All about ElifTech, a tech company providing software development solutions for businesses. Discover our services and learn more about our approach.

ElifTech – Software Development & Consulting Company

ElifTech | 1,724 followers on LinkedIn. Business-savvy software engineers ready to work for you | ElifTech is a young, ambitious and trusted global technology service company that designs, builds and implements effective software technology solutions supplying the needs of your business.

ElifTech | LinkedIn

ElifTech is a technology service company that designs, builds, and implements software technology solutions for its customers.

ElifTech - Crunchbase Company Profile & Funding

ElifTech has expanded a hotel booking company’s capabilities by adding new backend integrations. They’ve connected the client’s web-based APIs with third-party partners using Golang through the client’s system.

ElifTech Client Reviews | Clutch.co

We are a young, ambitious and trusted global technology service company that designs, builds and implements effective software technology solutions, fulfilling the needs of customers’ businesses.We...

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ElifTech has 5 employees across 3 locations. See insights on ElifTech including office locations, competitors, revenue, financials, executives, subsidiaries and more at Craft.

ElifTech Company Profile - Office Locations, Competitors, Revenue, ...

Any Twilio people here that can speak to overall company culture and work/life balance? ... Pros- Ability to improve professional skills gain other different skills that could make you a T-shaped specialist - There is always someone who will help you - It&#x27;s fun there · Cons- Due to a high intensity of the Ukraine market there is a turnover See All 4 Reviews ... I applied through a recruiter. The process took 5 days. I interviewed at ElifTech ...

Working at ElifTech | Glassdoor

ElifTech is an ambitious and trusted global technology service company that designs, builds and implements effective software technology solutions supplying the needs of your business. We cover all aspects of software product development using the latest technologies and frameworks, and quickly ...

ELIFTECH Reviews | View Portfolios | DesignRush

View ElifTech (www.eliftech.com) location in Lviv, Ukraine , revenue, industry and description. Find related and similar companies as well as employees by title and much more.

ElifTech - Overview, News & Competitors | ZoomInfo.com

Elif is a global supplier of flexible packaging solutions for food, beverage, pet, home and personal care industries.1

Welcome to Elif

Elif | 17,551 followers on LinkedIn. Sustainable Packaging for Life | Elif, a Huhtamaki company, is a benchmark flexible packaging provider. Since September 2021 Elif has been part of Huhtamaki, a key global provider of sustainable packaging solutions for consumers around the world.

Elif | LinkedIn

Information on acquisition, funding, investors, and executives for Elif Holding. Use the PitchBook Platform to explore the full profile.

Elif Holding Company Profile: Acquisition & Investors | PitchBook

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HUHTAMÄKI OYJ PRESS RELEASE 23.9.2021 AT 17:30 · Huhtamaki completes the acquisition of Elif, a major supplier of sustainable flexible packaging to global brand owners

Huhtamaki completes the acquisition of Elif, a major supplier of ...

View Elif Group of Companies (www.elif.com) location in Istanbul, Turkey , revenue, industry and description. Find related and similar companies as well as employees by title and much more.

Elif Group of Companies - Overview, News & Competitors | ZoomInfo.com

Overview · Portfolio · Work History · Services · Skills · Featured clients · Business managers · Agency member · Upwork activity

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Read writing from ElifTech on Medium. Business-savvy software engineers ready to work for you www.eliftech.com. Every day, ElifTech and thousands of other voices read, write, and share important stories on Medium.

ElifTech – Medium

Software development, mobile app development, web development, Empower Your Digital Transformation with ElifTech

