How WHIP and WHEP simplify WebRTC signaling and reduce latency

Excited to announce that dRPC is an official RPC Provider for Circle's Arc. Testnet access is now available via public endpoints: → https://lnkd.in/d5qQ-phP Built on NodeCloud, dRPC offers a robust RPC foundation for Arc devs: > AI-powered load balancing > Globally distributed nodes > Outage-proof performance > Trusted by top L1 and L2 ecosystems Designed for teams who’d rather build and grow — not babysit infrastructure.

A blog post on which I worked for about a month is finally live on the TechOps Services website, and it couldn't come at a better time. An RPC proxy and load balancer is a must when it comes to connecting your dApp or wallet to your own RPC node or even 3rd-party providers like Alchemy or Infura. A single point of failure is never a good choice, take it from the huge outage that the Internet faced today due to a single region of a single provider going down... In this post, I share benchmark results from dozens of tests, offering an evidence-based comparison between dshackle and aetherlay, two tools designed for pretty much the same, but differently: https://lnkd.in/diPiXAQJ

Recently benchmarked UnisonDB against BadgerDB and BoltDB using the official redis-benchmark tool — focusing on SET (write) performance through UnisonDB’s Redis-compatible interface. UnisonDB consistently delivers higher throughput and lower latency compared to both BadgerDB and BoltDB across multiple runs — showing the strength of its log-native design and optimized write path. Read more and explore the benchmarks: https://lnkd.in/gKs_Yhfw

Found something interesting while profiling our microservices last week: Using async/await everywhere actually increased latency under high concurrency. Why? Because async isn’t “free” — it allocates state machines, creates continuations, and increases GC pressure. In CPU-bound code (like data mapping, compression, or in-memory joins), async actually slows you down. ✅ Fix: Removed async from CPU-heavy code, kept it for I/O-bound tasks (HTTP, DB, file ops). ✅ Result: 23% lower CPU load under 1,000 concurrent requests. Lesson: Async is a tool — not a default. Use it with intent, not habit. #DotNet #PerformanceEngineering #Async #Microservices

Why SSE Still Matters in a WebSocket World? In the last post, we explored webhooks and how something as simple as a POST call powers integrations at a global scale. This time, we are going one layer deeper. We all talk about real-time, but that word hides a lot of complexity. - Do we really need bi-directional communication? - Do we really need WebSockets for everything that “updates live”? Server-Sent Events (SSE) is the underrated tool for one-way stream that quietly powers real-time dashboards, stock tickers, CI pipelines, and live logs. The moment we try to scale SSE, connection registries, fan-out, consistent hashing, and node ownership, it becomes a distributed systems problem. That’s where it got more interesting and harder. I broke it all down the same way I did with webhooks, from how connections are tracked to how events are routed across nodes, and how to make it work when millions of users are connected. If you enjoy systems that look simple but hide beautiful complexity underneath, you’ll probably like this one. Read it here - https://lnkd.in/gNG5GWGh #ServerSentEvents #SSE #RealTimeSystems #StreamingData #EventDrivenArchitecture #DistributedSystems #BackendEngineering #SystemDesign #ScalableArchitecture #PubSub

🚀 Day 1 — Learning Distributed Systems: RPCs, gRPC & tRPC 🚀 Today in my 21-Day Distributed Systems Sprint, I dove into the backbone of microservices: how services communicate efficiently. I explored: - RPC (Remote Procedure Call): calling functions on other machines as if local. - gRPC: high-performance, strongly typed RPC using HTTP/2 + Protocol Buffers (protobufs). - tRPC: TypeScript-native RPC for fullstack apps with end-to-end type safety. I built my first Express + TypeScript gRPC service with unary and streaming RPCs, learned how metadata, TLS, deadlines, and error codes work, and even compared REST vs gRPC vs GraphQL vs tRPC. Github repo for the demo gRPC and tRPC project: https://lnkd.in/gYJ_KCgq 💡 Takeaways: - Use gRPC for internal microservices, especially cross-language systems. - Use tRPC for fullstack TS apps for simplicity and type safety. - Always pick the right tool for your communication pattern. 📖 Check out the full Medium article with examples and deep explanations here: https://lnkd.in/gnFyCn9j ⭐ Do star the repo if it helps you. It really motivates me to keep documenting and building more examples every day! I’ll be posting daily updates, experiments, and code snippets. If distributed systems, microservices, or scalable backends interest you — follow along! #DistributedSystems #Microservices #gRPC #tRPC #BackendEngineering #LearnInPublic #TypeScript #NodeJS #SystemDesign

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

🧩 When I started, we deployed manually and considered a release successful if nothing crashed. 🚀 Today, CI/CD is standard, observability via OpenTelemetry is the norm, and fault tolerance is designed in from day one. 💥 The backend has evolved from “just a server” to the nervous system of every digital product. ✅ What has been the most important technological shift in recent years for you? #BackendDevelopment #SoftwareEngineering #Development #ComplexSystems #TechLeadership

Designing Production-Ready RAG Pipelines: Tackling Latency, Hallucinations, and Cost at Scale: ... data quality standards. The quality of data affects user experience through hallucinations which occur when poor data quality exists. System ...

EPCIS is the language, every translation layer distorts the message. TL-XML is the proof. Translation layers and proprietary schemas add friction, latency, and data drift, distorting traceability at its source. Watch the full episode of Decommissioned: Standard Deviation. How data standards should power automation, efficiency, and insight. #Serialization #EPCIS #DataStandards #DigitalTransformation #PharmaSupplyChain #DecommissionedPodcast #Ankhero