Sicura

sicura

On the Proportions and on the Movements of the Human Figure

AI and RAG in Knowledge Graph Enlightenment 

Reflections on the Decline of Science in England, and on Some of Its Causes by Charles Babbage, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Section 3 here SECTION 3. ON THE FRAUDS OF OBSERVERS. Scientific inquiries are more exposed than most others to the inroads of pretenders; and I feel that I shall deserve the thanks of all who really value truth, by stating some of the methods of deceiving practised by unworthy claimants for its honours, whilst the mere circumstance of their arts being known may deter future offenders. There are several species of impositions that have been practised in science, which are but little known, except to the initiated, and which it may perhaps be possible to render quite intelligible to ordinary understandings. These may be classed under the heads of hoaxing, forging, trimming, and cooking. OF HOAXING. This, perhaps, will be better explained by an example. In the year 1788, M. Gioeni, a knight of Malta, published at Naples an account of a new family of Testacea, of which he described, with great minuteness, one species, the specific name of which has been taken from its habitat, and the generic he took from his own family, calling it Gioenia Sicula. It consisted of two rounded triangular valves, united by the body of the animal to a smaller valve in front. He gave figures of the animal, and of its parts; described its structure, its mode of advancing along the sand, the figure of the tract it left, and estimated the velocity of its course at about two-thirds of an inch per minute. He then described the structure of the shell, which he treated with nitric acid, and found it approach nearer to the nature of bone than any other shell. The editors of the ENCYCLOPEDIE METHODIQUE, have copied this description, and have given figures of the Gioenia Sicula. The fact, however, is, that no such animal exists, but that the knight of Malta, finding on the Sicilian shores the three internal bones of one of the species of Bulla, of which some are found on the south-western coast of England, [Bulla lignaria] described and figured these bones most accurately, and drew the whole of the rest of the description from the stores of his own imagination. Such frauds are far from justifiable; the only excuse which has been made for them is, when they have been practised on scientific academies which had reached the period of dotage. It should however be remembered, that the productions of nature are so various, that mere strangeness is very far from sufficient to render doubtful the existence of any creature for which there is evidence; [The number of vertebrae in the neck of the plesiosaurus is a strange but ascertained fact] and that, unless the memoir itself involves principles so contradictory, as to outweigh the evidence of a single witness, [The kind of contradiction which is here alluded to, is that which arises from well ascertained final causes; for instance, the ruminating stomach of the hoofed animals, is in no case combined with the claw-shaped form of the extremities, frequent in many of the carniverous animals, and necessary to some of them for the purpose of seizing their prey] it can only be regarded as a deception, without the accompaniment of wit. FORGING differs from hoaxing, inasmuch as in the latter the deceit is intended to last for a time, and then be discovered, to the ridicule of those who have credited it; whereas the forger is one who, wishing to acquire a reputation for science, records observations which he has never made. This is sometimes accomplished in astronomical observations by calculating the time and circumstances of the phenomenon from tables. The observations of the second comet of 1784, which was only seen by the Chevalier D'Angos, were long suspected to be a forgery, and were at length proved to be so by the calculations and reasonings of Encke. The pretended observations did not accord amongst each other in giving any possible orbit. But M. Encke detected an orbit, belonging to some of the observations, from which he found that all the rest might be almost precisely deduced, provided a mistake of a unity in the index of the logarithm of the radius vector were supposed to have been made in all the rest of the calculations. ZACH. CORR. ASTRON. Tom. IV. p. 456. Fortunately instances of the occurrence of forging are rare. TRIMMING consists in clipping off little bits here and there from those observations which differ most in excess from the mean, and in sticking them on to those which are too small; a species of "equitable adjustment," as a radical would term it, which cannot be admitted in science. This fraud is not perhaps so injurious (except to the character of the trimmer) as cooking, which the next paragraph will teach, The reason of this is, that the AVERAGE given by the observations of the trimmer is the same, whether they are trimmed or untrimmed. His object is to gain a reputation for extreme accuracy in making observations; but from respect for truth, or from a prudent foresight, he does not distort the position of the fact he gets from nature, and it is usually difficult to detect him. He has more sense or less adventure than the Cook. OF COOKING. This is an art of various forms, the object of which is to give to ordinary observations the appearance and character of those of the highest degree of accuracy. One of its numerous processes is to make multitudes of observations, and out of these to select those only which agree, or very nearly agree. If a hundred observations are made, the cook must be very unlucky if he cannot pick out fifteen or twenty which will do for serving up. Another approved receipt, when the observations to be used will not come within the limit of accuracy, which it has been resolved they shall possess, is to calculate them by two different formulae. The difference in the constants employed in those formulae has sometimes a most happy effect in promoting unanimity amongst discordant measures. If still greater accuracy is required, three or more formulae can be used. It must be admitted that this receipt is in some instances rather hazardous: but in cases where the positions of stars, as given in different catalogues, occur, or different tables of specific gravities, specific heats, &c. &c., it may safely be employed. As no catalogue contains all stars, the computer must have recourse to several; and if he is obliged to use his judgment in the selection, it would be cruel to deny him any little advantage which might result from it. It may, however, be necessary to guard against one mistake into which persons might fall. If an observer calculate particular stars from a catalogue which makes them accord precisely with the rest of his results, whereas, had they been computed from other catalogues the difference would have been considerable, it is very unfair to accuse him of COOKING; for—those catalogues may have been notoriously inaccurate; or—they may have been superseded by others more recent, or made with better instruments; or—the observer may have been totally ignorant of their existence. It sometimes happens that the constant quantities in formulae given by the highest authorities, although they differ amongst themselves, yet they will not suit the materials. This is precisely the point in which the skill of the artist is shown; and an accomplished cook will carry himself triumphantly through it, provided happily some mean value of such constants will fit his observations. He will discuss the relative merits of formulae he has just knowledge enough to use; and, with admirable candour assigning their proper share of applause to Bessel, to Gauss, and to Laplace, he will take THAT mean value of the constant used by three such philosophers, which will make his own observations accord to a miracle. There are some few reflections which I would venture to suggest to those who cook, although they may perhaps not receive the attention which, in my opinion, they deserve, from not coming from the pen of an adept. In the first place, it must require much time to try different formulae. In the next place it may happen that, in the progress of human knowledge, more correct formula: may be discovered, and constants may be determined with far greater precision. Or it may be found that some physical circumstance influences the results, (although unsuspected at the time) the measure of which circumstance may perhaps be recovered from other contemporary registers of facts. [Imagine, by way of example, the state of the barometer or thermometer.] Or if the selection of observations has been made with the view of its agreeing precisely with the latest determination, there is some little danger that the average of the whole may differ from that of the chosen ones, owing to some law of nature, dependent on the interval between the two sets, which law some future philosopher may discover, and thus the very best observations may have been thrown aside. In all these, and in numerous other cases, it would most probably happen that the cook would procure a temporary reputation for unrivalled accuracy at the expense of his permanent fame. It might also have the effect of rendering even all his crude observations of no value; for that part of the scientific world whose opinion is of most weight, is generally so unreasonable, as to neglect altogether the observations of those in whom they have, on any occasion, discovered traces of the artist. In fact, the character of an observer, as of a woman, if doubted is destroyed. The manner in which facts apparently lost are restored to light, even after considerable intervals of time, is sometimes very unexpected, and a few examples may not be without their use. The thermometers employed by the philosophers who composed the Academia Del Cimento, have been lost; and as they did not use the two fixed points of freezing and boiling water, the results of a great mass of observations have remained useless from our ignorance of the value of a degree on their instrument. M. Libri, of Florence, proposed to regain this knowledge by comparing their registers of the temperature of the human body and of that of some warm springs in Tuscany, which have preserved their heat uniform during a century, as well as of other things similarly circumstanced. Another illustration was pointed out to me by M. Gazzeri, the Professor of Chemistry at Florence. A few years ago an important suit in one of the legal courts of Tuscany depended on ascertaining whether a certain word had been erased by some chemical process from a deed then before the court. The party who insisted that an erasure had been made, availed themselves of the knowledge of M. Gazzeri, who, concluding that those who committed the fraud would be satisfied by the disappearance of the colouring matter of the ink, suspected (either from some colourless matter remaining in the letters, or perhaps from the agency of the solvent having weakened the fabric of the paper itself beneath the supposed letters) that the effect of the slow application of heat would be to render some difference of texture or of applied substance evident, by some variety in the shade of colour which heat in such circumstances might be expected to produce. Permission having been given to try the experiment, on the application of heat the important word reappeared, to the great satisfaction of the court. 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. Charles Babbage (1998).Reflections on the Decline of Science in England, and on Some of Its Causes. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/1216/pg1216-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 , located at www.gutenberg.org https://www.gutenberg.org/policy/license.html

