower that number is that's 14:40 for review the closer to zero 14:42 the more likely people are to want to 14:44 get that down to zero you know you 14:46 consider the case of 1000 errors to 14:49 review versus five errors to review 14:52 one is much more inviting than the other 14:54 as far as 14:55 you know someone on the team wanting to 14:56 go in and do the necessary work to get 14:58 those errors triaged 14:59 so try to hit inbox zero every day it's 15:02 going to make your team more engaged 15:03 it's going to allow them to spend time 15:05 in bug snag 15:10 efficiently 15:19 you

What Are the Best Practices for Triaging Software Bugs

I'm sure being a manager is not everyone's cup of tea. It has its own challenges that are quite unlike what we face as developers or engineers with our code. Dealing with people especially is a whole different ball game. Thought of transitioning into management? Or curious? I'll take you on my journey as an acting delivery manager and the little things that I learned. Some background I've been a web developer for 11 years, having worked on all sorts of products at many different companies. This story is set a few months back at Nintex, a company that makes automation software. There were hundreds of developers. I've since left the company to pursue my own things. At the beginning of the year, my delivery manager(DM) took extended paternity leave. I was offered the opportunity to be the acting DM for two months during his absence. I said yes, as it was a good chance to get a taste of what things are like on the other side. Getting prepared To make the transition smoother I . During this period I was shadowing my DM in the meetings and reporting to the stakeholders. I slowly took ownership of the feature works. took on the role unofficially a month earlier during the first few weeks of the unofficial period. What if I can't deliver a feature on time? What If I don't know a process? Would I micromanage? What if there is an urgent complaint case and we can't figure out the problem? So I had a chat with my DM before he left and was assured that the Engineering Director would have my back. There were many questions in my mind And things went wrong! Then the day arrived, and my DM was gone, and the . It was the release week, and while testing on the staging server, some tests failed. A mild panic sets in. As it was a cross-team effort, we had to coordinate with another team. And worked quickly to get it fixed before deployment to the production server. first two weeks turned out to be pretty bad After a lot of downtime from our cloud provider, Nintex finally had enough of it. We decided to immediately work on resiliency measures to reduce the impact of future downtime. But this put my team's carefully laid feature works plan into disarray. I had to figure out how to rearrange everything. Thankfully the product manager was understanding. Feature Delivery One thing I realized as a DM was there were more things to be aware of. As a developer, I would be deeply involved in the feature that I was working on. Not so much in what others were working on or upcoming work. . Being in the know of a lot of different things  at the same time introduces extra challenges—coordination, investigation, conversation, negotiation, cross-team collaboration, and so on. But as a DM, everything is important When it comes to the architecture and implementation, you don't need to be deeply involved as the developers. However, it is important to know at a high level. It helps in the planning and prioritization activities with the stakeholders. You would be able to see how the various features and products you own relate to each other. You won't need to rely on the developers to figure out every single thing. Also, your ability to make an informed decision will sometimes be crucial when there are competing plans, and the team can't come to a decision. Qualities of a Delivery Manager Believe me, there will be 101 things to do and more. Many meetings and conversations to participate and you will need a good app for managing all the tasks. Any app is fine as long as you are able to plan for the days ahead. It's almost impossible to get by using your memory alone. For emails, colour coding, tagging, and snoozing will all be necessary. Slack's remind feature is handy too. Multitasking: This is probably one of the most important lessons that I learned. A DM is an enabler who puts on the scrum master hat in an agile team and helps to resolve impediments. As a developer, you often get help to remove your blockers, but as a DM, you have to do it yourself, for you and others. Your presence in the daily standups is invaluable to take note of the blockers the team may have or foresee. Think and act like a DM. especially the product manager (PM). As a manager, you're given the trust to deliver work crucial for the business. It is important to assure the stakeholders that you are in control and able to deliver on time and of high quality. Doing a little preparation before speaking will help you answer the anticipated questions, especially when you're new to the role. Be confident when speaking to stakeholders, and any expected delay. It helps the PM deal with business expectations and communicate with other stakeholders as necessary. While the PM may or may not be in the same team, it's important to work together to achieve the business goals. Be honest about the progress of work with the stakeholders/PM if you foresee not hitting the deadline. Various factors may contribute to a delay. Unexpected complications in work, extended sick leaves, delay by dependency teams, losing key team members, underestimation, and so on. When you find yourself in such a situation, always talk to the PM to reschedule or reprioritize affected work items. Always negotiate This is common advice given to managers, but it does take some practice and especially trust in your developers to truly embrace the advice. I did struggle at the beginning, where sometimes I felt I was sticking my nose into things too much. As a developer, you may have your own way of doing things, but as a manager, you need to learn to delegate. Trust is very important. Don't try to get involved in everything. Do as much as needed and trust others to take care of the rest. Do not micromanage. . This can't be overstated. More than half of your time will be spent in all sorts of meetings and discussions. And the ability to listen more than you talk is of paramount importance, especially during one on one meetings. Satya Nadella, the CEO of Microsoft, during , when asked, "How do you run meetings?", said, "Listen more, talk less and be decisive when the time comes". This has always been in the back of my mind and proved to be helpful in my participation in all those meetings. Listen more, talk less one of his interviews . There were many times when I had to refer to developers, other managers, or PMs before I could answer queries, sometimes even simple ones. But there is no shame in saying you don't know something. Most of the time, people will be more than happy to wait for you to come back with an answer. My engineering director said that as a manager, if you know everything, then you are probably micromanaging. It's fine to say you don't know something Managing people Now you are bound to face this sooner or later quite often due to conflicting ideas on building something between the developers. There is no hard and fast rule for resolving conflicts. It all depends on the situation and experience in handling such situations. Knowing some basic processes for managing conflicts would be very handy as things could get tense or, though rarely, nasty. There are lots of resources on the net on this topic. Conflict management. As most of the day-to-day communications will be via emails and instant messaging, one-on-ones are a great opportunity for face-to-face meetings. Yet, it is not a meeting for work status update, rather use it for checking on how the person is doing in general. Use the time to build a connection and show that you value and care about them. In short, devote your full attention to the person at the other end. that guided me for the one-on-one sessions with my team members. Effective one-on-ones. This is a great article Conclusion Looking back there were many things that I could have done differently or better. I guess that's the learning process and . It takes practice and experience to get good at anything. I definitely enjoyed the experience and learned a lot during the short stint. making mistakes is part of learning Although I didn't get the opportunity during the short stint, building an independent and is something to aim for in the long run. So you need to pay a great deal of effort to the growth of the team. Hopefully, I'll get a crack at this in the future. high-performing team

