How .NET 10's garbage collector impacts performance and diagnostics

Speed matters! Users abandon apps that take >3 seconds to load. I just published a breakdown of caching and the basics of it, one of the most powerful techniques to dramatically improve application performance. Watch here: https://lnkd.in/gVknx86u  #SystemDesign #SoftwareEngineering #Performance

Docker — Bind Mount vs Volume ✅ Explanation: Both store persistent data, but with different behavior: - Bind Mount: Maps a specific host folder to the container. Example: -v /local/path:/app/data Useful for development (changes reflect instantly). - Volume: Managed entirely by Docker. Example: -v app_data:/data Better for production, portable, and safer. Best Practice: Use volumes for production data, bind mounts for local dev.

𝐒𝐩𝐚𝐧<𝐓> 𝐚𝐧𝐝 𝐌𝐞𝐦𝐨𝐫𝐲<𝐓> 𝐢𝐧 .𝐍𝐄𝐓: 𝐖𝐫𝐢𝐭𝐢𝐧𝐠 𝐇𝐢𝐠𝐡 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐂𝐨𝐝𝐞 Most .NET performance issues are not caused by algorithms. They come from unnecessary memory allocations. In this new article, we explore how Span<T> and Memory<T> help us: ✅ Avoid copying data ✅ Reduce GC pressure ✅ Work with slices of arrays and strings ✅ Improve throughput in real workloads ✅ Write faster code without unsafe tricks The result is cleaner, safer, and more efficient .NET apps. 👉 Link in the comments #DotNet #CSharp #Performance #Span #Memory #HighPerformanceCode #Backend #SoftwareEngineering #CleanCode #GarbageCollection

Did You Know? In n8n, every webhook node comes with two URLs; a Test URL and a Production URL. Here’s why that matters: When you’re building or testing your workflow, you use the Test URL. Once everything works and you publish your workflow, n8n automatically switches to the Production URL. If you keep using the test one after publishing, your workflow won’t trigger anymore🫣. So the rule is simple: ✅ Use the Test URL while building. ✅ Switch to the Production URL after activation. This small detail saves many people from hours of debugging! If your webhook suddenly stops firing, double-check the URL, it’s probably still the test one. #automation #n8n #nocode #webhooks #workflowautomation #aiautomation #makecom #zapier #businessautomation #crmautomation

🚀 Fault Tolerance vs. High Availability: What’s the Difference? Ever wondered how systems stay online during failures? Let’s break it down simply: 🔧 Fault Tolerance (FT): Think of it as a system that *never stops*. It uses mirrored components (like Penguin Solutions Stratus ftServer’s dual processors) to instantly handle failures—no downtime, no data loss. Perfect for critical apps like financial trading or healthcare where every second counts. 💯 🛠️ High Availability (HA): This is about *quick recovery*. If something fails, HA systems switch to a backup fast, but there might be a brief pause (seconds or minutes). Great for things like websites where a short hiccup is okay. ⚡ 🌟 Penguin Stratus & FT: Penguin Solutions Stratus platforms (like ftServer) are built for zero downtime with real-time redundancy and AI-driven monitoring to catch issues before they disrupt. Ideal for edge computing or mission-critical setups. 💡 Key Difference: FT = no interruptions, HA = minimal interruptions. Choose based on how critical your app is! #TechSimplified #FaultTolerance #HighAvailability #Stratus #Reliability #PenguinSolutions

🌊 Day 36 | Performance Engineering: The Power (and Pitfalls) of Connection Pooling Ever seen an app handle load perfectly at first — then suddenly slow down or throw “too many connections” errors? 😬 That’s often a connection pooling issue. 🧠 What’s happening: Each user request needs a database connection. Without pooling, the app creates new connections for every request — expensive and slow. With pooling, connections are reused — but only if the pool is configured just right. 💡 Watch for these signs: • Connection timeout errors under load. • DB sessions hitting max limit. • Response times growing over test duration. ⚙️ Tuning tips: ✅ Set max pool size based on DB capacity (not just app threads). ✅ Configure idle timeout to close unused connections. ✅ Monitor active vs. idle connections during load tests. ✅ Use connection leak detection to find unreleased connections. 🎯 Pro tip: Too few connections = queueing. Too many = DB thrashing. Find your sweet spot through iterative testing. #PerformanceTesting #PerformanceEngineering #Database #ConnectionPooling #LoadTesting

Handling HTTP Requests in React with AbortController Introduction When building React applications, we often need to fetch data from APIs. But what happens if a component is removed from the page before the request finishes? AbortController. What does “unmounting a component” mean? Unmounting a component means React removes it from the DOM. This can happen when: The user navigates to another page or component. Conditional rendering becomes false The parent component is removed or updated. After unmounting, you should not update the component’s state. If a fetch request is still running and tries to update state, React shows this warning: Warning: Can't perform a React state update on an unmounted component. This warning indicates a potential memory leak. The fetch continues running even though the component is gone, wasting memory and CPU. What is AbortController and why use it? AbortController is a browser API that allows you to cancel an ongoing fetch request. Benefits: Prevents warnings when a component unmounts before the req https://lnkd.in/gnMYmkCB

📊 𝗖𝗼𝗹𝗱‑𝗦𝘁𝗮𝗿𝘁 𝗗𝗿𝗼𝗽: 𝟮 𝘀 → 𝟴𝟬𝟬 𝗺𝘀 We reduced our HTTP‑trigger cold‑start by 60% using: 1️⃣ Precompiled Assemblies (func extensions install) 2️⃣ Premium Plan + Always On 3️⃣ Dependency Bundling (fewer, larger packages) Results Chart: Before: 2 000 ms After: 800 ms 💬 How have you tackled cold‑start? Tips welcome! #AzureFunctions #Serverless #DotNet #Performance

Have you ever faced a situation where a failing service starts slowing down your entire application? That’s exactly the problem the Circuit Breaker Pattern solves. What it is: A circuit breaker is a design pattern that prevents an application from repeatedly calling a failing service. It acts like an electrical #circuit_breaker — when failures exceed a threshold, it “trips” and temporarily blocks further calls. Why we need it: In distributed systems or microservices, a single slow or failing service can cause cascading failures. Without protection, your app threads get blocked, response times increase, and user experience suffers. What problem it solves: * Stops repeated calls to failing services * Prevents cascading failures across microservices * Gives the failing service time to recover * Improves system stability and user experience How to use it: * Track consecutive failures * Open the circuit after reaching a threshold * After a cooldown period, allow test requests (Half-Open) * Close the circuit if test requests succeed, otherwise keep it open This pattern is especially useful for APIs, payment gateways, external integrations, or any service your application depends on. Pair it with retry, fallback, and timeout policies to make your system rock-solid. #DotNet #Microservices #Azure #BackendDevelopment #Polly #SystemDesign #Resilience