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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted this🎉 We’ve just surpassed 30,000 stars on GitHub! ⭐ We’re incredibly grateful to everyone who helped us get here. Launched in June 2022, Dragonfly reached 10,000 stars in 75 days and has since grown into a global community using it in production, contributing code, and shaping what comes next. Every star is a vote of confidence, and we’re grateful for each one. Looking ahead to 2026, we’re sharpening our focus on what Dragonfly already does best: powering real-time, large-scale, intelligent workloads, especially caching and revenue-critical ML systems where latency predictability, scale, and simplicity are essential. Thank you for being part of the journey and for helping push Dragonfly forward. Join the momentum: https://hubs.ly/Q043RB820
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisBuilding with LlamaIndex? Get one backend data store for chat, docs, vectors, and metadata. 🧠 Dragonfly is a #Redis-compatible powerhouse for AI apps, delivering much higher throughput and simpler system architecture. Read our first blog post of 2026: https://hubs.la/Q03ZJ3Gm0 #AgenticAI #DataInfraDragonfly as a Multi-Purpose Data Store for AI ApplicationsDragonfly as a Multi-Purpose Data Store for AI Applications
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisA short customer story from the last few weeks 👇 A fast-growing company was running a ~200GB feature store on AWS. Growth rate: ~20% every quarter. On AWS, a single node couldn’t handle the throughput, so the setup required read replicas. More nodes, more complexity, more cost and a scaling path that only gets harder over time. Three weeks ago, one of their engineers found Dragonfly and booked a call. On that call I told them something that sounded almost too simple: "You probably won’t need read replicas. A single Dragonfly node should handle the full load." They just finished their POC. Result: - One Dragonfly node handles all the traffic - No read replicas - ~75% infrastructure cost savings One engineer. One day of work. And suddenly the scaling story becomes trivial, predictable, and cost-efficient. This is why we obsess over performance, efficiency, and simplicity.
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisExcited to share that Verisoul has raised a $9M Series A to build products that make the internet safer from fraud, bots, and fake accounts. Legacy incumbents have hundreds of engineers working on this. We have just 3. And yet, Verisoul: → Wins in H2H customer tests >85% of the time → Catches 70-105% more fraud with 10-28% fewer false positives → Analyzes Billions of data points across 100M+ User sessions every month How? 1/ Focus - our engineering team only works on signals, models, and architecture that move the needle 2/ Modern stack - we use world-class architecture elements like Spanner by GCP, StarRocks, Dragonfly, and Chalk & In house feature platforms 3/ In-office - our team sits together every day, working together on the hardest engineering problems I’ve seen in my career Join Us If this sounds like your kind of challenge, we're growing the team: 👉Site Reliability & Infrastructure Engineer 👉Platform Engineer 👉Data Intelligence Engineer (Real-time and Offline) Come work with Raine Scott and me in Austin!
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisYour cache cluster is throwing “𝗕𝗮𝗻𝗱𝘄𝗶𝗱𝘁𝗵 𝗔𝗹𝗹𝗼𝘄𝗮𝗻𝗰𝗲 𝗘𝘅𝗰𝗲𝗲𝗱𝗲𝗱” errors, but your CPU is idle. 😓 The culprit? You’ve been forced to scale out onto small, network bandwidth-constrained instances. Our latest blog dives deep into the hidden bottlenecks of scaling and why your data store must scale up before it scales out. https://hubs.la/Q03YmHCX0 #CloudComputing #Databases #PerformanceEngineering #ElastiCache #Redis #Valkey #ScalabilityThe Hidden Bottlenecks of Scaling Out: Network, CPU, and MemoryThe Hidden Bottlenecks of Scaling Out: Network, CPU, and Memory
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisJoin this session for a complete overview and demo of Dragonfly Cloud, the fully hosted version of the Dragonfly in-memory data store. Content will include: - An overview of Dragonfly's architecture - Performance benchmarks - Use cases and results from real customers - A full product demo
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisReady to catch Dragonfly at #AWSreInvent? 😃 We’re at 𝗕𝗼𝗼𝘁𝗵 𝟭𝟴𝟱𝟱! Come by for exclusive tech demos, strategic 1-on-1 chats, and some of the best swag. Drop by or secure your time with our team for a dedicated discussion: https://lnkd.in/gzqpfNtM Let’s connect! #AWSreInvent2025 #CloudComputing #DataInfrastructure
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisWe’re breaking the memory barrier! 🚀 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗱𝗮𝘁𝗮 𝘁𝗶𝗲𝗿𝗶𝗻𝗴 𝗶𝗻 𝗗𝗿𝗮𝗴𝗼𝗻𝗳𝗹𝘆: extending RAM with SSDs to handle massive datasets at a fraction of the cost. Read the announcement, deep dive, and benchmarks vs. ElastiCache: https://hubs.la/Q03VQXF40 #DataTiering #ElastiCache #DataInfrastructureDragonfly SSD Data Tiering: Cost-Effective Scaling for Massive WorkloadsDragonfly SSD Data Tiering: Cost-Effective Scaling for Massive Workloads
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Mykhailo Faraponov reposted thisMykhailo Faraponov reposted thisAWS re:Invent is fast approaching, and I’m excited to share that DragonflyDB will be sponsoring this year’s event. If you’re running large in-memory workloads, come by Booth #1855. We’d love to learn about the challenges you face and show you how Dragonfly can simplify scaling, cut infrastructure overhead, and deliver the performance your application demands. I look forward to connecting in person at AWS re:Invent. #reinvent2025 #Redis #Valkey #aws #devops