Learning Management: My Adventure as an Acting Delivery Manager

If you are like , then many of your hobby projects and portfolio examples are deployed to Heroku. Like , it is an attractive option to host your project because it is free. Unlike Github Pages, you can host a server on , so I use it whenever I need a free place to deploy a full-stack application. me Github Pages Heroku There is, of course, a catch, which is that your free Heroku dyno (virtual machine instance) will take a nap whenever it has gone for thirty minutes or more without receiving any web traffic. A user who tries to load an application with a sleeping dyno will experience a wait time of up to ten seconds, which is a sufficient amount of time for many users to conclude that your app is broken and move on. Especially in instances when you are using Heroku to showcase your work, like a portfolio project, this is a real problem. An easy solution for Nodejs Fortunately, it is really easy to keep your dyno awake with just a few lines of code. I used , because that is the language my back end is written in. For the sake of reuse, I created a small module, though a simple function is all that is required. Nodejs I used Node's function to make an HTTP request to my app at regular intervals of less than thirty minutes, thus keeping the dyno from snoozing. Why not use instead? It automatically repeats and would be slightly more concise, after all. You certainly could, but I have seen some accounts that can be . Though it is admittedly unlikely my use case would run afoul of this type of problem, it also turned out that error handling was easier using setTimeout, as you will see. setTimeout setInterval setInterval problematic I named my little utility function , and used a statement to declare it as the module's default export. I only needed to install one dependency: , though any Node library that makes HTTP requests will work. wakeUpDyno modules.export node-fetch The function has two parameters, - the address of the dyno (a string) – and – the amount of time in minutes that our function will wait between making its HTTP requests (an integer). url interval is called from inside , passing it both an anonymous callback function, and the length of time it is to wait in milliseconds between calls (the time in minutes – interval – multiplied by 60,000 ms/min). setTimeout wakeUpDyno Then, to wake the dyno, I put the HTTP request inside the callback function, and invoked it with the argument. url fetch = ( ); wakeUpDyno = { milliseconds = interval * ;
    setTimeout( {
        fetch(url);
    }, milliseconds);
}; .exports = wakeUpDyno; const require "node-fetch" const ( ) => url, interval const 60000 => () module This will do the trick of rousing a sleepy dyno, but unlike , will only run once. So, I needed to make the function call itself again after finishing its request. setInterval setTimeout fetch It occurred to me that if a fetch call were to fail, then function execution would never make it to my recursive call, and the program would exit with an error. So I decided to nest the request inside a block, followed by a block containing the recursive call. This way, the function will call itself again, whether or not the previous call fails. fetch try...catch ...finally fetch HTTP = ( ); wakeUpDyno = {
    setTimeout( { { 
            HTTP.get(url, () => { .log( )
            });
        } (err) { .log( );
        } {
            wakeUpDyno(url, interval);
        }

    }, interval);
}; .exports = wakeUpDyno; const require "HTTP" const ( ) => url, interval => () try console `Making HTTP request to ...` ${url} catch console `Error fetching ` ${url} finally module At that point, my utility was functional, but I also wanted to add an optional parameter, and also to give the parameter a default value of 25 minutes. callback interval In case of its failure, I nested the invocation of in another block, situated in the original block. I moved the recursive call to down to the more deeply nested second block, so that it would execute regardless of the success of . callback try...catch...finally ...finally wakeDyno ...finally callback So, my final code looks like this: fetch = ( ); wakeUpDyno = { milliseconds = interval * ;
    setTimeout( { { .log( ); fetch(url).then( .log( )); 
        } (err) { .log( );
        } { {
                callback(); } (e) { callback ? .log( , e.message) : ;
            } { wakeUpDyno(url, interval, callback);
            }
            
        }

    }, milliseconds);
}; .exports = wakeUpDyno; const require "node-fetch" const ( ) => url, interval = , callback 25 const 60000 => () try console `setTimeout called.` // HTTP GET request to the dyno's url => () console `Fetching .` ${url} catch // catch fetch errors console `Error fetching : Will try again in minutes...` ${url} ${err.message} ${interval} finally try // execute callback, if passed catch // catch callback error console "Callback failed: " null finally // do it all again return module To use it, I will it in my project, and invoke it when I start up my server, like this: require Express express = ( ); wakeUpDyno = ( ); PORT = ; DYNO_URL = ; app = express(); app.listen(PORT, () => {
    wakeUpDyno(DYNO_URL); }) const require "express" const require "wokeDyno.js" // my module! const 3000 // whatever port you like const "https://howimadeathing.herokuapp.com" // the url of your dyno const // instantiate Express app // will start once server starts And that is it! Once I uploaded it to Heroku, it worked exactly as intended, and my app hasn't slept since! One small caveat to this project: Heroku allows users a limited number of per month, so if you have multiple apps running this utility, you may run out! For that reason, in a future iteration of this module, I intend to allow scheduling so dyno hours may be rationed more effectively. free dyno hours Please reach out to me with any feedback or corrections. You can access the Github repository for this project, here .

