DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Ko'proq ko'rsatish📈 Telegram kanali DevOps&SRE Library analitikasi
DevOps&SRE Library (@devopslibrary) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 19 758 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 6 527-o'rinni va Rossiya mintaqasida 33 399-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 19 758 obunachiga ega bo‘ldi.
27 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 137 ga, so‘nggi 24 soatda esa 7 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 14.01% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.00% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 768 marta ko‘riladi; birinchi sutkada odatda 1 382 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 0 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent kubernete, cluster, infrastructure, storage, configuration kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 28 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
There’s a particular kind of infrastructure bug that’s deeply annoying to debug: the kind that only appears when your cluster is under load. Everything runs fine in steady state. Then you push a release, or traffic spikes and your autoscaler kicks in, and suddenly you’re chasing 502s that resolve on their own a few minutes later. Your first instinct is to blame the app. Then the deployment. Then the cluster. Then yourself. We hit exactly this pattern at Simon AI. The culprit turned out to be something fundamental about how nginx handles DNS — and fixing it properly required waiting for a feature that was finally open-sourced at the end of 2024. Here’s what we found, what we tried, and how we solved it.https://streamn-dad.medium.com/how-nginxs-new-resolve-directive-finally-fixed-our-kubernetes-502s-e32633804d33
kage (影, "shadow") clones a website into a folder you can browse offline, with every script stripped out. It opens each page in real headless Chrome, waits for the page to settle, snapshots the DOM a human would have seen, then deletes all the JavaScript and pulls the CSS, images, and fonts down to local paths. What lands on disk looks like the live site and runs no code.https://github.com/tamnd/kage
Gamedays are one of the most effective ways we proactively uncover gaps in our systems and processes. At Datadog, we regularly run a variety of gamedays to intentionally stress our platforms and learn how our systems and teams respond under real-world conditions. These exercises help us surface hidden vulnerabilities, strengthen our operational readiness, and continually raise the bar for our infrastructure. During one such gameday, a simulated zonal failure introduced targeted disruptions in an availability zone on a staging environment by inducing network latency, which exposed a weakness in our PostgreSQL architecture. Several of our Kubernetes-based PostgreSQL clusters had primary or writer nodes running in the affected availability zone. As network latency spiked, those primaries could no longer communicate reliably with their replicas. Replication lag quickly grew, writes stalled, and applications began serving stale data. Because no replica was sufficiently up to date, failover wasn’t safe and the clusters were effectively stuck. We rely on PostgreSQL as the backend database for many Datadog products, and this architecture has served us well under normal conditions. But the gameday revealed an uncomfortable truth: In the face of certain network failures, our setup prioritized availability over durability in ways that left us with no safe recovery path. In practice, this meant the primary continued accepting writes even while replication to replicas was delayed due to elevated network latency. The system remained writable, but replication lag continued to grow, and replicas drifted further behind the primary. As a result, failover candidates could no longer be promoted safely without risking data loss. We were left with only one viable option: wait for latency to subside and for replicas to catch up. We set out to fix this failure mode. Our goal was to make failover both automatic and safe, without compromising PostgreSQL’s performance characteristics more than necessary. To do this, we rearchitected our PostgreSQL deployment to use synchronous replication for failover candidates, coordinated by Patroni, an open source high-availability manager. In this post, we’ll walk through how we redesigned our Kubernetes-based PostgreSQL clusters for failover safety, how we balanced durability against latency, and what we learned while validating this approach through benchmarking and failure testing.https://www.datadoghq.com/blog/engineering/postgresql-ha-kubernetes
How Airbnb built a Kubernetes sidecar to deliver dynamic configuration reliably at scale.https://medium.com/airbnb-engineering/sitar-agent-building-a-reliable-dynamic-configuration-sidecar-at-scale-b7e00c152068
We investigated why firmware updates were causing our core servers to take four hours to reboot.https://blog.cloudflare.com/optimizing-core-unit-boot-time
Spontaneous swarming of responders might seem like a nuisance that breaks our tidy mental models of incident response, but it's actually very powerful.https://greatcircle.com/blog/2026/03/24/swarming-is-a-feature
If you serve LLMs on Kubernetes without inference-aware routing, your load balancer is likely wasting inference capacity. Generic HTTP traffic management blindly routes requests, assuming the backends in your cluster are interchangeable. But your model-serving backends are stateful and unevenly prepared to handle any given request. As a result, requests are often routed to the backend that’s not the one best suited to respond. Migrating to Gateway API gives you a more capable foundation for traffic management and opens the door to inference-aware routing. The Kubernetes Gateway API’s Inference Extension routes requests based on backend serving state, which tends to make better use of cluster capacity and reduce request latency. In this post, we’ll look at how the Inference Extension works, the routing strategies it enables, and the signals you can use to monitor whether inference-aware routing is behaving as intended in production.https://www.datadoghq.com/blog/llm-routing-kubernetes-inference-extension/
Practically all of my work happens inside a terminal. Git, kubectl, tmux, ssh'ing into a server, open practically the entire day. Something I use that much has to be fast. Any lag in opening a new tab, typing a character or hitting tab for a completion is something I feel hundreds of times a day. It's death by a thousand cuts.https://mijndertstuij.nl/posts/life-is-too-short-for-a-slow-terminal
Long-running, fault-tolerant SQL functions for teams that already keep their state in Postgres and want to stop stitching together cron jobs, workers, queues, and status tables to make background work reliable. Define the workflow in SQL, let pg_durable checkpoint each step, and resume after crashes, restarts, or failed steps. Durable execution is now a standard industry pattern, and pg_durable brings it inside Postgres with no extra service infrastructure required. Part of our mission to bring compute close to data.https://github.com/microsoft/pg_durable
Zero-config, fast io_uring-based HTTPS server. zeroserve serves a website packaged as a tarball, and handles hot-reload via SIGHUP.https://github.com/losfair/zeroserve