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisVictoriaLogs is used as a database for GDPR-compliant web analytics at Ayedo - https://lnkd.in/d7bCNCjPDSGVO-konforme Website Analytics mit nginx, VictoriaLogs und Grafana | ayedoDSGVO-konforme Website Analytics mit nginx, VictoriaLogs und Grafana | ayedo
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Mykhailo Faraponov reacted on thisMykhailo Faraponov reacted on thisБарбер рассказал прохладную былину.. Заказал себе с Китая реплику Нарсиля. Все доставили, 3.7 кг, фактически двуручник. И вот едет в машине, меч на заднем сиденье. Останавливают его 2 инспектора. Так, ну документы, туда-сюда. - Ого, а что это у вас на заднем сиденье? - (опускает стекло) Да вот, Нарсиль. - Чегоооооо? - (второй инспектор) Да ты чо, это же меч из Властелина Колец!!!! Слушай, дай попробовать... - (первый) Слушай, это точно разрешено? - Да, конечно, это реплика, не заточен, вон у коллеги потрогай сам.. И вот стоят на обочине два инспектора ДПС, один машет мечом, рядом проезжают другие машины видимо С ВОТ ТАКИМИ ГЛАЗАМИ у водителей... #tldr
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisIn-place Pod Resize in Kubernetes 1.35 🚀 One of the most practical improvements in the latest Kubernetes release is in-place Pod resize. Until now, changing CPU or memory resources required a Pod restart. Even with RollingUpdates, this still meant container restarts, cold starts, potential performance impact, and re-established connections. With in-place resize, we can now update resource requests and limits without restarting the Pod. Kubernetes updates cgroup settings directly. This is no longer an alpha feature – it's production ready. https://lnkd.in/ezYq-vMu #kubernetes #cncf #cloudnative #devops
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Mykhailo Faraponov reacted on thisMykhailo Faraponov reacted on thisVector search just got significantly faster in Dragonfly v1.37. In our latest release, we’ve made improvements to deliver 7x higher throughput and 65x lower latency for vector search workloads . Whether you're building RAG pipelines, recommendation engines, semantic search, fraud detection systems, or other high-concurrency vector workloads, this release delivers meaningful performance gains without additional infrastructure. Read the full announcement: https://hubs.la/Q045FZCF0 #vectorsearch #RAG
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisAs if the open-source battlefield is not bloody enough (Elastic vs. AWS, Hashi vs. World, Redis vs. itself), now comes AI to saw off the branch it is sitting on. https://lnkd.in/d_KxhbCV Is that a risk for Dragonfly? You’d have to be completely crazy to run your own data store, let alone write one from scratch. (For example: Roman Gershman)
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisChannels are overused in Go. A mutex is faster, simpler, and often the right choice. Since I started to learn Go, I always felt weird about using channels for managing the state of a struct, in order to make it thread-safe. I always thought of channels as a mechanism for transmitting messages around multiple goroutines, safely. But I saw this pattern in many codebases, when using channels with empty structs. At first glance looks fine, empty message passed, no memory overhead, pretty neat, right? But on a second thought, I decided to understand how channel are working under the hood, and it struck me, that it adds a bigger overhead . First, channels are executing more operations, besides locking, including, queue management, and context switching. And benchmarks are suggesting that for the same locking purpose, mutexes perform from 10x to 50x much better. And I don’t even mention “atomics”. Second, it’s easier to handle a mutex, with defer, rather than debugging a channels’ deadlock. But, on the contrary, channels are super easy to grasp, and I totally get it, but it should be used for the purpose it was build: to share memory by communicating. Which for a complex orchestration of data flow between goroutines it works best. This is why, I will stick to the principle to use the right tool for the job. #golang #goroutines #channels #performance #performanceoptimization #concurrency #concurrentprogramming #multithreading
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisWhen I gave my AI agents a mission to plan a journey to Jupiter, I expected them to crash and die. 💀 Why? I didn’t give them enough fuel ⛽ The spaceship should have crashed. But then something unexpected happened... Instead of blindly executing the plan (and dying), the agents started debating. They negotiated, argued, and proposed alternatives. Eventually, they chose a gravitational slingshot (via Venus to Jupiter), trading time for fuel. That was the breakthrough moment. 🤯 I realized I wasn’t watching code execute. I was watching a room full of engineers trying to solve a problem together. From that point on, the shift became clear to me: The future isn’t about strict hardcoded workflows - it’s about creating a capabilities matrix. I’m excited to share that I was chosen to showcase this unique space travel story at the Wix Engineering Conference 2026! 🚀 PS - demo code on GitHub will be shared before my talk, stay tuned!
