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DevOps&SRE Library

DevOps&SRE Library

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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 19 875 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 6 610-o'rinni va Rossiya mintaqasida 33 156-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 19 875 obunachiga ega bo‘ldi.

27 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 19 ga, so‘nggi 24 soatda esa -2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 13.30% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 6.75% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 644 marta ko‘riladi; birinchi sutkada odatda 1 342 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 2 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 Oktabr, 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.

19 875
Obunachilar
-224 soatlar
-117 kun
+1930 kun
Postlar arxiv
mq
mq is a command-line tool that processes Markdown using a syntax similar to jq. It's written in Rust, allowing you to easily slice, filter, map, and transform structured data.
https://github.com/harehare/mq

Say the Thing You Want
You’re in a 1:1 with your manager, and things are going just fine. You talk about the project and that other thing. Toward the end, she asks: “Anything else?” And there is something else. You want to lead that new initiative. Or move to a different team. Or you’ve been thinking about what stands in the way of your promotion. The thought is right there, sitting in the back of your throat. You’re going to say it, and then… “Nope, all good.” You get out of the call feeling a specific kind of regret. You rationalize it somehow and then tell yourself you’ll bring it up next time (you won’t).
https://terriblesoftware.org/2026/04/01/say-the-thing-you-want

Why Teamwork Makes (Or Breaks) Your Incident Response
High-severity incidents expose how a team really works together, usually within the first ten minutes.
https://uptimelabs.io/articles/teamwork-incident-response

Why reviewing AI-generated code is devilishly hard
When working on code with GenAI assistance you need a better understanding of the system than when working without.
https://www.spinellis.gr/blog/20260523

Humans aren't fast enough for 4 9's
When thinking about Service Level Objectives (SLOs) and contractual Service Level Agreements (SLAs) for availability, I always like to put the percentages into concrete numbers.
https://incident.io/blog/humans-arent-fast-enough-for-4-nines

On benchmarking
Benchmarking is hard. There are many ways to do it wrong and few to do it right. But zooming out from any single system or harness, there are broad principles that should be applied to all benchmarking. Using these correctly makes it difficult to produce biased results. Am I the world's best benchmarker? Certainly not. I invented the language balls, after all. But correctness and precision are important parts of PlanetScale's culture. We've spent considerable time learning the art of benchmarking, and are here to share best-practices. Here, we're focusing primarily on benchmarking databases, but these principles apply to many domains.
https://planetscale.com/blog/on-benchmarking

You Shipped It Fast. But Did You Ship It Right?
AI tools have genuinely changed how fast teams can produce code, but they haven't changed how fast a codebase can safely absorb that code.
https://stackoverflow.blog/2026/05/12/you-shipped-it-fast-but-did-you-ship-it-right

The Problem with AI-Generated Post-Incident Reviews
The real learning comes from analyzing the incident while writing the document, not reading it; the document at the end is the residue of the learning.
https://greatcircle.com/blog/2026/05/05/problem-with-ai-generated-post-incident-reviews

agentgram
A single front door for all your AI agents and MCPs
https://github.com/dfradehubs/agentgram

Что общего у SRE и рыбаков? «GitOps = реальность» — это миф? Не создаёт ли Chaos Engineering ещё больше хаоса?.. Звучит как т
Что общего у SRE и рыбаков? «GitOps = реальность» — это миф? Не создаёт ли Chaos Engineering ещё больше хаоса?.. Звучит как те самые внезапные вопросы перед сном в будний день 👀 И, кстати, ответ на все три у нас имеется! Правда, не здесь, а в подкасте «В SREду на кухне» — его ведут опытные инженеры из Авито. Они обсуждают наболевшее, приглашают внешних гостей и коллег, а также делятся дополнительными инсайтами, статьями по теме и анонсами встреч в своём канале. Советуем подписаться и сохранить на будущее пару выпусков 🧠

SlimFaas
SlimFaas is a lightweight, plug-and-play Function-as-a-Service (FaaS) platform for Kubernetes (and Docker-Compose / Podman-Compose).
https://github.com/SlimPlanet/SlimFaas

