The modern data stack has gained a lot of traction over the last 12 months but takes companies 6 months+ to set up from scratch

Hey Hackernoon Readers, I’m , one of the managing partners at blockchain venture fund . -- First of all, a huge thank you to David, and entire Hackernoon community and staff for awarding me : Christian Kameir Sustany Capital five writing awards in 2021 Contributor of the Year - Money Contributor of the Year - VC NFT Wizard of 2021 Contributor of the Year - Art Contributor of the Year - Internet As someone who has focused on the decentralization of the internet since 2008, I think that the most exciting technology of the present is Web 3.0 because we can return agency to the users of the technology again, rather than allowing large companies to social-engineer users to cater to corporate objectives. Learn more about my thoughts and opinions on Web 3.0 and my journey in the tech industry via the interview below. 1. What do you do and why do you do it? As managing partners at Sustany Capital, we focus on operating a thesis-driven venture capital firm investing in Web 3.0, decentralized finance, and legal technologies. I have been a tech entrepreneur since the internet dial-up days and led the merger of two of the earliest internet service providers in Europe. In 2000 I moved to California to start a technology venture fund. I  studied classical literature and graduated from Muenster's School of Law. I am a board member at , co-chair of the Banking and Financial Services Interest Group at the , and lecture a class at . I write and speak on topics ranging from high-tech investing to decentralized finance, identity, and blockchain. Our current book project - working title ' ' - will be published in Q2/2022. Open Travel Decentralized Identity Foundation Harvard Streaming Money 2. Tell us more about the things you write about! I have been writing on ideas to “fix the web” since 2008. A core objective to me is to fix information distribution on the world wide web to do the most good. As such it is essential to foster solutions that contribute to creating consensus, and reverse the current paradigms that seek engagement for divisive content. Internet users should not be treated as NPCs - gamer-speak for non-player characters - but improve their own experiences daily by network technology that serves the interest of the individual. To me, advertising is not a suitable business model on top of a shared resource (commons). 3. How did you end up on your current career path? I started in software development in 1985, and I am as fascinated with the opportunities of network technology now, as I was back then. Realizing that I would never be a great coder, but understanding software principles well enough to explain them to others, I decided to join a startup as their general counsel. At the time - in 1997 - we were selling dial-up internet services, and we had to explain why this technology was relevant and interesting. The same is still true for the upcoming fundamental changes to the internet (Web 3.0), today. 4. What tech are you most excited or about right now and why? Returning control over bytes back to users: regardless if this refers to money or any other digitally expressed value or thought. Blockchain-based solutions are a central part of that, and many other cryptographic primitives that remove friction from our daily lives, and allow individuals around the world to engage in peer-to-peer interactions. Why this may sound corny: these are true ! freedom technologies 5. What tech are you most worried about right now and why? Blockchain-based solutions can both enable self-sovereignty or be ultimate surveillance tools for entities and governments which value individual freedoms less than the control of their subjects (see my article on ). The Folly of Digital Fiat 6. If we gave you 10 million dollars to invest in something today, what would you invest in and why? Disruptive finance solutions that replace the middleman, and Web 3.0 primitives that make centralized institutions unnecessary (read more ). here 7. What are you currently learning? We are currently writing a book on . As strict observers of the scientific methods, we started out aggregating the current financial landscape three years ago. We are learning something new about the evolving financial landscape daily. However, we are interested in a wide spectrum at the intersection of finance, technology, law, and socio-economic issues. Streaming Money 8. What’s the best advice you’ve ever given someone? Never choose unhappiness over uncertainty! 9. What’s the best advice you’ve ever received? A. The meaning of your communication is the response you get. B. There is no failure, only feedback. C. The map is not the territory. About HackerNoon’s 2021 Noonie Awards The annual Noonie Awards celebrate the best and brightest of the tech industry, bringing together all who are making the Internet and the world of tech what it is today. Please be sure to , nominate, and vote for the people and companies who you think are making the biggest impact on the tech industry today. check out our award categories