ElifTech

Just as mobile apps and social media revolutionized the consumer experience more than a decade ago, now artificial intelligence (AI) is set to shake up enterprises. Over the years, businesses have come to rely heavily on technology to facilitate communications, enhance productivity, and drive innovations. Today, the integration of AI into business operations promises even greater potential. It's worth noting that numerous groundbreaking technologies of the past have traced a similar trajectory: initial recognition, excitement culminating in the hype, a gentle letdown when the hype confronts reality, and then a meteoric rise once the technology breaches a critical threshold and demonstrates its value. This trajectory mirrors the advancement of generative AI but at an unprecedented, breakneck speed. ChatGPT was officially unveiled to the public on November 30, 2022, primarily as a techno-demonstration. A mere two months post-launch, it already had an impressive user base of approximately 100 million active users, earning the title of the fastest burgeoning consumer application in recorded history. From then on, generative AI has sustained a rapid pace of progress, with the advent of multiple new tools and applications showcasing the enormous capacity of this technology to revolutionize how individuals conduct their lives and professional activities. Moreover, a recent survey conducted by Salesforce underscores the prevailing sentiment among IT leaders, with that generative AI is anticipated to play a significant role in their organizations in the future. This technological advancement enables organizations to derive greater value from their extensive data pools and streamline labor-intensive processes such as transcription of meeting notes and management of consumer inquiries. These prospects for enhanced efficiency have instigated a competitive rush among businesses to leverage AI. According to an analysis by McKinsey, generative AI is poised to add a value of $2.6 trillion to $4.4 trillion annually, primarily by enriching customer experiences, innovating research methodologies, and facilitating task automation. Furthermore, Salesforce anticipates generating over . 86% asserting $2 trillion in business revenue and creating approximately 11.6 million jobs from 2022 to 2028 Notably, AI adoption is not limited to just tech giants or innovators anymore. Businesses of all sizes and across industries are recognizing the potential of AI solutions to transform their operations. Whether it's improving supply chain management and forecasting, optimizing resource utilization, or delivering personalized customer experiences, AI is becoming a valuable asset across the business spectrum. Now decides next: The swift rise of generative AI The period of innovation that took off around 2007 made use of social media and app stores to help companies achieve scale in the consumer market, but this time is different. They were the engines of growth, brand visibility, and user acquisition, as entrepreneurs and innovators raced to tap into the ever-expanding digital marketplace. However, this time, the narrative has taken a turn. While social media networks and app stores continue to play a significant role in consumer engagement, the generative AI boom is redirecting the focus toward the engine rooms of enterprises, making people and processes radically more productive. Unlike the prior wave that saw AI-generated content as the front-rank innovation, the present technological tide is characterized by deep learning algorithms and AI systems that are increasingly sophisticated and accessible. AI is changing how products are designed, how customer data is analyzed, and how decisions are made. Enterprises are turning to AI to optimize supply chains, forecast market changes, automate administrative tasks, personalize customer service, and improve cybersecurity. This distinction is crucial: the present era is less about reaching the consumer directly and more about enhancing the fundamental capabilities of businesses to serve those consumers more effectively and efficiently. It's a shift from consumer-facing front-end innovations to backend process optimizations that can bring about more profound and lasting transformations across industries. Enthusiasm for generative AI solutions is still surging, and significant transformations are anticipated within the next three years. Yet, this excitement is not without its apprehensions, as also express a sense of uncertainty. 30% of IT leaders Some anticipate that generative AI will catalyze profound changes within their enterprises and respective sectors in the next three years—remarkably, almost a third are foreseeing significant transformations to either unfold presently (14%) or within a timeframe shorter than one year (17%). There is a trend where many enterprises are gearing up to escalate their applications of AI, pivoting towards a more substantial integration of generative technologies. This reflects the broader market dynamics, where firms globally are quickening their pace, advancing from experimental proof-of-concept stages to broader, more ambitious deployments. These deployments span diverse use cases and data types, with companies seeking to seize the swiftness and value that generative AI promises, all while judiciously navigating its potential risks and societal ramifications. Measuring business value and benefits of generative AI Companies all around continue to discover innovative, practical applications for the technology, far surpassing the realm of artificial chatbots. Businesses aren't just using generative AI for operational tasks. The technology is also being adopted in traditionally people-driven roles, such as sales and marketing, with resounding success. Current generative AI efforts remain more focused on efficiency, productivity, and cost reduction than on innovation and growth. A significant portion of organizations are currently harnessing generative AI for practical gains such as enhancing efficiency and productivity (56%) and lowering costs (35%). This trend aligns with historical precedents associated with tech adoption phases. In the early stages, organizations typically prioritize subtle enhancements to their existing processes and services, picking off the low-hanging fruit, while fortifying their understanding, proficiency, and assurance in the nascent technology. As their expertise evolves, they broaden or recalibrate their focus towards more innovative, strategic, and transformational advancements—putting the novel technology to work for driving growth, gaining a competitive edge, and unlocking new capabilities that were previously inconceivable. Leaders with higher levels of AI proficiency demonstrate earlier indications of ascending this curve, being keener on revealing new concepts and insights. Even so, these practical advantages continue to remain their primary focus. Unquestionably, productivity and efficiency can be metamorphic, especially when contemplating the significant scale that generative AI brings to the table. However, the most substantial benefits and strategic differences will potentially emanate from using the technology as a catalyst for innovation. On one hand, it can aid in devising new products, services, and functionalities that would have been unimaginable otherwise. On the other hand, it can foster new business paradigms and workflows throughout an organization, thereby redefining the way businesses function. As has been the case in the past, organizations are predicted to first focus their efforts on enhancing efficiency, augmenting productivity, saving costs, and pursuing other forms of gradual improvements. This approach is expected to aid