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Mykhailo Faraponov liked thisMykhailo Faraponov liked thisLast month, I almost completely switched from #cursor to #cloudcode in the terminal (Ghostty). When I first tried Claude Code about seven months ago, I decided to stay with Cursor because of the UX - the classic IDE experience and the convenient ability to review and accept changes. At the time, I couldn’t understand how anyone could use “YOLO” mode (where changes are auto-accepted), especially since you often need to apply semi-manual fixes. But things are changing. Now Cursor feels more like a single-process solution, while Claude Code feels more like a multi-process workflow. Working from the terminal makes it easier to iterate quickly, spawn parallel tasks, and move faster without being locked into a single flow. It still needs polish and occasional fixes, but the effort has shifted. Instead of going back and forth with the LLM, guessing at issues, I’m focusing on real engineering work - investigating race conditions, adding tests for edge cases, and strengthening the implementation.
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ScalableSpace
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See projectSimple Shared Database Hosting with Redis, KeyDB, PostgreSQL, MySQL, Clickhouse, Cassandra support based on multi-cloud K8S
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ScaleChamp
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See projectMulti Cloud Managed Databases Provider.
With Redis, KeyDB, PostgreSQL, MySQL support.
Across ALL major and some minor clouds.
With 3 languages support! -
FortressShell
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See projectContinuos Integration SaaS and on-prem to help individuals and companies to speed up dev-test-release cycle. Bachelor degree dyploma project
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English
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Milan Jovanović
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You don’t need DDD on day one. I see devs overbuilding their domain models way too early. Trying to impress someone, maybe? When I built a fitness tracking app, we started with simple transaction scripts. Just one procedure per user action. It was fast, easy to reason about, and worked great. As the app grew and logic got more complex, we gradually moved to a richer domain model. That’s the key: Transaction scripts aren’t a stepping stone. They’re often the right choice for simple use cases. Start simple. When complexity shows up, then reach for DDD. What am I actually trying to say? Software engineering is about understanding the tools and patterns you're using. They all work - given the right context. It's your responsibility to understand that context. Now, this takes some experience and trial and error. --- Do you want to simplify your development process? I created a free Clean Architecture template to help you. Get it here: https://lnkd.in/eBbQcsCY
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Mobile Innovation Network
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🚀 Let's Talk: Gradle Dependency Configurations in Android If you’ve ever written implementation, api, or compileOnly in your build.gradle, but weren’t exactly sure what’s happening behind the scenes — you’re not alone! 👀 Let’s break it down: 🔹 implementation Most commonly used. Adds the dependency to your module, but hides it from other modules that depend on your module. Helps keep build times fast and dependencies encapsulated. 🔹 api Used when you want to expose a dependency to other modules that depend on your module. Useful for creating shared libraries or SDKs. 🔹 compileOnly Adds the dependency at compile-time only. It's not bundled with the final APK. Great for annotations or compile-time libraries like Lombok. 🔹 runtimeOnly Used for dependencies needed only at runtime—not at compile time. 🔹 testImplementation / androidTestImplementation Used to add dependencies for unit tests or Android instrumented tests respectively. Keeps test dependencies separate from production code. 🔍 Why does it matter? Understanding and using these configurations correctly improves build performance, promotes clean architecture, and avoids bloated APKs. 💬 How do you organize your Gradle dependencies? Share your thoughts or best practices below! #Android #JetpackCompose #KMP #CMP #Kotlin #kotlinMultiplatform #ComposeMultiplatform #ChainTech #MobileInnvoationNetwork
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Kamalesh R V
Vellore Institute of… • 3K followers