ON THE FRAUDS OF OBSERVERS.

Topographical Notes

Built on small pebbles

MASON BEES

MORE ENQUIRIES INTO MASON-BEES

THE LEUCOPSES

The Mason-bee of the Walls are erected on small-sized pebbles

THE MASON-BEES

THE FIRST MONTH (continued)

The Aptitude for Detumescence

Blockchain technology has been developing drastically with many applications and attracting more and more new users. The amazing technology has been utilized in education, agriculture, medicine, and especially trading. You may have known about coin and token, but how about NFT, a newly emerging term? What is an NFT? A brief history of NFTs In 2012, there was a need to store documents such as certificates, stocks, or licenses on blockchain leading to the birth of NFTs in 2017. It was the first time NFTs are used under the ERC-721 standard on the Ethereum network. It was not until 2021 that the glorious era of NFTs started. Definition of NFTs An NFT is a type of digital asset on blockchains. Every NFT has its own identification code and is used to represent a real-life asset such as a drawing, a song, or even a house. Therefore, they are unique and cannot be replaced or exchanged equivalently as usual tokens. (Non-fungible token) Clearly explained, if I have one USDT and you have another USDT, we can exchange for each other because basically, they have the same value, which means they are fungible. On the other hand, when I have an NFT and you have another NFT, we can trade our NFTs by using cryptocurrency or fiat but we cannot make any equivalent exchange because they have different values. That’s why they are called “non-fungible tokens”. Since NFTs are created on the blockchain, they obtain securable features such as immutable, sustainable, and explicit. Every NTF once minted on a blockchain cannot be altered and will be permanently stored on that blockchain’s public ledger that can be seen by everyone. Besides, an NFT cannot be split into smaller parts just as a coin or a token. How does an NFT work? NFTs run on a blockchain just like coins or tokens, but the difference is that NFTs cannot be traded equivalently. An NFT has its own value, but the price is set by the market. An NFT can be sold at a better price when it is scarce and many people want to have it. Sellers should know how worthy their products are to set suitable fixed prices or they can choose to sell by auction. Blockchain is well known for its decentralization. That means when NFTs are minted on a blockchain, creators can really own their works. Recently, most NFT marketplaces adopt a policy to offer NFT authors a passive income called loyalty. Moreover, when traded, every NFT transaction will be recorded, which enhances its transparency. As mentioned earlier, an NFT’s price can be volatile as cryptocurrencies depending on the market. If you want to trade an NFT, you should consider carefully the project and the blockchain of that NFT. Most NFTs are now minted and stored on the Ethereum blockchain, one of the most popular and prestigious blockchains. Some of the prominent NFT marketplaces are Opensea, Binance NFT, SuperRare, Rarible, etc. NFTs’ use cases NFT is now widely used in various aspects including gaming, collectibles, fashion, ticketing, and especially metaverse. Gaming NFTs are mostly used in gaming to represent characters’ skin or weapons. Gamers can actually own their in-game items. With multi-chain technology, they can even send their items to different accounts in other games easily. Collectibles Many artworks are now created and sold as NFTs, which helps to reduce counterfeiting and damaged by shipping. NFT is durable and will never be lost on the blockchain so it is the best solution for artworks and collectibles to maintain their quality forever. Ticketing Due to its uniqueness, an NFT can be used as a ticket to enter a music or sports event to reduce forgeries. Metaverse The metaverse is known as a virtual-reality space generated by computers in which people can interact with each other. NFTs play a vital role in accessing the metaverse. Every NFT is a representation as a key for users to get into the metaverse. Bottom line With the development of blockchain technology, NFTs have emerged as a necessity. NFTs have played an increasingly important role in entertainment and authenticity. The future of NFTs seems to be very bright and promising. However, if you want to invest in an NFT, you need to have some background knowledge and carefully consider many aspects to ensure you will make a profit.