Prevent Your Free Heroku Dyno from Sleeping 

Fear has often been the cause of my worst business decisions and eventually lead me to lose control of one of my companies. I’ve paid a high price to understand this lesson. In the Power of Habit, talks about the human brain being made up of a number of layers, and that we just have a less evolved “dinosaur brain”, much of which we share with other animals, and a higher order brain, a more evolved brain, which gives humans higher level thinking and abstract thought. Unfortunately, our pesky dino brain is our survivalist brain, and whenever we are under stress, our dino brain takes over. Charles Duhigg identified six basic emotions (anger, disgust, fear, happiness, sadness, and surprise), and these are the ones that our dino brain lives by. Don’t feel bad though, when we were cave-humans, we needed those emotions in order to survive. We needed anger to fight, disgust to know what not to eat, fear to survive, happiness to keep moving forward, sadness to take stock and surprise to kick our adrenaline into high gear when under threat. Paul Ekman All those emotions served us then, but times have changed. Instead of getting angry at prey, we get angry at our co-coworkers. Instead of being afraid of predators, we get afraid of losing our jobs, our businesses running out of money and giving up our lives for them. Ever wonder why you feel outraged by the news media? They know exactly how to manipulate your dino brain to get a response out of you. Seen those studies on how ? Bombarded all day with happy images of other peoples lives can’t be great for self-esteem, but that’s what you get every time to fire up Facebook. Of course, its mostly a , but your dino brain doesn’t know that. social media makes you unhappy facade When you are a startup entrepreneur, the stakes are even higher. At first, you think, this is great, I’m my own boss, I can do what I want, and I don’t need to do things I don’t need to. You look at all of your employed friends and family and feel pity — But you aren’t. You’ve traded some security for freedom, but your boss is now your customer, client or yourself, your investors may act like your boss. If you are in business and making money at all, you are beholden to someone. You are now fully responsible for your life, you can’t blame anyone else if you fail, and if you are not working or your business is not making money, you will fail. And the fear of failure includes anxiety, shame and all sorts of unhappy thoughts. The key is to spot and acknowledge the emotion of fear and eliminate it as much as you can when you are making important decisions. Fear is like electricity in the body and when you acknowledge its presence and start to be conscious of it and its tactility you can move it in your body like any other energy coming from your emotions. One of the best pieces of advice on public speaking is “ ”. Let the fear drive you forward. Let it give you the energy to push through the right decision. This is tough, our ego does everything to reinforce its existence and fear is one of its favorite things because it gets refueled — recharged through fear. feel the fear, and do it anyway , or ask yourself “If I had a lot of money what would I do in this situation?”. This can help you prioritize the long-term and to execute on your vision. Try to make your decisions as if you had a comfortable cash flow Ask yourself: This question takes you back to your core values and ethics and can help you face the fear of failure in important and critical moments. “Who would I like to be in the future or what would I want to be perceived or known for?” When taken by fear, we often push today decisions for later, which is probably the worst thing that you can do. Think of it another way: the sooner this is done, the sooner it will be behind me and I won’t have to think about it anymore. (Also good advice for the procrastinators out there) Do not postpone to tomorrow what can be done today. Seneca has a very good quote about this: “Let us postpone nothing. Let us balance life’s books each day… The one who puts the finishing touches on their life each day is never short of time.” Adversity, intense competition, political games at your board and even treason are more common in business and they can trigger fear and make you doubt. These are the hardest things to spot because they attack directly what’s below the fear, your self-esteem and makes you question your self-worth. Low self-esteem is probably the main reason when fear kicks in during those moments and situations. Luckily, is just a tool which we can use for both good and evil. We can use it to keep in touch with the people we love, and we can use it to brag about our “wonderful lives”. We can use it to be educated, informed and saddened, all at the same time. technology Proper use of tech can help you to eliminate the outrage, and bump up your self-esteem at the same time. As entrepreneurs, we have a lot of emotion vested in our businesses, and if things aren’t going well, it’s easy to take it personally. When we are not meeting our goals, when our business is floundering, looking for its legs, we can easily get depressed. Here is where technology can help: Use on YouTube to center yourself and be more mindful. has recently been used successfully as a tool to combat depression. If you are fully in the present, then you are not regretting the past or worried about the future. meditation videos Mindfulness Edit out the voices on which are bragging about how great their lives are by them, or even better, why not take a ? Take a break and reset yourself. Trust me, you will feel much better for it. Facebook snoozing social media vacation You’ve probably been burning the candle at all ends trying to succeed. Use on iOS to get a good nights sleep. Listen to a . Go to the gym and out. Just do something other than working on your business for a little bit. Bedtime Sleep sounds app work your anger and frustration Use tech to free your time up for self-care. There are a plethora of free and cheap tools out there (like , , or ) which can help to alleviate the day-to-day stresses of an entrepreneur. Use them. Fabulous Headspace Calm Use apps like to connect with a counselor or business coach who can help you through a rough patch, if you need it. Or just connect with a trusted friend who is not connected with your business at all and talk it out. Talkspace If you don’t feel that you know anyone you could talk to this about, then use a and just record yourself talking. Do it in the car or some other private place. Listen to it (or not) then delete it after. Just talking it out will help. recorder app A great thing to do also and that I have been doing a few times is to go in the nature, in a park and to shout as loud as you can. You will feel the liberating effect it can have. When we let fear take over our business decisions we begin to make bad ones. Even if tech outrages you, it can help you knock out fear and take a bite out of depression. When combined with good discipline in your personal work, like meditating everyday on a regular basis; and good self care by cultivating time for yourself, you develop enough awareness not to be caught by your fear.