the workforce in acclimating to the use of generative AI and demonstrating how this technology can simplify their professional roles. Moreover, initial successes will likely yield cost benefits and stimulate a momentum that can be redirected toward pursuing higher-value areas. This could involve more strategic and distinctive endeavors, like facilitating the creation of novel products, services, and business models. Not to mention, it paves the way for innovative work methods that were impractical before the advent of generative AI. Reflecting the focus on immediate gains from generative AI, are currently leaning heavily toward readily available solutions. They're tapping into: the majority of companies : These applications are aimed at enhancing everyday efficiency by automating routine tasks and processes. Productivity Tools with Generative AI Integration : These platforms are typically used across organizations to improve various business functions by leveraging AI's data processing and analysis power. Enterprise Systems with Generative AI Capabilities : Such applications are designed to be broadly applicable, aiding a wide range of industries and sectors with generalized tasks. Standard Generative AI Applications : Platforms like ChatGPT exemplify public LLMs, known for their versatility in language processing, capable of diverse applications like conversation, content generation, and more. Public Large Language Models (LLMs) like ChatGPT On the flip side, there's less enthusiasm for the more niche, customized generative AI tools, including: : These are specialized solutions intended for particular sectors, offering tools that align more closely with unique industry demands and vocabularies. Industry-Specific Software Applications : Organizations may opt for private LLMs to tailor language processing capabilities according to their proprietary needs or for enhanced data privacy. Private Large Language Models (32%) : It's a bit of DIY in the AI world, taking publicly available open-source LLMs and modifying them to fit their specific business requirements more closely. Customized Open-Source LLMs (25%) The prevalent reliance on generic, out-of-the-box solutions aligns with the present, emergent phase of generative AI integration, with a strong emphasis on streamlining and augmenting the productivity of conventional operations. Nevertheless, as the applications for generative AI branch out — becoming more distinct, specialized, and strategically imperative — it is anticipated that the strategies for development and the supporting tech infrastructures will evolve accordingly, embracing a more bespoke approach to deliver greater competitive advantage and value generation. What’s the change? Generative AI may not possess the ability to rapidly build a large user base like social media platforms or mobile apps, but it is bringing about a unique change—one that is transforming large organizations from within. It’s all about transforming how large organizations operate from the inside out, making every task more efficient and boosting overall productivity. Unlike consumer-centric technologies, generative AI doesn't construct an external user platform; instead, it builds an internal one, bolstering the backbone of organizations. This helps free up employees to engage with more challenging, valuable work. And it doesn’t stop there. AI-powered analytics can dig into the deep sea of data an organization produces, pulling out valuable insights and trends. The kind that can shape and guide strategic decisions, leading the business down a more profitable path. , reducing the workforce's mundane load and freeing up time for higher-value work. AI-powered analytics can sift through vast amounts of data to generate insights that inform strategic decision-making, consequently steering the company towards more profitable paths. It can revolutionize customer service by deploying chatbots for instant query resolution, elevate human resource functions with predictive hiring and talent analytics, and improve the supply chain with predictive logistics. AI models can automate routine tasks The point to emphasize here is that generative AI isn't about displacing human effort; it is about enhancing it. It's about 'augmentation' rather than 'automation.' It’s a tool that empowers the workforce to be more creative, strategic, and efficient, driving a significant upswing in productivity. The ultimate triumph of generative AI in the enterprise context is that it manifests the power to transform large organizations by enhancing the efficacy of their most valuable asset - people. It fosters a culture of collaborative intelligence where human creativity and decision-making are complemented by AI capabilities, harnessing the best attributes of both to give businesses a quantifiable competitive edge. As we move forward, generative AI's distinctive proposition—to make organizations fundamentally more efficient and productive—will be key. In a world increasingly driven by technological advancements, it is this potential to bolster human talent and streamline business processes that positions AI as a game-changing force in enterprise evolution. One of the most compelling facets of generative AI is its universal applicability. From small startups to multinational enterprises, businesses can deploy AI technologies to automate complex tasks, derive insights from large data sets, and create new ways of engaging customers. Unlike previous tech waves that often required substantial investment, making them the domain of large players, generative AI levels the playing field. Now, even small enterprises have the potential to disrupt established markets and challenge incumbents by leveraging AI-driven innovation. Furthermore, generative AI's versatility extends beyond mere operational efficiency. It's a catalyst for creating new products, services, and business models. With the ability to analyze trends and forecast demands with unprecedented accuracy, businesses can identify and capitalize on emerging market opportunities faster than ever before. Moreover, generative AI empowers companies to deliver highly personalized customer experiences, something that has become a significant differentiator in today’s competitive landscape. However, the journey toward AI integration is not without its challenges. Data privacy, ethical considerations, technical infrastructure, and skill gaps are some of the key issues enterprises must navigate to unlock the full potential of AI. As businesses push the boundaries of what's possible with AI, they also bear responsibility for ensuring that their innovations are ethical, transparent, and equitable. This includes addressing issues related to privacy, data security, employment, and the potential unintended consequences of AI systems. Business leaders must prepare their organizations for this transformation journey, fostering an AI-ready culture grounded in learning, adaptability, and ethical responsibility. Final Say Summing up, the generative AI boom is not just another chapter in the annals of technological advancement. It is a critical moment with the potential to fundamentally transform how businesses operate and compete. By embracing this revolution, companies can unlock new levels of efficiency, innovation, and customer engagement. But this requires not just adopting new technologies, but also adapting to the new realities they create—cultivating the right skills, embracing change, and navigating the ethical landscape with consideration. In doing so, businesses can harness the full power of generative AI, propelling themselves into a future where they’re not just participants in the digital revolution, but leaders shaping its course.