An NFT: What it is and How it Works

To weather the COVID-19 storm and navigate the rapidly changing digital world, businesses are adopting at a faster pace. To help our clients sail through digital transformation and that deliver on their promise, we took up the challenge to identify AI trends and innovations that will define 2022. Here’s what we found. artificial intelligence create artificial intelligence solutions Factors Shaping AI Trends for 2022 Economy growth drives enterprise IT spending. Nearly two years after the onset of the pandemic, the global economy . The United States, China, Germany, and South Korea to pre-pandemic GDP levels per capita by the end of this year. Subsequently, worldwide IT spending this year (an 8.4% increase from 2020). Regarding AI spending trends, half of the businesses surveyed by Appen anything between $500,000 and $5 million in AI projects (34% up from 2020). The global AI spending, meanwhile, $83.5 billion. could accelerate 5.6% in 2021 are expected to recover is projected to reach $4.072 trillion are planning to invest could soon reach The global labor market sees a rapid change. Since Q4 2019, job openings in the United States , while the official number of last August. The paradox could be explained by the fact that COVID-19 has changed multiple industries, such as travel, hospitality, education, and healthcare. The pandemic-related health risks and policy rearrangements have only aggravated the unemployment crisis. In the meantime, the demand for skilled IT workers , reaching 26,800 new tech jobs in August in the USA alone (up from 10,500 jobs in July 2021). These factors could have a profound impact on artificial intelligence trends for the upcoming year. have surged 33% unemployed Americans reached 8.38 million has skyrocketed Cybercrime hits record high. Last year marked a drastic shift to online everything. Global eCommerce sales, for example, in 2020. The number of employees who use personal devices for work purposes . And before the pandemic, only 45% of executives security as an integral part of their companies’ strategy. As a result, the FBI last year than in 2019. The USA officials estimated the damage caused by different types of cyberattacks, including malware, distributed denial of service (DDoS), and phishing events, at a whopping $4.2 billion. Could artificial intelligence innovations possibly help enterprises lead through the cybersecurity crisis? grew by 27.6% has now reached 67% had regarded received 69% more cybersecurity complaints Enterprise struggle to implement AI at scale. Globally, businesses on artificial intelligence projects in 2020. Yet, just 11% of AI adopters on their AI investments. One of the common reasons for such lackluster results is a failure to get a buy-in from the C-Suite and scale AI innovations across the enterprise. According to a survey conducted by Alegion and Dimensional Research, 78% of all AI/ML projects between proof of concept (POC) and full-scale deployment. spent $50 billion saw a sizeable return come to a halt The environmental crisis is worsening. Recent reports indicate that Earth compared to preindustrial times. The temperatures could further rise by up to 2℃ in the next 30 years, causing irreversible damage to agricultural land, forests, and biological systems. By 2050, climate change could of the global economy’s total GDP. It’s high time enterprises leveraged AI advances to address climate change. has already warmed by 1.1℃ wipe off up to 18% National AI strategies emerge. As more economies recognize AI’s potential to boost growth, resilience, and productivity across public and private sectors, national artificial strategies are beginning to take shape. A total of 50 countries, including the United States, China, and the United Kingdom, in the works. The , for example, will focus on fostering and attracting AI talent, addressing the semiconductor shortage, battling cybercrime, and ensuring the country’s leadership in the artificial intelligence race. Through 2021, the Biden administration could pour $6 billion into artificial intelligence projects and initiatives, influencing AI trends for decades on end. have national AI strategies US artificial intelligence strategy Business AI Innovations and Trends to Watch in 2022 ROI-driven AI implementation AI-augmented automation Rise of responsible AI Use of AI in cybersecurity Environmental AI innovations AI Trend #1: More Companies Could Adopt an ROI-Driven Approach to AI Development “Launching pilots is deceptively easy but deploying them into production is notoriously challenging… Although the potential for success is enormous, delivering business impact from AI initiatives takes much longer than anticipated.” — Chirag Dekate, Senior Director Analyst at Gartner Some of the common reasons for AI projects’ unclear financial outcomes include: Limited access to quality training data A lack of resources and skills to implement artificial intelligence at scale A tendency to overcomplicate things — for instance, by using deep neural networks where simpler yet highly effective machine learning techniques could produce similar results A failure to gain buy-in at the executive level and proceed to a full-blown project Here at ITRex, we believe that one of the biggest artificial intelligence trends for 2022 (and the years after!) will be taking an incremental, ROI-driven approach to AI development. The concept of ROI-driven AI engineering and deployment pivots on: Fostering collaboration between business and IT teams, which could help companies decide on the business outcomes of deploying AI innovations beforehand and ensure C-Suite support Selecting a limited number of use cases for an AI pilot while devising a broader implementation plan early on Upskilling existing IT teams and enlisting the help of experienced artificial intelligence companies — either for turnkey AI system engineering or , such as discovery, cleansing, and labeling data preparation tasks Utilizing a powerful combo of SaaS, open-source, and custom-made AI solution components to speed up development cycles Ditching vast piles of historical data, which has become less relevant since the COVID-19 outbreak, in favor of wide and small data; the former is aggregated from a variety of sources, while the latter is easier to interpret and delivers instant insights Learning from failures, retraining algorithms on new data, and creating a continuous loop for machine learning model redeployment AI Trend #2: Enterprises Will Aim for AI-Augmented Automation “Last year, IT spending took the form of a knee-jerk reaction to enable a remote workforce in a matter of weeks. As hybrid work takes hold, CIOs will focus on spending that enables innovation, not just task completion.” — John-David Lovelock, Research Vice President at Gartner In the pandemic-ridden world, the role of information technology has shifted from supporting business operations to delivering business value. This change has had a profound impact on AI innovations and trends. A breakdown of AI use cases in business. Source Fueled by 5G rollouts, more powerful computer chips, the diminishing sensor prices, and flexible , the convergence of , artificial intelligence, and the technologies has become a viable reality. This powerful trio brings companies one step closer to and pervasive intelligence. cloud services robotic process automation (RPA) Internet of Things (IoT) AI-augmented automation From lightweight RPA robots that to self-checkout solutions that , recent advances in artificial intelligence will help enterprises achieve resilience and significant cost reductions. Here are some stats to prove it: take over payment processing tasks in healthcare know precisely which items a customer has put in the basket 80% of executives are their business process automation efforts (World Economic Forum) currently accelerating 25% of companies in workflow automation, while 51% of enterprises are planning to do so shortly (Salesforce) already use AI By 2023, 40% of infrastructure and operations (I&O) teams will use in large enterprises, freeing up IT personnel’s time for strategic work (Gartner) AI-augmented automation 66% of businesses by deploying artificial intelligence systems (McKinsey) have increased their revenue Through 2021, enterprise AI budgets have increased, with 74% of companies or more for their artificial intelligence projects, which marks a 55% increase from 2020 (Appen) allocating $500,000 AI Trend #3: Responsible AI Takes Center Stage “Responsible AI helps achieve fairness, even though biases are baked into the data; gain trust, although transparency and explainability methods are evolving; and ensure regulatory compliance, while grappling with AI’s probabilistic nature.” — Svetlana Sicular, Research VP at Gartner In their recent , David De Cremer and Garry Kasparov described AI-based machines as “fast, more accurate, and consistently rational,” noting, however, that present-day AI innovations often lack intuition, emotional intelligence, and cultural sensitivity. article for Harvard Business Review While end-to-end automation and subsequent workforce reductions are not yet among the artificial intelligence trends for 2022, governments will need to address the moral implications of artificial intelligence adoption in their national AI strategies, ensuring positive automation outcomes for all parties involved. When it comes to business AI, companies should focus on creating intelligent systems that and based on their ethnicity, age, gender, religion, or place of residence. Additionally, stakeholders need to clearly communicate automation benefits to get employees on board and encourage them to participate in AI deployment and training. explain the rationale behind their decisions do not discriminate against people These numbers indicate that ethical, responsible artificial intelligence usage will be one of the defining AI trends for the upcoming year: Through 2022, every company could have in development (CIO, Gartner) 35 AI projects 65% of companies how their AI systems make decisions and predictions (FICO, Corinium) cannot explain 78% of enterprises are poorly equipped to consider the ethical implications of using artificial intelligence (FICO, Corinium) Only 45% of businesses engage in ethical AI monitoring (FICO, Corinium) By 2023, all AI professionals a good grasp of responsible AI principles to secure a job (Gartner) will have to demonstrate AI Trend #4: Artificial Intelligence Will Lead the Cybersecurity Revolution “We’ve seen a lot of the ransomware attacks and what it’s done. And in particular, it has impacted business resiliency. It’s no longer the case of encrypted computer and, you know, Reimage, and carry on. It’s impacting massive amounts of business and costing hundreds of millions of dollars.” — George Kurtz, CEO at CrowdStrike Holdings, Inc. Using intelligent algorithms for cyberattack prevention became one of the most significant AI innovations of the past years. Forward-thinking enterprises leverage artificial intelligence to detect suspicious traffic within corporate IT networks, identify malicious software programs, spot infected links in employees’ emails, and even model cyberattack scenarios based on vulnerability assessments. The trouble is, the other side (i.e., cybercriminals) can do the magic too. For example, hackers can now manipulate the data used for AI model training, causing adversarial attacks. Other AI breakthroughs in the cybercrime field include inference, which allows attackers to access sensitive data by reversing AI engineer systems, and advanced social engineering techniques driven by behavior analytics. Additionally, hackers may employ AI to pinpoint security vulnerabilities in corporate IT systems. To address these looming threats, companies looking to deploy AI innovations should closely monitor all the data presented to AI models, review real-world data used for model training, and build the elements of randomness into their artificial intelligence models. Below you will find several statistics shedding light on artificial intelligence trends in the cybersecurity domain: Over use artificial intelligence to detect cybersecurity threats (Capgemini) 51% of enterprises Through 2021, 30% of organizations have already fallen victim to adversarial attacks — compared to just 12% in 2020 (FICO, Corinium) Hacking, customer fraud, and data breaches have grown in 2021 (FICO, Corinium) by 5–12% Automated cybersecurity solutions could increase the global revenue opportunities in the next five years (Accenture) by $5.2 trillion Between 2020 and 2027, the global AI cybersecurity market could be growing at a , topping $46 billion by the end of the given period (Meticulous Market Research) CAGR of 23.6% AI Trend #5: Artificial Intelligence Will Drive Sustainability in Enterprises “We cannot reduce what we cannot measure. Corporations ‘ climate action does not match our ambitions: one of the main reasons is that corporations don’t accurately measure their climate impact and track it enough over time. Fortunately, tools and techniques to help us exist, one of the most powerful ones is artificial intelligence.” — Charlotte Degot, Managing Director and Partner at BCG GAMMA Through 2022 and beyond, governments and businesses alike could turn to artificial intelligence to reduce reliance on fossil fuels, combat deforestation, and cut CO2 emissions. And while green AI innovations are still scarce at national levels, we’ve seen several commercial AI deployments that assist businesses in achieving their sustainability goals. Google, for instance, coupled their data center cooling technology with deep learning and reduced energy consumption . And CO2 AI, a novel sustainable artificial intelligence solution by Boston Consulting Group, helps enterprises by accurately measuring their carbon footprint and making intelligent recommendations. by 40% cut CO2 emissions by 30–40% These numbers prove that environmental sustainability is one of the hottest business AI trends for 2022: Artificial intelligence helps companies by up to 10% (BCG) reduce greenhouse gas (GHG) emissions The use of AI for GHG emission monitoring could result in $208–424 billion savings for global companies in the coming years (BCG) Artificial intelligence could in achieving 93% of the environmental sustainability goals defined by the United Nations (Springer Nature Sustainability Community) aid the world The growing adoption of sustainable AI systems could create up to globally (PwC) 38.2 million jobs The economic impact of AI-driven environmental solutions could reach $5.1 trillion by 2030 (PwC) If you need help navigating the emerging artificial intelligence trends or implementing AI innovations, please ! Together you’ll build a brighter, safer, and greener future! contact the ITRex team Also published . here