How To Overcome Fear & Make Better Business Decisions

Email overload has a serious impact on productivity, the attention span and stress at work. In our previous article, we analyzed email overload ramifications and proposed a to contain it. 7 steps methodology Today, we’ll take a more practical approach and look into the tools you can use (with Gmail) to both reduce the number of emails you receive and accelerate their sorting. We’ll first look into Gmail’s built-in features and then propose some tools to extend them. GMAIL BUILT-IN FEATURES Before we look into the solutions to extend Gmail’s functionality, let’s see what we can do with the built-in features. Over the years, Google added several functions to help its user prioritize and sort their email flow. HIGH-LEVEL CATEGORIZATION WITH “INBOX” Inbox is a new product released to the public in 2015. Its goal is Inbox is now available in two different ways: you can use it as a replacement for Gmail, by going . to sort your emails into categories. on the Inbox website The standalone product has up to 8 bundles: Out of the box, the accuracy of the bundling is not exactly top-notch, but it can get better as you refine it. Trips, Saved, Purchases, Social, Updates, Forums, Promos, and Low Priority. Inbox brings many other exciting features, such as batch-archiving email, snoozing the important one to respond later or creating reminders without leaving the app. Sadly, : Inbox will no longer be available as a standalone product by the end of March 2019. Google is shutting it down If you would rather keep all the other features offered in Gmail, . Just go to the ⚙️ on the top right > Configure Inbox. There are up to 4 categories available with the Gmail version: . you can also activate Inbox on the regular Gmail website Social, Promotions, Updates, Forums THE FEATURE IMPORTANT In Gmail, there are several built-in prioritization systems among which the important flagging. It looks like a yellow flag next to your email. There are two ways to use it: By default (on the new Gmail Inbox), you can manually flag each mail as important or not. In Settings > General, activating the setting will have . You can still interact manually with the tagging, and it will improve the precision of the automated tagging. personal level indicator Google automatically tag the emails for you UNSUBSCRIBING MADE EASY Thanks to a little script, it’s possible to unsubscribe from newsletter without even leaving your mailbox and with just a couple clicks. Il will . unsubscribe you automatically from emails that to which you gave a specific label It just takes a couple minutes to set it up: on your Drive and open it. Copy the sheet Click the arrow at the top of the sheet and then configure. You’ll have to authorize the script and then pick a label. That’s all the script needs to work. Gmail Unsubscriber Now go to your mailbox and label any unwanted email as . Every 15 minutes, the script goes through your mailbox to unsubscribe you. unsubscribe The Google Sheets will populate itself with all the services it unsubscribed you to. You can thank Amit Argawal for the script. This hack is quick to set up, easy to use and can potentially save you much time. Use it to the bone! GOING FURTHER WITH LABELS Labels can prove to be super useful for more than just cleaning up the undesirable. You can create as many as you may need and nest them. Labels are particularly helpful because they are such as the filters, the search or the Priority Inbox (Settings > Inbox > Inbox Type). integrated with other Gmail features The Priority Inbox structure your inbox into up to 4 sections (the default is ). You can mix it with your custom labels. Important and Unread, Starred, Everything Else MASTERING GMAIL SEARCH OPERATORS Ever spent way too long looking for an old email? Thanks to the star or the important label crucial information should already be segregated from the rest of your mailbox. Sometimes it’s not enough: this is when the search modifiers come into play. The modifiers are incredibly potent because they can be : any information you remember about the mail can be useful to find it back. For instance, will search for emails with either lunch or dinner in their subject line, labeled important, containing a Google Drive document and sent/received before June the 10th of 2017. Search modifiers are plentiful and pretty straightforward. The is available on Google’s documentation. stacked with one another indefinitely label:important has:drive has:document before:2017/06/10 {subject:dinner subject:lunch} full list EXTENDING GMAIL MEETING SCHEDULING You’re scheduling many meetings for your work, and the back and forth is becoming a hassle? There are several ways to go around this issue. The first and most natural to implement is to adopt an Think about the intent — what you’re trying to achieve — when you’re replying to an email. If the goal is to set up a meeting, offering several meeting time option from the first email can help remove unnecessary steps. We covered in another article. It can be used for anything and not just emails. action-oriented writing style. action-oriented writing While this simplifies the email flow, you still have to check your calendar every time before suggesting potential meeting times… Unless you get some help. LET AN AI ASSISTANT HANDLE THE BACK AND FORTH If your working in sales or any other field requiring to book several meeting each day, you can consider getting helped to save more time. There are AI scheduling assistants that can help you deal with the meetings overload. The process is quite straightforward. These AI assistants, such as or connect to your Google Calendar. When you want to schedule a meeting with someone, you add the email address of the assistant in the cc field. The bot will then reach out to your recipient offering several meeting times. Once your recipient reaches back to Kono/Amy to confirm, the meeting is automatically added to your calendar. Kono Amy With Kono, there is even a that can quickly schedule meetings with your teammates in a single command such as: . The bot also handles rescheduling if needed. Slack bot @kono schedule meeting with @Bob and @Robert next week SNOOZE, SCHEDULE AND FREEZE EMAILS WITH BOOMERANG helps you to make sure your emails get a reply, and you don’t forget about any of them. It comes with several features allowing you to: Boomrang Schedule email to send later Remind you if you don’t hear back from someone after sending an email “Boomerang” emails which is a bit like snoozing: your email is archived and comes back in your inbox at the time you choose. Pause your inbox which stops new email from coming into your inbox until you’re ready for them. You can set up an auto-responder for the bounced emails and set up exceptions that bypass the pause. GWAP LIKE YOU MEAN IT All the previous tools we mentioned to make it more structured and provide additional features to handle the flow of incoming emails better. are built on the existing Gmail inbox At , we have a different approach to this issue. We know that each company is different and has its email processes, so we let our (“groups”) to sort the incoming storm. The benefits are apparent after the setup phase. Gwapit customers create and share custom filters Screenshot of Gwapit’s main dashboard with all the notifications coming from different apps goes above simply managing your emails notifications. It . We currently support Gmail, Slack, Github, JIRA, and Confluence. Gwapit connects to your workspace apps to regroup and prioritize your notifications flow Gwapit is currently in beta, . build it with us Originally published at gwapit.com on October 2, 2018.