🚀 Java 25 LTS is here! (Released Sept 16, 2025) Think back for a moment… Do you remember the first time you wrote this? 👇 public static void main(String[] args) { System.out.println("Hello, World!"); } Most of us didn’t really understand what public, static, or String[] meant. We just trusted the magic. ✨ Now fast forward to Java 25 → that same magic feels simpler, cleaner, more approachable: void main() { System.out.println("Hello, World!"); } ✅ Streamlined syntax ✅ Beginner-friendly ✅ Still enterprise-grade at its core Java 25 shows us that a language can be: 👉 Elegant enough for beginners 👉 Robust enough for the enterprise It’s a reminder: great design is both powerful and approachable. 👀 Curious—when was the first time you wrote your “Hello, World!” in Java? (And do you still remember how confused you were by that method signature? 😅) #Java #Java25 #LTS #DeveloperExperience #Coding #HelloWorld #JavaCommunity
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Stephan 🦄 Schmidt
Amazing CTO • 12K followers
#ADRs (Architecture decision record) are like event sourcing. ADRs are written down decisions about architecture. Why did you chose React? Why not Angular? What were the Pro and Cons and why was that solution the winner? They make it easy for developers new to the company or new to the team to understand the decisions BEHIND the current tech stack and architecture. So they can make better decisions themselves. A side effect of ADRs is that you do not have the same discussion over and over again. How are they like Event Sourcing? ADRs have not the downside of normal documentation. Normal documentation is hard to keep in sync with reality. It's a tedious process, and nearly impossible if you did not find the right level of documentation (deep enough, but not too deep). ADRs do not change. They are write-one-read-often, they are read only. They don't need to be maintained, they are always correct. In this way they are like events in Event Sourcing. Those also do not change. And ADRs can be seen as an event, and to get an understanding of the current state of your architecture, you need to read and aggregate those ADRs, just like events in event sourcing. https://adr.github.io/
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Richard Seidl
Richard Seidl • 14K followers
"So we have automation classes where people need to test, students need to write automation scripts and that's how they got introduced to what is a test case. And you would have to automate it." - Dmitrij Nikolajev In this episode, I talk with Dmitrij Nikolajev about teaching software testing to the next generation. Dmitrij, who balances roles at InSoft and Vilnius University, shares his approach to making software testing engaging for students. He focuses on practical, hands-on experience, using tools like Postman and Selenium to teach automation and performance testing. Dmitrij redesigned his course to appeal to both new learners and those already in the industry. He leverages real-world examples to highlight the importance of testing, encouraging students to understand the consequences of failures. We also discuss the role of AI tools like ChatGPT in the learning process and their impact on student progress. What do you mean? What do you think of the approach to first teach test automation instead of test theory? Write in the comments. #softwaretesting #career #quality ISTQB® - International Software Testing Qualifications Board
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Stefan Đokić
Paysend • 108K followers
RabbitMQ is a message broker. Think of it like a reliable postal service for your software. Whether you're building microservices or want to offload work from your main app, RabbitMQ is one of the best tools to help you get there. Instead of one system directly calling another (which creates tight coupling), RabbitMQ acts as the middleman: • One part of your app sends a message. • Another part receives and processes it when it's ready. This is known as asynchronous communication, and it’s particularly beneficial for performance, reliability, and scalability. Key Components: • Producer: The one who sends the messages. • Consumer: The one who receives the messages. • Queue: Where the messages wait until they are processed. • Exchange: The "dispatcher" that directs the messages to the appropriate queues. • Binding: The rules that connect exchanges with queues. You can easily set it up using Docker. Read full implementation: https://lnkd.in/dTeRjEA8
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Matt Mochalkin
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Is NGINX + PHP-FPM becoming obsolete? 🚀 The "Worker Mode" revolution is here and the performance gains are impossible to ignore. I just dropped a deep-dive benchmark pitting the two heavyweights of the modern PHP ecosystem against each other: FrankenPHP vs. RoadRunner, running on Symfony 8 and PHP 8.4. We didn't just test "Hello World." We pushed them through real-world scenarios: ✅ Database Writes & Doctrine ORM ✅ Heavy Serialization (API Platform style) ✅ CPU-bound Matrix Multiplication ✅ Memory Leak & Restart Stability The Results? Both runtimes decimated the traditional FPM setup, offering 3x-4x throughput gains in database scenarios. 🔹 RoadRunner proved to be a beast in raw stability and ecosystem maturity (Queues, gRPC). 🔹 FrankenPHP shone with its incredible simplicity (single binary!) and winning Time-To-First-Byte on heavy serialization tasks. If you are building high-performance Symfony applications in 2026, you need to understand these architectures. 👇 Read the full benchmark analysis and GitHub repo: [https://lnkd.in/daCmrwDj] [https://lnkd.in/dbunCVbS] Which runtime are you betting on? Let's discuss in the comments! 💬 #Symfony #PHP #FrankenPHP #RoadRunner #WebDevelopment #Backend #Performance #TechLeads