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Opinion piece: What we can learn about documentation and logging I have a long history of telling people I'm the dumbest person in this industry. This comes with the con that people think I'm dumb, but also an amazing pro. If I can read your documentation and use your tool, you did an amazing job because you got an idiot like me to use it. Extra points for a fast "aha!" moment. and are f*cking shit, I hate javascript, and can someone / something please address the dumpster fire we have going on holding the entire front end of the internet together. It's 2 AM, let's chat boys and girls. NPM yarn Welcome to Hacker f*cking noon, where we can write sh*t like this. you a picture.... Let me paint I need to upload some code to the cloud, what code isn't important. The README.md for step 1 is clear as day: Requirements yarn

Run ```make zip adapter=coinpaprika``` Simple, I need yarn, then I need to run that command. Now, I have worked a lot with python, and maybe I'm spoiled because works 99% of the time, but this can't be much worse right? I have a macOs, how do I install on this OS? Let me go to their . It seems so straightforward! This is great! I can run one of multiple commands, let me just try the easiest. make pip install documentation page brew install yarn And I get an error: curl: ( ) The requested URL returned error: Forbidden
> Failed to download https: 22 403 //yarnpkg.com/latest.tar.gz. Hmm, not sure what that means, but no worries. I can just google this, maybe the site is down? Maybe I have weird firewall rules? The triage list of possible issues is pretty long here, and I explore a number of them. After unsuccessfully triaging, I decide just to move onto the next command. I don't really need to become an expert on the ins and outs of this package to use it for it's intended purpose right? sudo port install yarn After trying this I get a number of other weird issues, follow similar triage paths. So let me try something else. Let me dig even deeper trying to figure out what I'm doing wrong. I google the error Check github for issues Try the command on my friends computer and ask them Spin up a Ubuntu VM in my Google cloud and try to install using the f*cking Ubuntu commands it f*cking supplied, and then start to google and triage those errors, till finally I come across this sh*t. You can install yarn with NPM, just run:

npm install yarn -g I suspect this won't work, but I of course try it both on my mac and my linux VM anyway, and then proceed to lose my f*cking sh*t. The INSTANT I saw npm I knew all hope was lost. Which brings me to my first point. 1. Clear, concise, logging is critical You are a coder, you work with computers. We get it, we are technical people, however the users trying to use your tools are human. When an issue comes up, a human is going to fix it. Not a robot. A human. And humans are emotional creatures. Every second your tool is being debugged by a developer, their hate for your stupid logo grows, and want for an alternative grows. It's a great way to drive away developers. So if you'd like your project that you've spent years building to be despised by the community and moved on from, then please, don't add logging. I know it's hard and a bit tedious, but every time you get an error and someone doesn't understand the issue about why the issue happened, you have a responsibility to upgrade your error and documentation so that anyone can use it seamlessly. Here are some tips. Here is a great example of what I think is sh*t: : [~/code/lottery-react -  (master)] $ npm run start patrick@Patricks-MacBook-Pro-2 > lottery-react@ . start /Users/patrick/code/lottery-react
> react-scripts start