A practical guide to achieving Inbox Zero with Gmail

We can all do more with 24 hours I had a friend visit me from Kansas City, Kansas. A small town boy, he went to school in the big city of Chicago, but he had never experienced the even bigger city of New York. My excitement was palpable. I was talking faster than normal, I was walking faster than normal, and I was basically bouncing up and down as I described everything I had planned for him during the upcoming weekend. We’re going to wake up and go to the gym. Then we’re going to get breakfast. Then we’ll play some tennis. Then we’ll get in a basketball game. Then we’ll see a movie. Then we’ll go to happy hour with our friends. Then we’ll grab dinner. Then we’ll see a comedy show. Then we’ll… I was interrupted. “Hold the phone, J, there are only 24 hours in a day!” “Only?!” I replied. The number of hours in the day is directly correlated with what we do and how we make the most of those hours. Duh. Our perception of these 24 hours varies. Clearly my friend believed it was impossible to fit all of those activities into one day. But not I. I believe in bear hugging every single hour of the day so tightly, that there is essentially nothing left to remain, aside from sleep and maybe 43 minutes of (phenomenal show). The Sinner After hearing my friend skeptically and almost mockingly announce that the day was simply not long enough to fit in all of these activities, I began to jot ideas down as to how to refute his point. I came up with 11 ways to add seconds, minutes, and dare I say it, hours to the day. “close shot of gray monkey face” by on VITALIY ANOKHIN Unsplash 1. Stop Snoozing The alarm goes off and what is 99% of our first reactions? Let’s hit the snooze button! Just a little more rest won’t hurt… Well, I agree, it certainly won’t hurt, but it will certainly waste precious moments of your day! Waking up and hitting snooze can lose you 5, 8, 19, or in some cases hundreds of minutes! I actually wrote a book about overcoming the snooze button called In it, I outline a full, 5-step routine for beating that alarm and waking up with excitement rather than stress and anxiety. I stopped snoozing, and my productivity went through the roof. Getting COMFY: Your Morning Guide to Daily Happiness . The Morning Guide to Ensure a Stress Free, Positive Life So next time that alarm starts ringing, put your two feet on the floor and get your day started. 2. Keep Meals to Under 20 Minutes This one is difficult for me because I love to eat as much as the next guy. But a useful tip for preserving time is to limit the lengths of your meals. Treat meals as fuel rather than extravaganzas. By no means am I saying to scarf down your food like an animal, but do not lallygag and throw this time away. Have a productive, energy boosting meal, and move on to the next activity. 3. HIIT Every incredible day should include some sort of exercise or workout. But, oftentimes, these can be very time-consuming. Hour-long runs, lifts, classes, yoga sessions, followed by transportation to and fro, and a shower can take out a large part of the day! High Intensity Interval Training. For this reason, I recommend HIIT. Short, emphatic bursts of energy that will get your heart racing, your muscles throbbing, and your body sweating. These workouts are usually full-body, 30 minutes or less, but you can get a fantastic sweat in in just 10–15. 4. Do the Hardest Thing First After creating your to-do list and assessing what it is you are going to attack on any given day, I cannot recommend enough doing the hardest thing first. View your brain capacity like a fresh new pencil. It starts out absolutely pristine. When it first hits the paper, it is working flawlessly. It is effortless to get it to do what it was crafted to do. Then you move on to the next sentence, and the pencil is now a little smaller, it’s harder to write with. Then the next paragraph, and it has shrunk even more. Then the next page and the next, and it has written so many words that it has shrunk to almost nothing. Your brain functions more efficiently when it is fresh. Taking care of the most difficult, the most stressful task first allows you to use the highest amount of brain power possible. It provides you with the opportunity to solve problems quicker, make quicker decisions, and achieve more in a shorter period. Waiting until the end of the day to work on this task can draw out the process. It will lead to frustration, making it even longer to complete. Do what is most daunting first, and save time, energy, and frustration by doing so. 5. Show up Early Being punctual has so many advantages. Besides the obvious ones, it also adds minutes to the day. Being early gives you the opportunity to get started at a meeting on time. It makes the day feel less rushed, and feeling less rushed is a large part of it actually being less rushed. The earlier you are also, the more likely it is to begin early, which pushes everything up and adds time as well! “man wearing red cap crossing street” by on Tyler Nix Unsplash 6. Power Walk Speed walking is a great way to get around, and it can definitely give back a few extra ticks on the clock. It may look silly, but it works! 7. Don’t Stall in the Shower Showers are a hotbed for time wasting. Yes, they are wonderful and relaxing and all that good stuff, but they can also be efficient. Get clean, get out. That’s my motto. Try making the water extra cold so that you want to get out more than you want to stay in. The Numbing Reality of the Almighty Cold Shower 8. Have Productive Down Time I am a big believer in breaks and the power of recharging. But, this does not provide me the leisure of fully zoning out or wasting a significant amount of time deviating from the task at hand. If I have a doctor’s appointment, a meeting, anything in which I know there is the possibility of waiting before the event, I make sure to bring something else to work on. Additionally, as funny as it sounds, I even use bathroom breaks to get sh*t done, no pun intended!!! Why Bathroom Breaks are the Secret to Growing Your Following on Medium Embracing necessary rest time, but also realizing the ability to use it to your advantage most certainly adds time to the day. 9. Do Not Sit Standing desks are all the rage these days. While the health risks of sitting may be over-exaggerated, one thing is for certain. Sitting for extended periods of time, especially sitting and doing things like watching tv, or browsing the internet, or looking at your phone, will waste beautiful minutes. The less you sit, the more you are on the go, the more you will feel like the day is lengthening. 10. Skip the News The news is draining. It is filled with negativity, drama, devastation, hate, and sadly much worse. A pessimistic and negative mentality and world view will suck the energy out of you, making it difficult to bounce back and be as present as possible with the time in the day. Not to mention, you get back the time you would normally take reading or watching it on tv. Try this instead. No News Challenge I once heard somebody say that they only learned the news from other people. I am terribly sorry that I forgot whoever said this, but I am going to create a game out of your amazing words of wisdom and explanation. 1. Do not read the news at all in the morning, or throughout the day 2. Ask people about what is happening around the world in politics, sports, entertainment, business, technology, etc. 3. Write down the stories you are told 4. At the end of the day or right before bed, check the news and see how many of the top stories you became aware of, even though you did not pick up a newspaper or read a single article You may feel uncomfortable doing this — asking somebody about the news, immediately becoming the student in a conversation. But, asking people questions gives them a feeling of empowerment, and as long as we are comfortable empowering people, which we should be, we both win. We get the news, and they get the feeling like they taught somebody something. Not to mention, no time was wasted. 11. Ditch Distractions During High Time This last one means that when you are on a roll, you have some momentum, you are in the zone, block out all other distractions. Do not watch tv. Do not have social media open. Do not even have wi-fi on unless you absolutely need it. Understand when you work best and devote that period of time fully to the task at hand, without anything else to get in the way. This will add back those minutes in which you would otherwise be doing something else. Final Thoughts We all have the same 24 hours to work with. Bill Gates does, Meryl Streep does, Barack Obama does. So why does it seem like some people, like the ones mentioned above, can achieve so much? Why does it seem like some people are everywhere? Why do people accomplish more than others if we have the same amount of time to do so? The answer comes down to how we make the most of our time. The answer comes down to how we conserve time. The answer comes down to how we value time. “Once you have mastered time, you will understand how true it is that most people overestimate what they can accomplish in a year — and underestimate what they can achieve in a decade.” — Tony Robbins The same goes for the day. Most people overestimate what they can accomplish in the 5 or 6 hours they devote to scheduling themselves and getting busy at work. But most people underestimate what they can accomplish in a full 24 hours, in which time is meticulously accounted for. Time is precious. Make every moment count. Want to Feel More Comfortable in Any Situation? Become a part of the Getting COMFY community, which pushes you and proves to you we can all be getting comfier in our own skin, by joining . here