Top 5 Business AI Innovations and Trends to Watch in 2022

Exploring JavaScript and Smart Contracts with Agoric CEO Dean Tribble

Explorando JavaScript y contratos inteligentes con el CEO de Agoric, Dean Tribble

Explorer JavaScript et les contrats intelligents avec Dean Tribble, PDG d'Agoric

एगोरिक सीईओ डीन ट्रिबल के साथ जावास्क्रिप्ट और स्मार्ट कॉन्ट्रैक्ट्स की खोज करना

Agoric の CEO である Dean Tribble と JavaScript とスマート コントラクトを探る

Explorando JavaScript e contratos inteligentes com o CEO da Agoric, Dean Tribble

Khám phá JavaScript và Hợp đồng thông minh với Giám đốc điều hành Agoric Dean Tribble

与 Agoric 首席执行官 Dean Tribble 一起探索 JavaScript 和智能合约

If you’ve been considering whether voice technology is worth paying attention to or if it’s just a trend, you’ll find this article useful. Even the most ardent doubters must admit that voice-based solutions are gaining popularity faster than many other advancements, which is highly questionable. To dispel any doubts, let’s go over the statistics. , the number of voice assistants could hit 8.4 billion by 2024, surpassing the global population. Besides, that the worldwide voice recognition industry is expected to expand from 10.7 US$ in 2020 to 27.16 billion US$ in 2026. That being said, we can notice the huge expansion of the market, and that could trigger the majority of apps to correspond to the level and undertake an upgrade. According to projections Statista estimates Surely, the cold figures are not enough to make a decision, so we are going to highlight a few valuable reasons to consider Voice technology, which are going to influence both users and your profit. So, let’s get to the point. Major reasons to consider Voice Technology Competitive advantage Certainly, we mentioned that the number of voice assistants will increase to impossible heights, but it doesn’t mean that making your app a part of this number will be a bad idea. If you narrow down the industry you are going to fill in with the new app and conduct research on the competitors – you’ll be very pleased to see just a few of them or even none with voice assistants’ integration. Implementing new technologies, especially those that require the application of AI and Machine Learning, will definitely create a competitive advantage over the other apps. And even if you think that there is no way how you can integrate voice recognition – think harder. Voice ordering along with voice technology could facilitate any task and any feature for the user, whether it is a Transportation Management System (here you can add the possibility to administrate parcel delivery with the voice), or an Online Tutoring Platform (here users could schedule classes, and manage audio material with their voices). 24/7 Availability for Users Users’ orders and queries can be responded to at any moment by sophisticated voice assistants. Furthermore, because AI can so closely mimic an intellect, many repetitious jobs may be successfully mechanized. As a result, voice technology may be the most cost-effective approach for a company to increase customer happiness while also growing its customer base. As for another benefit, if you’ll extend the time spent in your app to 24/7, you’ll get the possibility to interact with them longer, which is equal to higher user engagement and leads to more profit. Production efficiency For the users, the efficiency starts right after they turn on the voice ordering/voice recognition. With that function, they can do several tasks at a time. This affects their satisfaction with the app and attracts more customers. The other issue is that businesses are constantly seeking methods to improve their efficiency. As a result, numerous executives have begun to use voice technology for company management as well, by implementing it to the internal operations. With AI-trained voice assistants, the workflow happens faster, because multiple tasks could be conducted by the machine, with a simple order from an employee. Customization Voice technology offers data that can help you comprehend your target user. For example, you can look at how many times a specific type of voice search query led a person to your webpage. This provides you with information on the user’s browsing and purchasing habits. With such information, you can create better marketing strategies, and upgrade an app to fulfill the users’ demands. Which is obviously important for further app’s presence on the market range. Now, when you ascertained what voice technology could mean to your app, it’s time to acknowledge how to apply this innovation into your idea, and how to deploy it. For your convenience, we gathered below a simple guide for you. Just keep reading! Part #1: Installation First of all, you need to create an . After that, you can go to and start creating your first Alexa skill. To do so, you need to decide on the skill name. The skill name could be everything, however, the creation implies to make it customized and unique, so there is no plagiarism on the market. For the example, we chose ‘Incora assistant’. Amazon account on Alexa Developer Console The next step is to choose a model between pre-built ones and custom made. Surely, it’s your choice, but we recommend picking up a Custom option and building it through your efforts. With that, you need to decide on a method to host your skills. You can use Alexa-hosted variants for personal training. Although for production, we recommend hosting the Lambda function on AWS, so in that case, you should select the block ‘Provision on your own’. To get started, Alexa’s interface offers to choose a template for establishing backend code and interaction model. And once again, if you agreed upon creating a unique solution, click on the ‘Start from Scratch’ option. Finally, when the initial preparation is over, you can continue building your Voice Technology. Now, you need to figure out the Skill Invocation name. Make sure to find a phrase or a word, that will be easy to remember and spell for the user. Apparently, it could be similar to the Skill name. When you are done, don’t forget to save and build the model after each change you made. Hence, now you can create your own intents. An intent is an action that takes place in response to a user’s voiced request. In the sidebar go to ‘Interaction Model’ and then click on ‘Intents’. There you can create custom intents. Afterward, you should generate sample utterances. The sample utterances are a collection of plausible spoken sentences that have been aligned to the intents. Then create a Lambda function. To do this, we use Node.js, serverless, and Alexa ask-sdk. Let’s start writing some code. We need to create handlers for standard Alexa intents, including several paths to the file with different requests. You can find them below. src/handlers/LaunchRequestHandler.js const LaunchRequestHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'LaunchRequest'
 },
 handle (handlerInput) {
   return handlerInput.responseBuilder.
     speak('Welcome to Incora assistant. You can ask about technology stack, projects, and a lot more').
     reprompt('What\'s your request? ').
     getResponse()
 }
}