There might be a problem the project dependency tree.
It likely a bug Create React App, but something you need fix locally.

The react-scripts provided by Create React App requires a dependency: : Don try install it manually: your manager does it automatically.
However, a different version babel-eslint was detected higher up the tree:

  /Users/patrick/code/node_modules/babel-eslint (version: . ) 

Manually installing incompatible versions known cause hard- -debug issues. you would prefer ignore this check, add SKIP_PREFLIGHT_CHECK= an .env your project.
That will permanently disable this message but you might encounter other issues. fix the dependency tree, try following the steps below the exact order: . Delete -lock.json ( .json!) / yarn.lock your project folder. . Delete node_modules your project folder. . Remove from dependencies / devDependencies the .json your project folder. . Run npm install yarn, depending the manager you . most cases, this should be enough fix the problem. this has helped, there are a few other things you can try: . you used npm, install yarn (http://yarnpkg.com/) repeat the above steps it instead.
     This may help because npm has known issues hoisting which may get resolved future versions. . Check /Users/patrick/code/node_modules/babel-eslint outside your project directory. example, you might have accidentally installed something your home folder. . Try running npm ls babel-eslint your project folder.
     This will tell you which other (apart from the expected react-scripts) installed babel-eslint. nothing helps, add SKIP_PREFLIGHT_CHECK= an .env your project.
That would permanently disable this preflight check you want proceed anyway.

P.S. We know this message long but please read the steps above :-) We hope you find them helpful!

npm ERR! code ELIFECYCLE
npm ERR! errno npm ERR! lottery-react@ . start: `react-scripts start`
npm ERR! status npm ERR! 
npm ERR! Failed at the lottery-react@ . start script.
npm ERR! This probably a problem npm. There likely additional logging output above.