11 Ways to Add Time to Your Day

TL;DR This is a story of the journey I went through. I wanted to design a machine learning system that would tell me whether I can snooze in the morning and still arrive on time for work. I do get a bit technical in this article, so I added some links to some of the more advanced terms in this article If you want to learn how to build image recognition systems, there are better articles out there. But if you want a couple of good chuckles, and see how easy it is to get something that resembles machine up and running, then this is article is for you. learning Context and Problem definition Just after completing Professor Ng’s , I was looking for challenging problems to put those newly learnt algorithms to good use. Machine Learning course I came up with a lot of fun and interesting ideas. But ultimately, none of those were actual problems. Yes, space exploration sounds fun. But let’s be real, I’m only considering this for the sake of working on a complex project. Not because I have this burning desire to find new clusters of stars. Then one morning, I once again made the ill-advised decision to hit snooze on my alarm clock. Because of traffic, I arrived gross and sweaty at work, on time.. somewhat There’s nothing like a morning at work after a good run It was a yucky way to start the day, but it made me realize that this is what I should work on. There’s not much I actually complain about. But if I had the superpower to assert with confidence whether to hit that tempting snooze button, life would truly be wonderful! The outline of the problem was pretty clear. In the end, we want a system that tells us ahead of time whether the route is clear and sleeping another 10 minutes won’t hurt. Luckily for me, it just happens that I live in Singapore, where we have access to a ton of public data, including traffic camera images. Designing a system pipeline With all this in mind, I designed to following pipeline for my machine learning system: Get traffic camera images Build to classify image subsections tool Classify a lot of examples car/no car Crop and resize selections out of original pictures Build own deep Neural Networks Train Neural Network to detect cars Detect the car sections in actual traffic pictures Count how many cars in pictures Gather images for the times and locations of my commute specifically Build time series with how many cars, at what time, and where Estimate whether there will be traffic tomorrow Snooze peacefully 😴😴😴 And there began my data science journey. And boy oh boy, what a journey! 1. Getting traffic camera images This was surprisingly one of the easiest parts. did an good job with their . With little to no experience with the json, csv, and request Python libraries, you can quickly and neatly download a lot of . Data.gov.sg APIs traffic camera images I decided to download data from all around the country and at all times. Even though in the end we will only need to detect cars in front of my apartment complex at around 9:00 AM. I did that in order to train a Image Recognition System that can then easily be applied to other places and times. more versatile Now that we have a bunch of traffic camera images, let’s work on detecting cars 2. Classifying subsections of an image Getting traffic images is great, but unfortunately, can can’t just shove that in a Neural Network and expect it to do a decent job at counting cars. (Well maybe we could, but it is probably not the most elegant and accurate way of dealing with the problem). So I started going through each image, try to keep track of the coordinates of each cars to later crop them out to train our car detection Neural Network. I quickly realized that this was getting out of hand. So I wrote a script to make my life easier. very This is one of the reasons why I fell in love with programming in the first place: . We use programs to program, so we can program a program, so that it would program better and we don’t have to program as much! we have the power to make our work tools better I used the library to make a program where I can make image selections with only a couple of clicks and key strokes. Tkinter We wrote a script to classify cars within a picture, now is time to use it 3. Classifying loads of examples car/no car Labelling traffic camera images Even if it was dull, repetitive work, I managed to label almost 200 cars and more than 1500 non cars selection across 30 ish images, under an hour. I made the executive decision that this was enough data to move on to the next (I was bored). 4. Cropping and resizing selections This part is also pretty straightforward. The script I wrote for part 3 stores the image selections relevant information in a neat file. I only have to keep track of whether the selection is a car or not, the coordinate of the top left corner, the size of the selection. Knowing all this, I used the library (I know, it is very fitting to our little project) to crop out cars and non-cars selections. csv Pillow 5. Writing code to build, train, and test my own deep Neural Networks This is it, we’re building our own lads! Oh boy was I in for a treat. I decided to build it from the ground up, so I would get a deeper grasp of what is going on under the hood. The concepts behind neural networks are not that hard to get (except maybe the derivations for the update functions). But implementing all of it is a whole other story. Neural Network For starters, it helps if you’re not an idiot. I implemented the different components and all the logic looked fine to me.. However, none of my node weights were updating properly. After a couple hours of debugging, and a couple grams of hair missing from my scalp, I found out I was using Python 2 this whole time where and not Python 3 where . So all my coefficients would at some point end up being 0 (and turns out ), so the network would not update itself at all. really 1 / 2 = 0 1 / 2 = 0.5 0 + a = a I also spend a lot of time trying various hyperparameters for the network as I found that it wasn’t performing well enough. I was baffled, I was training my 3 layer of 5 units each Neural Network on 9 whole training examples, and , the algorithm wasn’t doing a good job at guessing the 10th example. I was essentially a 50/50 for the network to get it right. Was I lied to this whole time? Are Neural Networks not the I was made to believe they were? Luckily, I had the presence of mind that you can update your Neural Network 100,000 times, but you need a bit more than 9 data points to get an algorithm somewhat close to being useful. somehow high-performing-state-of-the-art-predictive-classifier maybe So I used an actual data set, namely, the set from scikit-learn. Why this one in particular? Well you see, we used the particular data set in one of my favorite class assignments I had in university (we had to build an , if you’re looking for a fun, math focused problem, go check it out). iris data ID3 The algorithm was now doing better (better than our previous 50/50 algorithm, yay!). However, it was still acting a bit weird. No matter how many times the algorithm was running, or how fast it was performing updates, I would always end up with either a 60% accuracy or a 40% accuracy. I felt really discouraged. Even if it was doing better, how could such an algorithm ever be able to tell cars apart from road signs, if it can’t even tell dumb flowers apart??? I was on the verge of quitting programing and following Edmund Blackadder’s footsteps. For fun though, I decided to see at least how well Neural Networks from standard libraries would do. So I ran the data set against scikit-learn’s . I was astonished. Not only were the results far from the 99% accuracy that I was expecting, but the results were also almost always the same as the results I got when using my implementation. So no matter how ugly and inefficient our code is, we must have gotten a least a couple things right. Hurray! Neural Network classifier Our subpar 60% or 40% was in fact not due to our poor implementation, but most likely due to our data set which is too small. still But oh well, we finally have a tool to design and train deep Neural Networks. Good enough by my books, gotta keep moving! 