module.exports = LaunchRequestHandler src/handlers/HelpIntentHandler.js const HelpIntentHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'IntentRequest'
     && handlerInput.requestEnvelope.request.intent.name === 'AMAZON.HelpIntent'
 },
 handle (handlerInput) {
   return handlerInput.responseBuilder.
     speak('You can say: \'alexa, hello\'').
     reprompt('What\'s your request? ').
     getResponse()
 }
}

module.exports = HelpIntentHandler src/handlers/FallbackHandler.js const FallbackHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'IntentRequest'
 },
 handle (handlerInput) {
   return handlerInput.responseBuilder.
     speak('Can you repeat it, please? ').
     reprompt('What\'s your request? ').
     getResponse()
 }
}

module.exports = FallbackHandler src/handlers/ErrorHandler.js const ErrorHandler = {
 canHandle () {
   return true
 },
 handle (handlerInput, error) {
   console.log('ERROR HANDLED', error)
  
   return handlerInput.responseBuilder.
     speak('Sorry, I had trouble doing what you asked. Please try again. ').
     reprompt( 'What\'s your request? ').
     getResponse()
 }
}

module.exports = ErrorHandler src/handlers/CancelAndStopIntentHandler.js const CancelAndStopIntentHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'IntentRequest'
     && (handlerInput.requestEnvelope.request.intent.name === 'AMAZON.CancelIntent'
       || handlerInput.requestEnvelope.request.intent.name === 'AMAZON.StopIntent')
 },
 handle (handlerInput) {
   return handlerInput.responseBuilder.
     speak('Goodbye ').
     getResponse()
 }
}

module.exports = CancelAndStopIntentHandler src/handlers/SessionEndedRequestHandler.js const SessionEndedRequestHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'SessionEndedRequest'
 },
 handle (handlerInput) {
   // Any cleanup logic goes here.
   return handlerInput.responseBuilder.getResponse()
 }
}

module.exports = SessionEndedRequestHandler Here you should add the custom handler for this intent such as ‘TechnologyStackIntentHandler’. src/handlers/TechnologyStackIntentHandler.js const TechnologyStackIntentHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'IntentRequest'
     && handlerInput.requestEnvelope.request.intent.name === 'HelloWorldIntent'
 },
 handle (handlerInput) {
   // add your own logic
   // get data from some API, database, etc.
   return handlerInput.responseBuilder.
     speak('Our technology stack comprises JavaScript (Node, Angular, React, Ember, Vue), Python (Django), Mobile apps (React Native, Ionic).').
     reprompt( 'What\'s your request? ').
     getResponse()
 }
}

module.exports = TechnologyStackIntentHandler For the next step, you need to have or create an . Set AWS credentials on your local machine. Configure file and run yarn deploy or npm run deploy. AWS account serverless.yml serverless.yml service: alexa-lambda-example