"There is no Failure, only Feedback"  with 5x Noonies Winner Christian Kameir

Negative sentiment around Trump lifted slightly when he was diagnosed — and dropped when he returned to the White House. During the September 29th, 2020 Presidential debate held in Cleveland, OH, Donald Trump said to Joe Biden: “They give you good press, they give me bad press because that’s the way it is, unfortunately” — Donald Trump Until now, this assertion by Trump has been hard-to-impossible to prove or disprove. But a new media study released by Import.io has shown that the POTUS is correct in this assertion — to a degree. The analyzed 49,682 news stories from the web sites of 1,571 U.S.-based, English-language news organizations. This huge data set represents coverage through September 1st through October 7th that mentions Trump, Biden, or Trump and Biden. The data was measured in terms of both volume and tone. study by Import.io Here’s what they found: Trump & Biden Coverage — Not Overwhelmingly Positive Neither candidate has predominately positive coverage, but Trump’s is certainly more negative in tone. The timeline shows Biden in Blue and Trump in Red. Certain events like Trump praising SCOTUS Ruth Bader Ginsburg and Trump’s own diagnosis with COVID-19 did create a temporary lift in sentiment toward Trump — but it was short-lived. Media sentiment timeline — Trump vs. Biden TL;DR analysis — Neither candidate has greatly positive coverage but Trump’s coverage is more negative and swings more wildly around key events. Trump gets far more coverage… Since September, there have been 5x the number of stories about only Trump vs. stories about only Biden. If you factor in stories that mentioned both candidates, Trump still gets x2 the amount of coverage. Volume of coverage — Trump vs. Biden Trump may not evince great sentiment from media, but he is great at being talked about. TL;DR analysis — More facts to consider: The media sentiment towards both candidates took a negative turn immediately following the first Presidential debate.When Trump was diagnosed with COVID-19 on Oct. 2, it was the biggest day in terms of media coverage of the 2020 US Presidential election, followed by September 30th, the day after the first Presidential debate.After the announcement that Trump contracted COVID-19, coverage spiked for Trump (but not for Trump/Biden or Biden alone) and Trump’s sentiment score reached an all-time high.The elevated media sentiment score for Trump continued in the days during his hospitalization but then dropped again upon his return to the White House Conclusion As pundits on both sides marvel at the mass appeal of this highly polarizing President, these figures beg the question — is it true that It remains to be seen, and the remaining weeks running up to the campaign are likely to be full of surprises. all news is good news? Import.io extracts and analyzes web data at scale for global companies. To learn more about the methodology of the study, . check out the company’s blog entry *Article uses original composite image made using campaign web site imagery.

50k+ News Story Study Finds Trump Gets 5x the Coverage, but Not Much Love

Photo by on Sanjeevan SatheesKumar Unsplash Recently my team have started working on the first big React Native app. Quite soon I had to implement a page with filters list: Problem In the initial version of the page, a single click on checkbox element initiated a noticeable delay. takes most of FlatList[update] 250ms There are 75 elements in the list and only 11 visible at a single moment of time. So I was expecting (which has a virtualization feature out of the box) to rerender only a single changed element (in the worst case — only visible elements). But it . FlatList rerenders all items To show a selectable list of categories I retrieve from redux state and create a new array that contains Category data and flag : Original Approach Categories extendedCategories isShown Solution After the small change, render time went down to 56ms. To , I had to stop mutating data source for FlatList and rerender items ONLY if they have changed. cut down render time 5x times Instead of creating a new data source object after each rerender, I use existing array to map over. And calculate on the level. Now the data source is always the same object and prop will get new value only when checkbox changes it’s value. categories isShown FlatList isShown 2. Use for PureComponent renderItem is similar to . The difference between them is that doesn’t implement , but implements it with a shallow prop and state comparison. ’s only shallowly compares the objects. If these contain complex data structures, it may produce false-negatives for deeper differences. PureComponent Component Component shouldComponentUpdate() PureComponent PureComponent shouldComponentUpdate() Redux State — an array of all meta info about categories Categories — an array with only selected categories {id, name} SelectedCategories After clicking on the category, it is added to array, and object is always the same, without mutations. If the user clicks on an already selected category, it is being removed from the array. SelectedCategories Categories SelectedCategories Profiling From my experience, unlike React, extra rerender in React Native affects user experience much worse. The fastest way to find extra renders is old in render function. After you found an issue, use Chrome Profiler tab in developer tools to dig into it. Or (coming in 16.5). console.log new React Profiler Want to play with the code? Check out the GitHub repo! _Contribute to ProductCrafters/rn_perf development by creating an account on GitHub._github.com ProductCrafters/rn_perf P.S. If you enjoyed this article and want more like these, please clap and share with friends that may need it. 🚀 . We help US startup founders to bring their ideas to life. If you need some help, send a message ✉️ My team uses JS and React to build production apps over 3 years oleg@productcrafters.io