6. Training Neural Network on car images How exciting, we get to finally use our Neural Network we spend an unnecessary amount of time designing! Sadly, our algorithm can’t handle too many inputs and logical units. While it was still on par with scikit-learn algorithm for a 5-input and 7-ish-logical-unit networks, it completely blew up up when trying to handle images. (For reference, I am using 32px by 32px with 3 color channels for in image input, so the input has features which is a lot more than 5) Errrr wrong, try again next time! 32 * 32 * 3 = 3072 Goodbye custom Neural Network :’( To be more precise, it was actually my custom (sigmoid and ReLu) and their derivatives that went boom and tried dividing stuff by 0 (I do not recommend trying to divide by 0). activation function It was heartbreaking, but we got a problem to fix folks: I still need to know whether I can snooze or not! So I gave in, and used a library’s implementation. Only a fool would change a winning team, so I went with the good ol’ scikit-learn Neural Network Classifier. The algorithm was doing quite well actually, right out of the box I got a consistent 88% accuracy over my test set. I then performed . I looked for the best values for my network size, my learning rate, and the number of iterations to go through. I managed to increase accuracy up to 91%, so I saved the Neural Network model and called it a day. hyperparameter fine tuning We ended up training a Neural Network with 90%+ accuracy, let’s see how it holds against raw traffic images 7. Detecting car sections in pictures It’s great that our algorithm is working fine on pre-cropped car/no car images. Now we need to find those cars in traffic camera images. I chose to go with the . Essentially I look at the top left corner, see if it is a car or not, if it is, I keep track of that car. Then I slide to the right, and when i reach the end of the line, I go back to the left and shift down. sliding window technique There is no doubt in my mind that this approach is one of the most gruesome out there. But pigs don’t get fat on clear water. In that case, we’re the pig and we need some fatty porridge. Maybe in the future we’ll be more sophisticated and we’ll use crystal clear feature detections methods.. But not now. I want results and I want them fast! The results were….interesting. It was doing ok, but a lot of consistent errors that I could foresee would impair our traffic detection algorithm. First run on an actual traffic image As you can see, it does detect some cars pretty well, but also the arrows indicating the roads’ destinations. And more importantly, it detected of cars on the right and the bottom… a lot Turns out, I was trying to detect cars outside the picture on the right and at the bottom. I was doing one too many slide in both direction.. This tweet felt painfully relevant at that time: All jokes aside, after fixing that issue and refining the parameters, we got something that wasn’t half bad, and I was happy. Labels and lane dividers are still an issue, but it s good enough to get something to work. Now that we detect cars pretty well, it’s high time we count how many there are in a picture. 8. Counting cars So our sliding door technique paired with our car recognition system work pretty well. But now, how are we supposed to know how many cars there are?? We can’t just count how many times our car algorithm detects a car. As you can see from the previous image, one car can be detected multiple times, and some non car sections are detected, but only once, and probably should be ignored. This sort of looked like a clustering project, so of course, having just learn the technique, I just dove into implementing it for our problem. One thing though, this technique actually requires you to know how many neighborhood there are (in our case, how many cars there are). Huh?? But that’s what we’re trying to find out.. But it’s all good, we’ll run k-NN for all numbers between 1 and 30, and see which one is It actually did work, surprisingly. But god was it slow. k-nearest-neighbors the most correct. Then, one day while I was grocery shopping (that’s not relevant to the story at all, but I’m rolling with it), I realized I was overcomplicating things for no good reason. How would a 3 year old solve this, I asked myself. Well, they would probably color any blob that is connected, then do that for all the blobs in the picture, and count how many times they colored a blob. My outsourced team, counting cars for me while I take a nap So I did just that, a 3-year-old’s coloring algorithm and ran it against our beloved traffic camera images. It definitely was ugly and inaccurate, but here’s the thing: we don’t need to know how many cars there are. What we need, is the number of cars detected to go up significantly when the actual number of cars is high, and vice versa. Luckily for me, my algorithm was doing just that. Yay me! We detected 13 cars, top left is the image with the detected cars, bottom left is the neighborhood heights, top right is the normalized neighborhoods, one of them colored in, bottom right is the same as top right but we removed the colored neighborhood (so we don’t count is again) We detected 20 cars here. While there probably aren’t 20 cars, it s a higher number than what we detected on the previous image, and there is significantly more traffic We can finally estimate the traffic flow, all that’s left for us to do is to build traffic historical data, so we can extrapolate for future days. 9. Gathering images down my apartment at 9am Ezpz, that’s just step 1, but instead of looking at any and all picture the government allows me to see, I need to only look at the ones coming from camera 6703 around 9AM, because ultimately that’s all I care about. Boom, onto the next step! 10. Building traffic time series Ezpz squared! We just get those car counts and timestamps we got from last step and store them in some file somewhere. Damn we’re really dashing through those stages aren’t we? 11. Extrapolating from our time series So let’s recap, we have the “ ” there was for the past 20 days . Now let’s guess what it’s gonna be tomorrow! Better yet, let’s guess for the next 5 days! number of cars ish At first I wanted to use a algorithm as it is the state of the art and it does well against seasonal trends, and that might be a thing for traffic. Upon further reading, I learnt that LSTM actually relies on a recurrent Neural Network architecture. Having only 20 data points, I did not want to repeat our step 5 disaster and waste countless hours for nothing. So in the end, I went with the method, which also does well with seasonal trend, but is uses a more statistical approach that works with fewer data points. LSTM ARIMA We got something like this: Blue is actual data, red is prediction Not too shabby, huh? Considering we trained the model on 15 examples to guess the next 5. You know what, I ship it! Hurray! We gathered enough data to predict the future! Nostradamus would be so proud. 12. Snoozing peacefully 😴😴😴 I now check every night if I will snooze tomorrow. Never have I ever been late for work since! And my project and I lived happily ever after, the end. Errrr wrong again, better luck next time! Even though we’re estimating the number of cars pretty well, and predicting tomorrow’s traffic somewhat decently, there are still improvements to make. Of course, we have plenty of places to look for optimization. But the bigger problem is that our base hypothesis is not accurate enough. Yes, traffic does play a big role in determining the length of my commute, but the commute itself plays a huge role too. You see, I take the bus then the train to go to work. While missing a train only adds another 2 minutes to my morning travels. If I get unlucky and three buses pass by me just before I can get to them, I might be looking at another 20 minutes to my 40 minute journey.. Where to go from there As I just mentioned, it would be interesting to make use of the real time bus arrival updates and see how much it would improve our current system. Of course we can always improve our car recognition Neural Network by feeding it more labelled data. We can also improve of our simple sliding doors and neighborhood counting techniques Ultimately, checking the traffic the day before isn’t the most practical anyway. So ideally, we have a script that runs on its own while we sleep, and counts cars in real time. Based on that, it rings the alarm sooner or later. Parting thoughts Wow that was a long story, I’m glad you made it this far. All in all, it has been a blast building this entire system from scratch. And I was surprised at how easy it ended up being. This is mainly because I forced myself to work on it in small increments, but everyday. Once you’ve figured out how to break big problems into smaller ones, the sky is the limit. So, be ambitious! Go and solve complex things! As long as you enjoy doing it, all you need is to keep at it and you’ll have something to be proud of in the end! You can find all the code . The code isn’t really plug and play, but I’m more than happy to answer any questions you may have. here Cheers!