npm ERR! A complete log this run can be found :
npm ERR!     /Users/patrick/.npm/_logs/ - - T04_38_46_190Z-debug.log 0.1 0 with is not in to package "babel-eslint" "10.0.3" 't to package of in 6.1 2 is to to If to true to file in To in 1 package not package and or in 2 in 3 "babel-eslint" and or in package file in 4 or on package use In to If not 5 If and with with package in 6 if is For in 7 in package If else true to file in in case to is 1 0.1 0 Exit 1 0.1 0 is not with is of in 2020 05 08 What the f*ck Usually, my terminal doesn't take up the whole screen, so I only see the bottom. I can only image a new developer's reaction seeing the screaming at you 50 times. Giving them flashbacks of father beating down the door in his drunken stupor at 2 AM, just for trying to get to actually print "helloWorld". npm ERR! helloWorld The GOOD thing about this (if you don't instantly go catatonic), is that if your anxiety meds calm you down from the epileptic induced error overload, if you scroll up, it does give you some good tips that DO usually solve the issue. Which is: You probably forgot to run npm install silly Which I have a different issue with, and seem 1000% times simpler... Am I wrong? Please let me know. A rant for another day.... pip install requirements.txt Anyway, the logging has a lot of good information in it, which is awesome, and it is clear, which I love. The part that is ass is the fact that it's the length of an 8th graders essay where the grading rubric was based solely on whether or not they hit 1,000 words. VERY The other issue is why the living hell are such a massive file? Am I just a python brat? And a java brat? And a go brat? Why is it that I don't have this massive folder on any other language. Ug, that's a rant for another day. node_modules 2. Documentation needs to reduce friction If you want people to use your tool quickly and efficiently, they need to have an " " moment quickly and efficiently. This is especially true for new developers, since ofter once someone finds a tool that works, . aha! they tend to stick to it Let's look at the documentation for pip and npm? Each home page has a "Getting started" or "Quickstart" page. Great! That's what I want! To quickstart! : Here is python/pip's In this first section I now know almost everything I need to know. The rest of the page is as concise and beautiful as this portion. If you even hit that link, you reach a page where the first line says: install pip pip is already installed if you are using Python 2 >=2.7.9 or Python 3 >=3.4 YES. THIS. EVERYTHING ABOUT THIS. ITS ALREADY THERE. I'm going to need it! Why would it NOT be installed??? What's the most important thing I need from pip? What is right at the top of the documentation? Brilliant right? It's installing packages. How to install packages. : Now we go to npm's You would think the most important thing is creating a new user account or paying for your account. Ya know, since they put those at the top. But it's not. It's not the most important thing. The most important thing is installing packages. 3. The ridiculous dependencies This is the one most people quote. Since javascript doesn't have a standard library like python, people are free to write there own and import anyone else's. This has the massive pro of being open-sourced as hell, but the massive con of no consensus at all, and sometimes for you to use one package someone wrote, means you need to install 2,000 other random files. Talk about "lightweight". Oops. This can mean that if one package is updated, broken, removed, fixed or something, your code may no longer work, and when you go to debug it you have to go 10 dependencies deep to figure out the actual issue. This is all over the world. exactly what happened in 2016 Not to mention that I just praised npm for being open-sourced as hell, except in this same instance they kicked someone's package to the curb to make room for a bigger companies. #openSourcedUnlessYoureNotABigCompany Photo by on Mohamed Nohassi Unsplash Summary Look, at the end of the day, I was eventually able to work out the kinks and get my project to work. And I know if I spent more time reading through everything I probably would be a lot better at these technologies. I'm not a javascript pro by any context, and I know that a response can be "Well then why do you say they suck if you're not even a pro??". First impressions are huge. And what I'm trying to say, is that the experience of working with these tools, especially early on, shouldn't be this frustrating. If you want developers to work with your tools, reducing the complexity and friction should be a top priority. It feels like npm has reached a point where they are saying: "Well, the web is built on javascript, and we are the dominant package manager, so they will have to come to us. F*ck them." (Not an actual quote) I think this will be a massive misstep for them, as we saw Microsoft go through nearly exactly the same journey. Becoming complacent, started building shit products, and then . becoming dominated by competitors who were sick of their shit I also don't want to say pip is perfect. Virtualenvs are the programming equivalent of "wtf" for beginners, but somehow I (being the dumbest human in the industry) was able to figure it out. And if you don't believe me. Google "npm is bad" and read the shitstorm of posts about how bad npm is. From being a , , , , . poorly managed company more information on the joke of package dependencies why we need to address the issue of npm the million devrants from this site hacknews and reddit filled with hate And now me too. Let me know if you think I'm just a shitty pissant coder, brilliant documentation analyst, or something else. I have more helpful content 99% of the time, like blockchain tutorials, python and machine learning, and fintech engineering. Follow me on , , , and ! Medium Twitter Youtube GitHub