How to improve React Native list performance 5x times

Here’s a quick(ish) tip on how to use non-recurring revenue services (training, consulting, etc.) to 2.5x (or more) the recurring revenue you get from a customer. This tip requires that you have a baseline understanding of Customer Success . Let’s say you have a customer at $10k/ARR and they’re humming along just fine. If you leave them to grow on their own, it might take 18 months before they’re ready for the next pricing tier or add-on that would take them to $25k/ARR. By knowing where the customer is on their journey, you can intelligently offer services that can short-circuit their path to the next Success Milestone that has that logical expansion opportunity attached to it, and achieve account expansion much faster than if you left them to grow organically. Let’s say they hit a at 6 months in (remember, each customer will likely hit that milestone on their own cadence), and you know that a training program would not only help their current active users get more value from your product but could increase the number of users in their company, so you offer that up for a fee, but maybe only to break even. Success Milestone And that training program would get them to that point in 3 months, meaning they’re ready to move up to the next pricing tier 9 months earlier than they would organically. In businesses with professional investors and a board of directors, a large percentage of non-recurring revenue is often frowned upon since it’s not predictable and valued lower by said investors or potential acquirers. HOLD UP! SaaS So generally in these types of companies you want the “attachment rate” of non-RR to RR to be low (whatever that means to your investors, board, etc.). If that’s you, don’t immediately dismiss what I’m saying here… in fact, keep reading. BTW, in bootstrapped or other businesses, revenue is revenue so don’t worry about attachment rates (until you go to sell, I suppose). So let’s say you have a training program that you can offer a customer to short-circuit their success, but you have to charge $2.5k just to break even on it. If the customer is paying $10k, that’s a 25% attachment rate, which is probably higher than most investors/boards want to see. BUT… after the training, the most logical next step for the customer is to buy additional seats, add-ons, etc. and they move to $25k/ARR, now that attachment rate is only 10%… now you’re cookin’ with evil gas. The moral of this story is… know where your customers are on their journey toward their Desired Outcome, proactively offer them things to help them grow, and when they take that AND grow, offer them the thing they’ve grown into. Oh, and since they expanded 9 months earlier than they would have organically, where might they be in the next 9 months? You might be able to 5x+ an account value in that first 18 months. Hmm…. ….. Lincoln Murphy is a world-renowned Architect, Consultant, Author, and Keynote Speaker. As founder of — and previously leader of Customer Success Evangelism at Gainsight — he’s used Customer Success to drive growth across the entire customer lifecycle for more than 400 SaaS and enterprise software companies over the last decade. Growth Sixteen Ventures Follow Lincoln on Twitter