Can I Snooze: building an image recognition system to sleep a little longer

Lessons Learned in Product Development products are notorious for being hard to install and slow to get usage in production. There is one corner of the security market where this is doubly true: the web application firewall (WAF). One of the is that once the deal has closed and the product is sold, it takes months to get installed and — worse yet — it often goes unused. Due to all the problems they create, (sometimes called passive mode). The astute reader is probably well aware that passive is the opposite of active, which means the investment in a defensive security product is doing exactly nothing to actively protect against real threats. Security secrets of the WAF industry WAFs get placed in monitoring mode It seems rather odd that the first lesson we learned in building a security product is this: Get the product in active use on customers’ production traffic When we set out to build , of course we wanted to build a product people actually used. More on how we did that in a minute, but we knew that we wanted to be a different kind of security company. Our next lesson was even more fundamental. Signal Sciences Product development in the fast lane. Photo by on Matthew Brodeur Unsplash In lieu of active defense, most WAFs emit streams of logs and events that even a large team of security professionals can’t analyze fast enough. It is pretty hard to function in this type of environment for a human. We knew we wanted to build a WAF that people could use but as we built the product, we started hoping to deliver a product that people enjoyed using. A product that brought joy to people in the roles of security, operations, and development. Can you imagine a security product built to bring joy? Well, we could. We started a cross-functional team to deliver joy to our customers. Here is a screenshot of the slack channel for the team: Signal Sciences slack channel for the Joy Team To be clear the Joy Team isn’t just a renamed group for our frontend UI or something like that. The team handles customer experiences from installing the product to maintaining documentation to operational health metrics. It is composed of support staff, software engineers and product folks who care about delivering joy to customers. These two values of c_reate a product that gets used in production_ and really helped us shape our core principles as a company. bring joy to customers Core Principles We wanted to build a product and a company that rallied around core principles that were radically different from the legacy WAF vendors, and security products in general. We created a set of core product principles: Ease of Use — Building all our products with a focus on simplicity and clarity Data Insights — Turning data into information Visibility — Making information accessible to drive faster response and decision making From Day 1, has been a customer-centric organization, and these principles are based on customer feedback to address the gaps we jointly saw in the industry. Signal Sciences Getting Our First Customers to Run in Production In the early days of , we knew that our customers would love using our product if they could just visualize attacks and abuse against their live apps and APIs. We didn’t want a fictitious experience where they would get access to a demo environment and see staged data. This meant only one thing, we wanted all customers to do a proof of concept (POC) with us, but in their real, actual production environments. Signal Sciences To some security vendors out there, this probably sounds like a pipe dream. Many people doubted we could get security folks to run our product in production, but they did. Sometimes they would even turn us on in production without telling us, often on a Friday afternoon. After this happened a few times, we affectionately began to refer to these times as “YOLO Fridays.” Luckily, most of these went well even in the very beginning of our company. But the real question is why? Why did customers trust us with their production traffic? We believe that it started with our now patented architecture: we could guarantee uptime with a split module-agent . We built a system that would fail open if something happened to our agent. This helped our conversation with operations, who often owns the web server, trust us enough to try it out. Once we got the OK to try an install, the next step was to ensure we had a quick and smooth install experience. design Snoozing Means Losing No one likes projects that go on and on — and none more so than under-resourced security teams who have many other strategic projects that deserve focus. From talking with our customers, their WAF projects tended to look like home improvement projects which are completed late and exceed budget. We knew we could deliver better security than existing solutions, but we realized we could also provide a significant improvement for customers in terms of getting their WAF projects back on track. We knew this because our founding team had already done this as security practitioners at Etsy, a top site in Alexa’s traffic rankings. In one customer engagement early on, we were informed we’d be part of a bake-off versus a large industry incumbent. By the time our POC had wrapped up, we had a meeting with the prospect and were eager to hear how we had fared. To our surprise, the prospect couldn’t give us any head-to-head points where we were stronger or weaker — because the competitor still hadn’t even been able to even install. Due to the inline complexities and operational dependencies required, such as DNS changes, legacy WAFs take months to install, and then constant laborious tuning and tweaking efforts, either performed in house or by expensive external resources. The Early Bird Gets the Bad Guy There are actually 2 parts to a successful install: the actual install, and the time it takes for the product to generate value. To satisfy the first part, we leverage packages and public repositories to help customers automate the install and update with configuration tools like Chef, Puppet, Ansible, and Salt. management Below is an example from a prospect where we created their account on the backend, sent them an invite, and they installed a live agent, . all within 15 minutes Figure 1. Sorry for all the redaction, but this is the log data from an actual production install. Total time from invitation to processing data: 15 minutes. We track customer install time as a KPI and monitor our Slack channels when new prospects bring their first agents online, and it became a race to see who could install the fastest! Today our record is under a minute, and the average is 62 minutes among companies from fast and agile WeWork to a complex enterprise like Under Armour. Once installed, our agents start processing data immediately, detecting attack payloads and applying flags that either block or log, depending on the mode you set in the Signal Sciences Dashboard. There is no learning mode, no RegEx signatures to manage to achieve blocking protection across all core attack types out of the box. So installation time is near instantaneous with time-to-value — a first in the WAF market, where so much time is required to spend authoring and tuning rules to avoid false positives. This brought a very real experience to customers to visualize and for the first time, see what attacks were happening against their web applications. This fact drives to the datapoint we find really exciting: 4 out of 5 companies who install Signal Sciences buy, since they, too, are able to quickly realize value like never before. A Customer Story Where Time = Value One of the great pleasures we have is talking to our customers about their install experiences — and this one about cost savings associated with selecting new products stood out to me. Recently, I spoke with Lance Horner, Head of Security for Day & Zimmermann, a century-old, family-held construction and engineering services company. He told me his story where he was starting to explore WAF products to allocate budget later in the 2018. His original plan was to do a “quick proof of concept” to get an idea around the cost of deployment, where the idea was to purchase later. When he went to install Signal Sciences in a proof of concept, it went so incredibly quickly and easily that he deployed directly into production in under 5 minutes. Due to the fact that his team was able to install the product so easily in production, generating immediate visibility and blocking of attacks, he gained approvals for the immediate release of budget to complete a project that freed up time and resources for other strategic projects later in the year. Demand more from your WAF If this article and our approach sounds interesting to you then we would like to ask you to give us a try and to take the Signal Sciences challenge. We can be up-and-running in your environment in minutes, and you get immediate value in blocking and visibility, saving you time from testing and configuring other types of WAFs on the market. We will show you that vetting a web application firewall solution doesn’t have to take weeks or months. You don’t have to believe our marketing, our current customers, or our industry awards. You can find out for yourself in minutes.

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