plugins:
 - serverless-pseudo-parameters
 - serverless-iam-roles-per-function

provider:
 name: aws
 runtime: nodejs14.x
 region: us-east-1
 stage: prod

functions:
 info:
   handler: src/index.handler
   events:
     - alexaSkill: amzn1.ask.skill.XXXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXX After that, you can go to the AWS lambda function and copy ARN. Go to the Alexa developer console and set your AWS lambda ARN as an endpoint. Finally, your skill is built, and you can try to test it using the Alexa developer console or any Alexa device. Don’t forget to switch to development mode in ‘Test’ inside the navigation bar. To test and provide assurance of the code, we deployed it to the developer console. After the testing stage, at long last, you get yourself a voice assistant. The next step would be just to integrate it into the hardware system. Part #2: AWS Cognito and Alexa Skill Account Linking Since in the first part we’ve highlighted the process of the initial installation of Alexa skill and the development of the custom Voice technology, here we are going to focus on the next stage needed – Account linking. These operations are required for user recognition, so your voice assistant would identify the person who is entering the system. So, account linking should help in building a user’s background for more personalized interactions and offer customized solutions. Simply said, by means of account linking, your voice technology collects all the data about users, and applies those information to reduce bothering questions for profile identification. This will be done automatically. However, let’s get down to this concept in depth. What is Account Linking regarding Alexa Skill? Certain personalized skills necessitate the option of adding the user’s identity to the other’s system user. The purpose is to establish a relationship between the Alexa user and your system’s user account. Account linking allows you to securely authenticate users with services using your skill. Once the skill and external user account have been connected, the skill can perform tasks from the user with that account. Account linking is conducted with the integration of OAuth 2.0. OAuth 2.0 is an open protocol that enables online, mobile, and desktop programs to request user authorization from remote services in a standard-compliant way. You may create your own OAuth server and identity management solution from scratch. But, to achieve the same result, you can utilize AWS Cognito that will assist you in developing a custom identity recognition. AWS Cognito uses User Pools, which are scalable user registry that can handle millions of members. User Pools is a fully managed service that is simple to set up without the need to worry about setting up server infrastructure, and it uses technical standards such as OAuth 2.0 to interrelate with your backend. Thus, below we will describe the process of Account Linking setup with the help of AWS Cognito since it will result in a custom-made service. But first, let’s discover the advantages. Advantages of Account Linking Account linking is a preferable method for those who want to develop a user-friendly solution, convenient for the target. But in detail, what are those benefits, that could convince you to establish Account linking for your Alexa skill? Users can omit the creation of new profiles for each platform separately, which decreases configuration time and increase users engagement. Account linking allows registered users to keep employing their old account while using a new social or passwordless access. It is convenient for users who enrolled without a password to join their profile to one with more details. Apparently, your application could integrate the user recognition, which will gather data from the other sources and fill in the missed gaps on your system’s profile. It allows your software applications to access profile page details kept across several sessions. Considering the advantages listed above, now you might question how to generate Account linking for your voice technology application, and adjust it to your needs. To learn more about that practical part of the process, follow further instructions. Getting started First of all, you need to go into select your skill, click and then in your left sidebar**.** Alexa Developer Console Tools Account Linking The first phase is to configure the users’ access and action within account settings. We recommend, to allow users to create an account or link to an existing account with you and enabling skill without account linking. Under the block you should select as an authorization grant type. Exactly this type is used so that the user could obtain access tokens from the authorization code. Securite Provider Information Auth Code Grant User Pool’s Setup For the next step, you need to have an existing AWS Cognito User Pool or create a new one and set it up. To do so, move onto the . There we will set up User Pools in order to get the client id and secret id, which will be needed for the further configuration on the Alexa Developer Console. AWS Cognito page Step 1: Sign in options At the first step of User Pool’s Configuration, you should choose the way how the users will be able to sign in. Between the options Username, Email, and Phone Number, we choose Email and go on to Step 2. Step 2: Security Here you need to decide on the ways how to make the user experience with account linking more securable. For that purpose, you need to choose the password requirements and authentification method. For illustrative purposes, there is no need to write a custom policy, so we select the defaulted parameters. The same is with multi-factor authentication, there is no need for us to choose MFA, so we preferred the No MFA option. However, when developing your own solution, you can decide which measurements to set, and define customized requirements. At this stage, you also need to configure the possible solutions for the users, when they forget their passwords. We definitely recommend enabling self-service account recovery, since it would be a common issue for each platform. And as a delivery method for the account recovery, we choose Email. Step 3-4: Sign-up options and Message delivery These steps are completely optional, and won’t affect the Account linking. Hence, we omit the instructions on them. You can also skip them as we did, or set up complying with your needs. Step 5: App integration Let’s create the User Pool Name. As this is the example, we selected ‘Test User Pool’. Then we enable to use the AWS Cognito Hosted UI, since here is the part important for the following process we highlight in this article, namely AWS Cognito and Alexa Skill Account linking. Then we configure a domain for the endpoints. Below we provided the screenshots to demonstrate this phase of the setup. Now you need to copy callback URLs from Alexa Developer Console and insert them into the provided fields. After all of the passed steps, you should set the sign-out URL. Since on the screenshot below, there is not the full version, here is the template we outlined for you: https://{YOUR_DOMAIN}.auth.us-east-1.amazoncognito.com/logout?response_type=code * Step 6: Configurations approvement Now you just need to submit all the changes you made and move on to the next stage of the Account linking process. Auth Code Grant Layout All the steps above lead to the formation of the client id and secret id. So, you copy that data from the tab . ‘ Test User Pool → App client: Alexa client’ Then, you should return to Alexa Developer Console and finish the initial configurations. Here are the templates of the full URIs: : Web Authorization URI https://{YOUR_DOMAIN}.auth.us-east-2.amazoncognito.com/oauth2/authorize?response_type=code&redirect_uri=https://pitangui.amazon.com/api/skill/link/{CODE} : Access Token URI https://{YOUR_DOMAIN}.auth.us-east-2.amazoncognito.com/oauth2/token For the last step, you need to create and connect AccountLinkingHandler in your Lambda function. src/handlers/AccountLinkingHandler.js const AccountLinkingHandler = {
 canHandle(handlerInput) {
   return !(
     handlerInput.requestEnvelope.session.user &&
     handlerInput.requestEnvelope.session.user.accessToken
   );
 },
 handle(handlerInput) {
   return handlerInput.responseBuilder
     .speak('Please link your account to the Incora assitance skill using the card that I have sent to the Alexa app. ')
     .withLinkAccountCard()
     .getResponse();
 },
};

module.exports = AccountLinkingHandler; Finally, you can use userAccessToken for getting any information from your system for personalization. An example of how to obtain accessToken can be found below. JavaScript const TechnologyStackIntentHandler = {
 canHandle (handlerInput) {
   return handlerInput.requestEnvelope.request.type === 'IntentRequest'
     && handlerInput.requestEnvelope.request.intent.name === 'HelloWorldIntent'
 },
 handle (handlerInput) {
   // add your own logic
   // const userAccessToken = handlerInput.requestEnvelope.session.user.accessToken
   // now you can use userAccessToken for getting any information from your system for personalization
   // get data from some API, database, etc.
   return handlerInput.responseBuilder.
     speak('Our technology stack comprises JavaScript (Node, Angular, React, Ember, Vue), Python (Django), Mobile apps (React Native, Ionic).').
     reprompt( 'What\'s your request? ').
     getResponse()
 }
}

module.exports = TechnologyStackIntentHandler That’s it, the account linking is already successfully adjusted and ready to be used! Now, your voice assistant is much closer to user satisfaction. Concluding Voice technology is the future of each industry. The potential of voice recognition will only grow as AI and Machine Learning advance, bringing usefulness to the market. Voice technology introduces a completely new manner of communicating with clients and enhances their engagement. Github code sample of the Installation Process. Github code sample of Account Linking. First published here: / Part 1 Part 2