How to Quickly 2.5x Your Recurring Revenue

Hello JavaScript Enthusiasts! Welcome to a new edition of "This Week in JavaScript"! This Week in JavaScript Today, we're covering Microsoft's game-changing TypeScript speed boost, Google's CPU-friendly AI model, and HTML's exciting new declarative attributes, plus exciting new tools you won't want to miss! 10X Faster TypeScript 10X Faster TypeScript Microsoft is porting the entire TypeScript compiler to Go, and the results are mind-blowing! Let's break down what this means: Microsoft is porting the entire TypeScript compiler Microsoft is porting the entire TypeScript compiler Why This Matters: Why This Matters: 10X Speed Boost: Initial benchmarks show 10x improvement across the board, with some codebases seeing up to 13.5x faster compile times!
Developer Experience: Lightning-fast IDE experiences and near-instant error checking are coming your way
Timeline: Command-line typechecking targeted for mid-2025, with full language service support by year-end 10X Speed Boost: Initial benchmarks show 10x improvement across the board, with some codebases seeing up to 13.5x faster compile times! 10X Speed Boost: Developer Experience: Lightning-fast IDE experiences and near-instant error checking are coming your way Developer Experience: Timeline: Command-line typechecking targeted for mid-2025, with full language service support by year-end Timeline: This transformation will be especially valuable for developers working with large TypeScript projects! HTML Gets Declarative with New Attributes HTML Gets Declarative with New Attributes The latest Chrome (and preview versions of Firefox and Safari) now support two new HTML attributes that reduce the need for JavaScript: support two new HTML attributes support two new HTML attributes What's New: What's New: command and commandfor: Add declarative actions to HTML buttons without directly writing JavaScript
Simplified Code: Open a popover menu with just <button commandfor="my-menu" command="show-popover">Open Menu</button>
Accessibility Included: These attributes automatically handle accessibility concerns like aria-expanded command and commandfor: Add declarative actions to HTML buttons without directly writing JavaScript command and commandfor: Simplified Code: Open a popover menu with just <button commandfor="my-menu" command="show-popover">Open Menu</button> Simplified Code: Accessibility Included: These attributes automatically handle accessibility concerns like aria-expanded Accessibility Included: Less code, more functionality – that's always a win for developers! Gemma 3: Google's CPU-Friendly AI Model Gemma 3: Google's CPU-Friendly AI Model Google just launched "the most capable model you can run on a single CPU or TPU," opening new doors for JavaScript developers: the most capable model the most capable model Key Features: Key Features: Size Options: Available in various sizes (1B, 4B, 12B, and 27B parameters)
Multilingual: Supports an impressive 140 languages
Context Power: Comes with a massive 128K token context window
Resource Efficiency: Implement powerful AI capabilities without massive computational resources Size Options: Available in various sizes (1B, 4B, 12B, and 27B parameters) Size Options: Multilingual: Supports an impressive 140 languages Multilingual: Context Power: Comes with a massive 128K token context window Context Power: Resource Efficiency: Implement powerful AI capabilities without massive computational resources Resource Efficiency: This is a game-changer for JavaScript developers looking to add AI capabilities to their applications! Tools & Releases You Should Know About Tools & Releases You Should Know About Let's speed-run through some of the other big tool updates this week! Nuxt 3.16: Performance improvements and new features that make Vue development even smoother. The update introduces enhanced HMR capabilities and smart bundling optimizations that can cut loading times by up to 35% for complex applications.
Bun 1.2.5: Continues to impress with blazing speed and expanded capabilities – if you haven't tried it yet, now's the time! This release adds enhanced WebSocket support and improves npm compatibility, making it even easier to migrate existing Node.js projects.
Melange 5: Better ReScript and OCaml integration for JavaScript developers seeking more type safety. The new version brings seamless interoperability with TypeScript definition files and introduces a powerful pattern-matching compiler that generates highly optimized JavaScript.
Transformers.js 3.4: Making AI model integration easier than ever for web applications. This update adds support for streaming responses and introduces memory-efficient model loading that can reduce RAM usage by up to 60% when running large language models.
Refractor 5.0: Robust virtual syntax highlighting using Prism – perfect for code editors or documentation sites. The latest version delivers performance improvements that handle files up to 10MB without UI freezing and adds support for 15 new programming languages.
PGlite: Run Postgres directly in WebAssembly – full database capabilities right in your browser with no server required! This groundbreaking tool supports most SQL operations including complex joins and transactions, while maintaining data persistence through IndexedDB with automatic sync capabilities. Nuxt 3.16: Performance improvements and new features that make Vue development even smoother. The update introduces enhanced HMR capabilities and smart bundling optimizations that can cut loading times by up to 35% for complex applications. Nuxt 3.16 Nuxt 3.16 Bun 1.2.5: Continues to impress with blazing speed and expanded capabilities – if you haven't tried it yet, now's the time! This release adds enhanced WebSocket support and improves npm compatibility, making it even easier to migrate existing Node.js projects. Bun 1.2.5 Bun 1.2.5 Melange 5: Better ReScript and OCaml integration for JavaScript developers seeking more type safety. The new version brings seamless interoperability with TypeScript definition files and introduces a powerful pattern-matching compiler that generates highly optimized JavaScript. Melange 5 Melange 5 Transformers.js 3.4: Making AI model integration easier than ever for web applications. This update adds support for streaming responses and introduces memory-efficient model loading that can reduce RAM usage by up to 60% when running large language models. Transformers.js 3.4 Transformers.js 3.4 Refractor 5.0: Robust virtual syntax highlighting using Prism – perfect for code editors or documentation sites. The latest version delivers performance improvements that handle files up to 10MB without UI freezing and adds support for 15 new programming languages. Refractor 5.0 Refractor 5.0 PGlite: Run Postgres directly in WebAssembly – full database capabilities right in your browser with no server required! This groundbreaking tool supports most SQL operations including complex joins and transactions, while maintaining data persistence through IndexedDB with automatic sync capabilities. PGlite PGlite And that's it for the twenty-sixth issue of "This Week in JavaScript." This Week in JavaScript. Feel free to share this article with a fellow developer, and make sure you're following us for more weekly updates! Until next time, happy coding!