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Sui Foundation
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Party Objects are here on Sui mainnet! Think of them as a new type of object that blends: 🔒 Control of owned objects 📑 Consensus versioning of shared objects That means objects you can move between fastpath & consensus, with built-in versioning - and soon, multi-owner + granular permissions. Learn more 👇 https://lnkd.in/eVZn8ZMJ
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Donald Murillo
Two Nerdy Cats • 780 followers
After months of testing (both professionally and as hobby) AI tools for Angular development, here are my findings: Most models struggle with Angular 18+ features without proper pre-prompting (I am looking at you Google). Claude 3.5/3.7 handles modern Angular best, but you need to guide it (Kudos Anthropic). Local models? Skip them unless you have 24GB+ RAM to spare. VSCode Copilot works great for large codebases (I think this is worth the $100), Cline is fun for smaller projects (I will be trying this on larger codebases soon, so stay tuned). Tools like Bolt.new (I had faith bolt.new...) keep trying to revert to Angular 16 - frustrating. More honest insights: https://lnkd.in/d7Ek2cSE Bonus: This is my basic to-go pre-promo (copilot-instructions.md / .clinerules / .cursorrules) # Angular Modern Development Guidelines & Single File Component Example This document outlines best practices for building modern Angular applications using: - **Signals & Computed Properties** for reactive state - New **output** instead of @Output - The **`inject()` function** for dependency injection - **Signal queries** (as available even if not stable) instead of decorators like `@ViewChild` - Angular's **new control flow syntax** - **OnPush change detection** for performance - **Strict TypeScript** (with no non-null assertions) - **Single File Components** (all template, style, and logic in one file) - **Tailwind CSS** for styling - **Tailwind Animations** when necessary - **Light and Darkmode** Always make colors compatible with light and dark mode > **Note:** Adjust any experimental API (e.g., signal queries) as the Angular framework evolves. ## 1. Prerequisites - **Angular Version:** 18+ (supporting signals, computed properties, and the new APIs) - **Project Structure:** Using an Nx monorepo (if applicable) - **TypeScript:** Strict mode enabled (avoid using `!` for possible null values) - **Tailwind CSS:** Properly integrated in your project build - **Animations:** Use tailwind animations module if animations are used ## 2. Comprehensive Single File Component Example IOU - will add it to a section on the guide. ## 3. Additional Guidelines - **Single File Components:** Encapsulate component's template, styles, and logic within one file - **OnPush Change Detection:** Use for performance and future-proofing - **Strict TypeScript:** Avoid non-null assertions and leverage strict mode - **Tailwind CSS:** Use utility classes directly in templates - **Animations:** Use Tailwind. Keep subtle and performant - **New Control Flow Syntax:** Use Angular's improved flow control instead of structural directives - **Dependency Injection:** Prefer the `inject()` function in standalone components - **Indentation** Use tabs and set them as 3 spaces #Angular #WebDev #AI
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Manvendra Patel
R1 RCM • 680 followers
Hey everyone, Been coding in .NET for years, but still feel like I’m always discovering something new. Last few weeks I focused on some topics that (honestly) we all know, but sometimes don’t go deep enough: - Async / Await & Task Parallelism – still easy to misuse. Knowing when to await and when not to block a thread saves headaches. - Dependency Injection (DI) – it is more than just AddScoped<>. Lifetime (Singleton vs Scoped vs Transient) matters a lot in scaling apps. -Entity Framework Core Performance – Avoid the classic N+1 queries, use AsNoTracking(), know when to use raw SQL. - Middleware vs Filters – I used to confuse them, but Middleware handles the request pipeline, Filters apply to controller actions. - Caching & Distributed Cache – In-memory vs Redis, and how it reduces response time. - Security in .NET – JWT tokens, Data Protection API, and how .NET 8 identity improvements simplify auth. I feel revisiting these areas makes me more confident during code review nd also in designing APIs that scale better. #DotNet #CSharp #BackendDevelopment #SoftwareEngineering #CloudComputing #DotNetCore #Azure #Microsoft
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