Introductory Guide to Voice Technology Implementation

Introduction With the growing demand to provide online services for the business, the modern infrastructure like Cloud Native, Containers, Kubernetes, and Service Mesh has become the de facto choice for enterprises to adopt and implement the solutions. While adopting Modern Software Infrastructure for new applications services or migrating legacy applications to the cloud, modern software architecture is playing a major role in defining how to adopt modern infrastructure for the enterprise. What is Software Architecture? There is no right definition defined to refer to what Software Architecture is. Many industry experts have their own definitions of software architecture. In Simple “The Architecture is a set of Software Structure or Structures”. Software consist of core systems, subsystems, and components and a Structure is a set of components and its relationships. What should Good Software Architecture consist of? The software architecture is not just to define components and its relationships but there is much more to add, like having target state roadmap, making strategic decisions, adopting the right architecture style/pattern, identifying the right technologies for building the software application or services, applying Architecture Characteristics. Also, understanding risks and non-functional requirements, and most important is to document and communicate to the stakeholders. A Software Architecture serves as a blueprint vision for the development teams which will define business requirements and their expectations from the system. The Software Architecture is a continuously evolving process which compressed with architectural design patterns and technical/strategic decisions. By building effective architecture we can identify design risks and mitigate them early. Good Software Architecture is to adopt the right architecture style and define its architecture characteristics which will help to maintain the quality of the software throughout its lifetime. Architecture Characteristics Any successful architecture depends on how well we define the Architecture Characteristics. There are many System Quality Attributes we can discuss but for me, the following Architecture Characteristics make a strong foundation for modern software architecture to develop a successful product. https://en.wikipedia.org/wiki/List_of_system_quality_attributes 1. Understandability: When defining the Architecture Structure our goal should not be just to make an effective software architecture structure. But It should able to communicate easily, quickly understood by development teams and stakeholders at the same time it should meet the business requirements. When a new developer joins the product team they should able to understand the software architecture with a short introduction. Considerations for Understandability: Understand your stakeholders what each team is required from the application. Understand the strengths and weakness of the development teams 2. Usability & Learnability: Achieving the Usability of a software product depends on a number of factors like target users, UX experience, and ease of using Product features. We need to consider what exactly Users want and What we are providing to users. Also, we need to understand how the target users intend to use the Software product or Application. The features provided by the software product/application must fulfill the User within the context and these features should be clearly visible to the user. The success of a product depends on how well users use the Software application or product and how easy the user can learn new application/product features. Also, the architecture decision to adopt new technology or frameworks the architect should be aware of how easy to learn or adopt the new technology or framework quickly by the developer. Considerations for Usability & Learnability: Know what kind of users will be using the Application adopt Accessibility Guidelines if required. All features of the application should be easily visible and accessible. Do good research on the adoption of new technology and framework. 3. Securability: The Application exposed on the web always has a risk of cyber-threats, if the application accessed by unauthorized users. Application security is responsible to stop or reduce cyber-threats, accidental actions, data theft, or loss of information. There are numerous ways to secure the application like authentication, authorization, auditing, and data encryption. The well-designed security for a Software application is to restrict user access based on Authentication and Authorization, Ability to detect and protect from DDoS attacks, prevention of SQL Injection, Ensuring the passwords are encrypted and secured as per password policy, and making sure the application communicates on Secured Protocols. Considerations for Securability: What Authentication mechanism to adopt and what roles should be given to different application features. Ensure Application communicates on Secured Protocols All passwords should be encrypted and secured Design to detect and protect DDoS Attacks and SQL Injection Data Encryption, Confidentiality & Integrity Auditing of User Activities on the Application 4. Reliability & Availability: When designing software architecture one of the key characteristics of the Application is Reliability & Availability. Reliability is an attribute of the system responsible for the ability to continue to operate under predefined conditions. Most times, the system fails due to the inaccessibility of external components like databases, external applications, and network connections. Availability of the Application is calculated based on Total Operation Time divided by Total Time this is expressed in percentage like 99.9%, it is also expressed in the number of 9s. For example, if our application availability is 99.9% (which is three 9s) then in a year we have a downtime of 8 Hours 45 Minutes for our application. Also, we have to consider if our application is dependent on other applications we have to consider the availability of depending application. Availability Calculator: https://uptime.is/99.9 Considerations for Reliability & Availability: When Application or Service is not available. What is required to recover the application whether it is automated or manual? How long we can take downtime? Does it meet Business SLA’s How the application will be sending notifications when a failure occurs. What is the resilience plan for the application? 5. Interoperability: Most of applications services are required to communicate with external systems to provide full-fudged services. A well-designed software architecture facilitates how well the application is interoperable to communicate and exchange the data with external systems or legacy systems. It is easy to design interoperability between well designed external interfaces and standardization systems. But we will have a lot of challenges with external systems or legacy systems which are poor quality and lack of standards. Considerations for Interoperability: Different Data formats need to considered for interacting with external systems. Quality of API and Different Versions of API Backward Compatibility. Possibility of rebuilding with industry standards. 6. Testablity: An industry estimates 30 to 40 percent of the cost is taken by Testing. The role of Software Architect to ensure they design every component can be testable. A Testable Architecture should clearly show all the interfaces, application boundaries, and integration between components. Testability is the ability to test different components and events of the Application. We should able to script to create the Test Environment, so It will enable developers and testers to quickly reproduce similar scenarios that occurred in production so they can quickly identify the issue and provide the fix or solution. Considerations for Testability: All the Business Requirements and NFR’s should be consistent and completely testable. Ensure All the environments DEV, TEST, UAT, and PRODUCTION are similar. All the components should be testable and even with limited resources. All the Integration points of the application should be testable. Capture the test results for internal and external testing. 7. Scalability: Over time business will grow and the number of users of the application will grow 1000’s to 100000’s. When the load gets increased the application should able to scale without impacting the performance. There are two types of scaling vertical scaling/scaling up and horizontal scaling or scaling out. Vertical Scaling is adding more hardware CPU/Memory/Disk to the existing server.Horizontal Scaling is to divide the load and respond to the requests by adding more servers/instances to the cluster of servers. This is more cost-effective as we can start with small and add more when the load increase on the application. Considerations for Scalability: Total number users during Peak Hours and Non-Peak Hours Amount of Data gets generated to scale Database or Storage How much of CPU, Memory, or IO-intensive operations required to scale Number of Concurrency Operations performed with in the application Long-Running Functions or Operations within the Application 8. Performability: The performance of the application is one of the key factors in Software Architecture. This characteristic is achieved by how well we design other Architecture Characteristics one of them is Scalability as discussed in the above. Performance is the ability of the application to meet timing requirements such as speed & accuracy. The performance score is generally measured on throughput, latency, and capacity. Throughput: Number of requests executed within givenLatency: Total Time taken to respond to each request or a specific request.Capacity: Number of requests handled while meeting throughput and latency. Considerations for Performability: Horizontal Scaling increases the number of instances, memory, and network bandwidth Load Balancing to route the requests to different available instances Parallel Processing or Concurrency Caching Solution Data Partitioning or Replication 9. Agility: Business and Stakeholders continue to demand rapid changes or innovation of the application or product to meet Time to Market. Agile practices are used to meet the demand and deliver features to meet Time to Market. But underlying architecture is always overlooked. To bring in agility in Architecture we should follow the direction of “Informed anticipation” the architecture should not over anticipate and design the application which will delay the application delivery and adding over complexity for the developer to build. At the same time, it should not under-anticipate future demands of the application which will risk developing features in the absence of architecture guidance. Architecture agility requires “just enough” anticipation. To achieve this “Just Enough” architecture anticipation is must be “informed” there are several methods to get informed like dependency analysis, product backlog, and technical debt. Considerations for Agility: Architecture development should follow the “Just In time” model. Maintain continuous focus on emerging customer-facing features. Focus on User Stories which over time can lead to increased complexity. Analysis of Product Backlog and Technical Debt items. 10. Observability: Applications and Services are developed using different architecture styles like microservices, serverless, and event-based. They getting deployed to modern infrastructures like cloud, hybrid cloud. The Applications consume these services as distributed functions across different infrastructures. To maintain the stability and performance of the application we should closely observe and monitor. Monitoring has become key to maintain the health of these services. Observability is not just a new fancy term for monitoring. Observability adds much more along with actionable insights along with monitoring like log aggregation/analytics, Notifications. Considerations for Observability: Central Log management by effective instrumentation to collect telemetry, logs, events, metrics, and traces. Define the context for Notifications when things go wrong. So DevOps can act quickly to resolve Have a visualization dashboard to make it easy to understand and convey what’s happening and why it is happening. 11. Fault Tolerance: When designing applications or services that will communicate different systems on different infrastructure and they tend to partial failure or full failure due to Network Latency, Broken Connection, or any other reason. In the event of these failures, the Architect should design where Application or Services should continue to its operation possibly at a reduced level in the event of failure. There are two types of tactics that can be adopted at design time and runtime. During the design time, we can expect what return values are expected from each operation and make sure there are no buffer overflows. At runtime failure, we should adopt what second-best action to be taken in case of failure to make sure the system continues to run. Considerations for Fault Tolerance: Detect all the Design Time and Runtime Failures of all components within the application and take corrective action. Define recovery actions in case of full failure Adopt prevention actions Final Thoughts: I tried this article to present my thoughts on what modern software architecture characteristics should be. Each of these characteristics deserves a longer discussion and also there other characteristics which are not touched. We can still debate what is considered a “good software architecture” for me the core characteristics laid out in the article considered good architecture. I am still open to your thoughts for discussion and debates. References: https://martinfowler.com/architecture/ https://learning.oreilly.com/library/view/fundamentals-of-software/9781492043447/ https://learning.oreilly.com/library/view/software-architecture-in/9780132942799/