Microsoft Promises 10x Speed Boost to TypeScript Following Port 

“Insanity is doing the same thing over and over again, but expecting different results” - Source unknown “Insanity is doing the same thing over and over again, but expecting different results” - Source unknown “Insanity is doing the same thing over and over again, but expecting different results” - Source unknown “Insanity is doing the same thing over and over again, but expecting different results” - Source unknown As you can see in the quote above, humans have this tendency to retry things even when results are not going to change. This was manifested in systems designs as well where we pushed these biases when designing systems. If you look closely there are two broad categories of failures: Cases where retry makes sense


Where retries don’t make sense Cases where retry makes sense Cases where retry makes sense Where retries don’t make sense Where retries don’t make sense In the first category, transient failures like network glitches or intermittent service overloads are examples for which retrying makes sense. For the second, where the failure originates from something like the request itself is malformed, requests are getting throttled (429s), or service is load-shedding (5xx), it doesn’t make much sense to retry. While both of these categories need special attention and appropriate handling, in this article, we will primarily focus on category 1, where it makes sense to retry. The Case for Retries In the modern world, a typical customer-facing service is made up of various microservices. A customer query to a server goes through a complex call graph and typically deals with many services. On a happy day, a single customer query meets no error (or independent failure) to give an illusion of a successful call event. various microservices For example, a service that is dependent on 5 services with 99.99% availability, can only achieve a max of 99.95% of availability (reference doc) for its callers. The key point here is that even though each individual dependency has an excellent availability of 99.99%, the cumulative effect of depending on 5 such services results in a lower overall availability for the main service. This is because the probability of all 5 dependencies succeeding on a single request is the product of their individual probabilities. reference doc Overall Availability =1 - (1 - Individual Availability) ^ (# of Dependencies) Overall Availability =1 - (1 - Individual Availability) ^ (# of Dependencies) Now, by using the same formula, we can see that to maintain a 99.99% availability at the main service without any retries, all the dependencies need to have an availability higher than 99.998%. So, this begs a question: how do you achieve 99.99% availability at the main service? The answer is we need retries! Retries Sweet Spot Retries Sweet Spot We discussed above that the maximum availability that you can achieve without retries is 99.95% with those 5 dependencies. Now, if we expand our above formula and try to model the overall availability to 99.99% of the main service, it will include retries as a factor in considering it. So, the formula becomes: Overall Availability =1 - (1 - Individual Availability) ^ (# of Dependencies + # of Retries) Overall Availability =1 - (1 - Individual Availability) ^ (# of Dependencies + # of Retries) If you plug these values, it gives you 99.99% = 1 - (1 - 0.9999) ^ (5 + Number of Retries). This gives you # of retries = 2, which means that by adding two retries at the main service, you will be able to achieve 99.99% availability. This demonstrates how retries can be an effective strategy to overcome the effect of cumulative availability reduction when relying on multiple dependencies and help achieve the desired overall service-level objectives. This is great and obvious! So why this article!? Retry Storm and Call Escalation Retry Storm and Call Escalation While these retries help, they also bring trouble with them. The main problem with retries is when one of the services you depend on is in trouble or having a bad day. Now when you retry when it's already down, it is like you are kicking it where it hurts! —  potentially delaying the service’s recovery. kicking it where it hurts kicking it where it hurts Now think of a scenario where this call graph is multi-level deep; for example, the main service depends on 5 sub-services which in turn depend on another 5 services. Now when there is a failure, you retry at the top, and this will lead to 5 * 5 = 25 retries. What if those are further dependent on 5 services? So for one retry at the top, you may end up with 5 * 5 * 5 retries, and so on. While retries don’t help with faster recovery, they can take down the service that was operating partially with this extra generated load. Now, when those fail, they further increase the failure leading to more failures and this retry storm starts and creates long-lasting outages. At the lowest level, the call volume reaches 2 ^ N, which is catastrophic and would have recovered much faster