Why NPM and Yarn f*cking suck

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Women Tech Fab For all those days I have been working to bring diversity into the tech domain, here was a hackathon that was happening exclusively for women and how could I not be a part of it?! For most hackathons in the past, I used to mentor and attach myself to teams from colleges and help them out during technical difficulties. This time around, I badly wanted to participate because I had everything they asked for: An Idea Team Of course the hackathon The idea Story In my previous company, I used to log my work, thought process, learning, and design decisions in a google document. As days passed by, the document started growing, and in the end, I had a 36-page document from which I could never infer my learning/thought process. One other issue was you can’t ensure all the employees log their work. On top of that, I used to set a reminder in Slack to remind my colleagues to make an entry. That’s when I wanted to turn it into a chatbot. iKeepLog A chatbot that sits in your organization’s messaging platform, that pings you at regular intervals to get your status update. You can log your status with #hashtags and over a period it will generate a learning and productivity curve. Though this was the base of my idea, you will see how our kick-ass team transformed it over for the hackathon. The Team My team was the most diverse set from the whole hackathon. We don’t belong to the same company. We all became friends by meeting at various tech community events in Chennai. — The Senior Software consultant from TarkaLabs or The DevOps specialist as I know him :D gladly accepted to be a part of my team. In fact I didn’t even ask him before applying. Naren — She is my go-to person when it comes to #womenInTech. Her new found love for React.js came in handy for a team which has no front-end skills. Krithika — Her new found passion to enter Software Development made the Founder of ThinkDiff S’kool reach out and become a part of my team. Bhuvana The Hackathon Application After applying with iKeepLog, I wanted to increase the chances of getting a spot in the hackathon. We started a Whatsapp group and began discussing other ideas. By the time I applied the second idea the organizing members had called to inform that both the ideas got selected. I tried hard to form a second team but had to drop it towards the end. Planning Trust me, if you are planning to use a Whatsapp group for hackathon discussions, don’t! Call them up, meet in a common place and brainstorm. By the time we realized, it was already the day before the hackathon! We listed out everything we exchanged over the calls and started connecting the major features to every new thought that popped up. By the end of the planning session we had a plan of execution for each member of the team. Plan To Action Day 1 As a woman who is struggling to bring diversity to tech communities, entering a room full of women who were equally pumped for a tech hackathon was a dream come true. We started the implementation after an energizing keynote and breakfast. The mentors started coming around, heard our ideas and gave us different dimensions to approach and pitch the idea. Vaishnavi from helped us crack the business aspects of the idea. Mad Street Den While I was struggling with Slack’s Documentation to bring the bot to life. Krithika started with the dashboard, Naren and Bhuvana immersed themselves into the backend implementation. At the end of Day 1, we had a slackbot which logs to a database and a backend API which generated a tag cloud from the logs. Naren worked late at night and got one version up in the server. Day 2 The 2nd day started with bringing more personality to the bot and a ping API for the bot to ping the user and lots of UI. While Krithika and Naren worked on the placement of UI components. I gave inputs for slides to answer the What ?, Why?, Who? And How? to Bhuvana. Once Bhuvana got the slides up, we ran it past Vaishnavi, and she gave a green signal and suggested a couple of more points. Final Presentation This was the final part of any hackathon where it all came to an end. The pressure kicks in no matter how much you have prepared. When a lot pick pushed the Team No 1 to 13th and when you see lots of great ideas presented before you, no one can judge you for getting so nervous. The slides went up, and my hands went cold with a deep breath exiting my lungs, I regained my confidence to present the what, why, how and who of iKeepLog. Cherry on the cake I sensed the feeling of accomplishment among my team. I can assure you they were delighted that it all came together finally. We celebrated it with samosas and kachoris. When we settled back in for the results announcement, the crowd grew impatient as we neared the moment. When they announced that we were the runners-up, I was immediately on cloud nine! No words in this world can explain my emotion at that instant, so here is a video of the same. Behind the scenes How we produce code How we produce code The Error that kept us up > material-dashboard-react@1.2.0 build /home/bhavani/iKeepLog/ikeeplog/web> react-scripts buildmodule.js:549throw err;^ Error: Cannot find module ‘./lib/parse’at Function.Module._resolveFilename (module.js:547:15)at Function.Module._load (module.js:474:25)at Module.require (module.js:596:17)at require (internal/module.js:11:18)at Object.<anonymous> (/home/bhavani/iKeepLog/ikeeplog/web/node_modules/react-dev-utils/node_modules/cross-spawn/index.js:4:13)at Module._compile (module.js:652:30)at Object.Module._extensions..js (module.js:663:10)at Module.load (module.js:565:32)at tryModuleLoad (module.js:505:12)at Function.Module._load (module.js:497:3) npm ERR! code ELIFECYCLEnpm ERR! errno 1npm ERR! material-dashboard-react@1.2.0 build: `react-scripts build`npm ERR! Exit status 1npm ERR!npm ERR! Failed at the material-dashboard-react@1.2.0 build script.npm ERR! This is probably not a problem with npm. There is likely additional logging output above.npm ERR! A complete log of this run can be found in:npm ERR! /home/bhavani/.npm/_logs/2018–06–23T16_41_42_805Z-debug.log` When you are sad but, your bot is not going to give up on you. What’s next on the list for iKeeplog iKeeplog is not just a hackathon thing. We are going to work on it more to convert the prototype to an MVP.

WTF did we do at the WTF Hackathon?