The Eleven Defining Characteristics of Modern Software Architecture

Las once características definitorias de la arquitectura de software moderna

It is known that the separation between software development teams as well as information technology operations teams that faced many problems in it.  After witnessing this problem, the web-developers came with the idea of developing DevOps which is considered to carry roots in the Agile methodology. The basic function of DevOps is to integrate the set of two teams to improve their collaboration and productivity. Thus there are many different types of definitions citing the concept and practical applications stating how useful the DevOps can be and it also defines that the concept behind its formation is multi-layered. Therefore most of us will surely agree to the fact that continuity and automation are constituted as the big parts of DevOps and probably it is one such tool that helps team members to ensure that these two are the elements that can be implemented possibly as we thought of. Moreover, the organization's specific needs are said to determine that the tools are considered to be the best for them to smooth the functioning of the production process. Given below are the list of best DevOps Tools that will definitely guide in how you could resolve the errors while working on big projects. 1. Docker- A self-reliant tool to solve all queries Docker is considered as the Linux-based open-source platform that focuses on containers and also implies the packaging of the software along with the dependencies and does ship everything together like a unit. It allows one to need not worry about managing dependencies as they can also be managed separately. It is known to be portable and highly securable too and even allows you to use any other language with it too. This tool is also known for integrating seamlessly with the arising number of other tools like Jenkins, Ansible, and Bamboo. It has been revealed by the research firm Forrester has stated that Docker will become the leading company in the field of enterprise . container platform category in the year 2022 2.  Ansible- Sensitising the configuration management through simplification It has been revealed by the that Ansible has become the most favored software automation for the DevOps. CIO It is regarded as the open-source tool for automating software that is efficient for offering provision, configuration management as well as application deployment which can be easily accessed and one doesn’t need to have the set of a dedicated systems administrator. Its functionality uses a simple syntax that uses the YAML language whereas NASA uses Ansible. No special coding skills are required and allow one to model even highly complex IT workflows. 3. GIT - A Retrieving source to view the codings of the past. Git is the highly popular open-source tool that is used by industry giants like Microsoft, Amazon as well as Facebook too. It enables one to track down the progress of their development work and also allow them to coordinate work among their team members. In simpler words, it is the tool that is used to give greater work and also allow one to revert to previously saved versions of the work. It also allows one to create branches separately and even led them to add-in the new set of features especially at the time when they get ready. Thus, a web developer simply needs to host the repository of the work like GitHub. Highly helpful in creating branches that provide an isolated environment for every recurring change in the coding databases. 4. Puppet - Quite helpful in automating and delivering of the software It is a DevOps tool that allows one to manage and automate software inspection and also help in the delivery and management of the business operation. It is considered as the open-source tool that carries a solid track record as well as thousands of modules that could easily integrate with many different platforms. With the help of Puppet, Enterprise one could easily manage the bigger as well as the smaller projects too. Moreover, it also allows one to manage multiple teams as well as thousands of resources. Holds the ability of working on larger infrastructure simply by automating the repetitive tasks. 5. Chef - Capable of configuring cloud-based applications It is considered as the most powerful open-source configuration management tool that allows one to turn their infrastructure into the codes that lets web developers manage data, attributes, roles, and much more. It is the puppet competitor and is known for supporting multiple platforms and can seamlessly integrate with cloud-based platforms. Irrespective of whether the size of the organization is big or small, this tool can automatically configure the infrastructure as well as application deployment and can manage the configurations across the network. It accelerates cloud adoption, improvised the risk management and accelerates software delivery. 6. Jenkins - A Quick tool to resolve coding errors It is the tool that is known for quickly resolving the issues in code and is a free and open-source tool used for automating the delivery pipeline and even allows one to test and report changes in real-time. It is the platform that carries a huge plugin ecosystem and seamlessly integrates with almost every DevOps tool and it also runs efficiently on Windows, Mac OS X, and Linux. To , It requires little maintenance and has built-in GUI tools. start with jenkins 7. Nagios - An Undisputed king to monitor network protocols It is used to find and correct problems that lie in networks and infrastructure, and it is one of the most popular free and open-source monitoring tools. Nagios Core and Nagios XI are the two Nagios editions that are known for offering many features that provide greater functionalities. These tools are used to monitor applications, Services, network protocols, and forum support are also available. It serves as the fast platform to detect outages and protocol failures and works efficiently in boosting the infrastructure of software. 8. Splunk - An advanced Tool that curates machine data It is one such DevOps tool that curates the machine data and even access logs and is said to be usable by almost everyone on the team. Since the machine data comprises a lot of information and is known for improving productivity as well as efficiency, thus it becomes hard for anybody to analyze and visualize that too without using a tool like Splunk. It allows web-developers to build custom-based Splunk applications and integrate it with Splunk data that too in other applications. It doesn’t require any database to store the data and exclusively makes the use of indices to store data. Conclusion In the end, it can be concluded that DevOps tools like , and much more will not only resolve the dispute in the coding but will structure the B2B website in such a manner that it will always remain on the top page of Google. Nagios, Jenkins, Puppet, Chef These tools are quite helpful in removing the technical errors from landing pages and also help in strengthening the founding roots of a website by allowing the digital marketing techniques to blend well with the AWS (Amazon Web Service) and other cloud computing platforms that enable the web-developers to build apps that are multi-functional and help in regaining the clicks of the customers. Moreover, in the coming age of artificial intelligence (AI), it will become very much crucial for web-developers to understand every detail about the significance, importance, and the practical usage of DevOps tools.

DevOps Tools That Will Help in Rectifying Errors in the Databases

Stories, News & Mentions about SICURA

Sicura’s Stories on HackerNoon