had there been no retries at all. This brings us to the meat of the article where we say we like retries, but they are also dangerous if not done right. So, how can we do it right? Strategies for Limiting Retries Strategies for Limiting Retries To benefit from retries while keeping the retry storms and cascading failures from happening, we need a way to stop the excessive retries. As highlighted above, even a single retry at the top can cause too much damage when the call graph is deep (2 ^ N). We need to limit retries in aggregate. These are some of the practical tips on how this can be done: Bounded Retries Bounded Retries The idea with the bounded retries is that you have an upper bound in how many retries you can do. The upper bound can be decided based on the time; for example, every minute you can make 10 retries or it’s based on the success rate for every 1000 success calls, you give service a single retry credit and you keep getting until you reach the fixed upper bound. Circuit Breaking Circuit Breaking The philosophy of the circuit-breaking technique is to don’t hammer whats already down. With the circuit breaker pattern, what you do is when you meet an error, you close the connection, stop making calls to the server, and give it breathing room. To check for the recovery, you have a thread that makes a single invoke to the service on a periodic basis to check if it has recovered. Once it has recovered, you gradually start the traffic and go back to normal operation mode. This gives the receiving service the much-needed time to recover. This topic is covered in much detail in Martin Fowler’s article. circuit-breaking technique Martin Fowler’s article Retry Strategies Retry Strategies There are techniques in TCP congestion control like AIMD (Additive Increase and Multiplicative decrease) that can be employed. AIMD basically says that you slowly increase the traffic to a service (think of it like connection + 1), but you immediately reduce the traffic when faced with an error (think of it like active Connection / 2). You keep doing that till you equilibrium. Exponential backoff is another technique where you back off for a period of time upon meeting an error and subsequently increase the time you back off up to some maximum time. The subsequent increase is generally like 1, 2, 4, 8.. 2^retryCount, but could also be Fibonacci-based like 1,2,3,5,8…. There is another gotcha while retrying, which is to keep the jitter in mind. Here is a great article from Marc Brooker who goes into more depth about exponential backoff and retries. Exponential backoff Here is a great article from Marc Brooker While these techniques talk about client-side protection, we could also employ some guardrails on the server side. Some of the things that we can consider are: Explicit backpressure contract: When under load, reject caller request and pass on the metadata that you are failing because of overload and ask it to pass to its upstream and so on.
Avoid wastage work: In the case where you expect service to be under load, avoid doing wastage work. You can check whose caller has timed out and don’t need an answer to drop the work altogether.
Load shedding: When under stress, load shed aggressively. Investigate in mechanism where you can identify duplicate requests and discard one of them. Use signals like CPU, memory, etc. to compliment the load-shedding decision-making. Explicit backpressure contract: When under load, reject caller request and pass on the metadata that you are failing because of overload and ask it to pass to its upstream and so on. Explicit backpressure contract: Avoid wastage work: In the case where you expect service to be under load, avoid doing wastage work. You can check whose caller has timed out and don’t need an answer to drop the work altogether. Avoid wastage work: Load shedding: When under stress, load shed aggressively. Investigate in mechanism where you can identify duplicate requests and discard one of them. Use signals like CPU, memory, etc. to compliment the load-shedding decision-making. Load shedding: Conclusion Conclusion In distributed systems, transient failures in remote interactions are unavoidable. To build higher availability systems, we rely on retries. Retries can lead to big outages because of call escalations. Clients can adopt various approaches to avoid overloading the system in case of failures. Services should also employ techniques to protect themselves in case a client goes rogue. distributed systems Disclaimer Disclaimer The guidance provided here offers principles and practices that could broadly improve the reliability of services in many conditions. However, I would advise that you do not view this as a one-size-fits-all mandate. Instead, I suggest that you and your team evaluate these recommendations through the lens of your specific needs and circumstances.

How ‘Helpful’ Retries Can Wreck Your System—and How to Stop It

Big Tech Loves These 45 System Design Questions—Do You Have the Answers?

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