T o produce great results, the agile approach to product development, deployment, and adoption demands a strong relationship between development and operations teams. Peer Mountain’s Blockchain DevOps Engineer, Florian Lagouche, ensures that communication and collaboration between these groups remains clear and effective. At the age of 25, Florian already has a wealth of experience in the relatively new field of DevOps. An enthusiastic technophile, he began his studies at Epitech Graduate School of Digital Innovation in Nancy, France, in 2010. Three years later, Florian did a year of study at Beijing Jiaotong University, then completed his education at Epitech Paris. Florian’s passion for tech kept him active outside the classrooms and computer labs. He did several internships before landing his first DevOps job at Boursorama, a subsidiary of global financial giant Société Générale. Florian’s two years at the French online bank proved to be an invaluable learning experience. During that time he upgraded Boursorama’s delivery system so that his team could push code on dozens of servers in just a few seconds, and roll back to a previous version immediately if necessary. In 2016, blockchain and cryptocurrencies captured Florian’s interest; he began working for Bitcoin analytics tool provider Scorechain in October that year. Florian and his team helped other companies, mostly financial institutions, learn about, and benefit from, blockchain tech. He also automated nearly every part of the Scorechain infrastructure, enabling developers to simply push their code to the git repository to automatically get a live version of it, after which they can push to production with one click. KYC3 got in touch with Florian in late 2017. They offered him the opportunity to apply his DevOps skills and experience to their new Peer Mountain project. Florian now manages the blockchain startup’s development cluster, as well as the KYC3 production clusters. To further help Peer Mountain deliver its decentralized trust, commerce, and compliance ecosystem, Florian also manages the blockchain startup’s infrastructure and automates product delivery processes. Florian stays active both physically and mentally in his spare time. He’s an avid sportsman who enjoys running, swimming, and skiing. While he’s aware of smart home tools like Google Home and Amazon Alexa, Florian dedicates time to automating household appliances and electronics, such as lights and speakers. “I don’t trust smart home assistants from big companies,” he says, “I like understanding how these things work, so I do it myself.” To speak with Florian and learn more about , join our lively ! Peer Mountain Telegram group

This is Peer Mountain: Meet Florian Lagouche

I heard the parts about from a lot of friends who is either working game or startup, spending about half of a day on doing the right configuration and understanding the right development tool. I would strongly recommend it to every React developers and teams, for the reason below: Storybook Storybook runs outside of your app, this allows you to develop UI components in isolation. It can improve component reuse, testability, and development speed. Quickly developing without having to worry about application-specific dependencies. ( ) by Storybook 1- Install $ npm i -g @storybook/cli$ cd my-react-app$ getstorybook 2- Make the right Config 5 config files is involved to the , they are all generated by CLI. The one I spent a bit more time is , as css-module is used in the target. git commit getstorybook [webpack.config.js](https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6#diff-6da49b24efd584154cfb4ec759745192 ".storybook/webpack.config.js") [.storybook/config.js](https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6#diff-6ab7cd89286451cc2620c7509b7d23b8 ".storybook/config.js") [.storybook/webpack.config.js](https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6#diff-6da49b24efd584154cfb4ec759745192 ".storybook/webpack.config.js") ./[package.json](https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6#diff-b9cfc7f2cdf78a7f4b91a753d10865a2 "package.json") [./stories/index.js](https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6#diff-fc0beb5060745097c94da659f02f2884 "stories/index.js") Target components Target component have to be a simple function that returns . HTML Elements / React.Component const Hello = ({ onClick, message }) => {return (<div><h1 className={classNames(style['title'])}>{ message }</h1><button onClick={onClick}>Click</button></div>)} Hello.propTypes = {onClick: PropTypes.func.isRequired,message: PropTypes.string.isRequired} export default Hello Run $ npm i --save-dev @storybook/react$ npm run storybook open browser localhost:6006 Troubleshooting The part was spent the most time is troubleshooting this issue:  — sh: start-storybook: command not found After installing storybook globally and generated needed config by , the error is showed: getstorybook sh: start-storybook: command not foundnpm ERR! file shnpm ERR! code ELIFECYCLEnpm ERR! errno ENOENTnpm ERR! syscall spawnnpm ERR! dashboard@0.0.0 storybook: start-storybook -p 6006 solution: $ npm i --save-dev @storybook/react$ npm run storybook Reference https://github.com/storybooks/storybook/blob/master/README.md https://github.com/wahengchang/react-redux-boilerplate/commit/aa2f4d6fd0ce55525bf471904eb82683a3d5d9a6

ELIFTECH

eliftech.com

11-50 employees

Since 2015

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ELIFTECH

EVERGREEN INDEX #4473

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ELIFTECH

eliftech.com

11-50 employees

Since 2015

COMPANY RANKING

ELIFTECH

EVERGREEN INDEX #4473

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