Building a Production-Grade HA Kubernetes Cluster on a Homelab with $0 in Cloud Costs
How I turned four Proxmox nodes, some enterprise surplus drives, and an afternoon into a fully automated HA k3s cluster with Rancher, Traefik, and Ansible — all running on hardware that draws less power than a gaming PC.
https://thiago-marsal.medium.com/homelab-k3s-ha-cluster-a-complete-architecture-guide-6a60005b6e99

Designing for Failure with CloudNativePG
This post focuses on three areas that separate a demo from production systems: backups, recovery and connection pooling.
https://dylanmarkdacosta.medium.com/designing-for-failure-with-cloudnativepg-2c3987605a39

Durable Workflows Beyond Vercel: Version-Safe Orchestration for Kubernetes
Workflow DevKit lets you write durable, long-running workflows directly in your Next.js and Node.js apps. You define steps with ’use step’, and the SDK handles persistence, retries, and replay automatically. Workflows survive server restarts, can sleep for days, and resume exactly where they left off. On Vercel, all of this works out of the box — the platform handles deployment versioning and queue routing behind the scenes. But what happens when you deploy to your own Kubernetes cluster? Version mismatch. And it’s subtle enough to corrupt data before you notice. We built Platformatic World to fix this. It’s a drop-in World implementation that brings the same deployment safety to any Kubernetes cluster. Every workflow run is pinned to the code version that created it. Queue messages are routed to the correct versioned pods. Old versions stay alive until all their in-flight runs are complete.
https://blog.platformatic.dev/durable-workflows-kubernetes-version-safe

Why Kubernetes Has No Login — And How We Solved It for AuditRadar
When we set out to build the Logins page for AuditRadar — a real-time audit log explorer for OpenShift and Kubernetes — we hit a wall that forced us to deeply understand how authentication actually works on each platform.
https://blog.audit-radar.com/why-kubernetes-has-no-login-and-how-we-solved-it-for-auditradar

A one-line Kubernetes fix that saved 600 hours a year
Every time we restarted Atlantis, the tool we use to plan and apply Terraform changes, we’d be stuck for 30 minutes waiting for it to come back up.
https://blog.cloudflare.com/one-line-kubernetes-fix-saved-600-hours-a-year

InfraDev Community приглашает на InfraDev Meetup #4: про AI и не только Прямо сейчас мы наблюдаем как AI в SDLC меняет процес
InfraDev Community приглашает на InfraDev Meetup #4: про AI и не только Прямо сейчас мы наблюдаем как AI в SDLC меняет процесс разработки — об удачных примерах и кейсах поговорим в этот раз. Обсудим, как разрабатывать инфраструктурные сервисы с помощью AI и как построить MLOps-платформу для обучения моделей. И не только: пока AI не перестроил DevOps-цикл, классические вызовы сборки образов для виртуальных машин остаются актуальными. Спикеры ▫️Кирилл Фролов, эксперт-разработчик в отделе разработки базовых сервисов, VK Cloud, VK Tech ▫️Павел Шипилов, Старший разработчик ML Платформы в Avito ▫️Александр Александров, системный архитектор в направлении разработки и управления инфраструктурой, VK Cloud, VK Tech Подробнее о докладах читайте на странице мероприятия. Когда: 10 июня, с 18:00 до 23:59 Где: Москва, Ленинградский пр., 70, офис VK Tech, БЦ «Алкон» (количество мест ограничено). Приходите на встречу или участвуйте онлайн. Зарегистрироваться.

Why Your KServe InferenceService Won't Become Ready: Four Production Failures and Fixes
A practitioner's account of the errors the KServe getting-started documentation doesn't tell you about — with exact terminal output, root causes, and working Kustomize patches.
https://sodiq-jimoh.hashnode.dev/why-your-kserve-inferenceservice-won-t-become-ready-four-production-failures-and-fixes

Incident Report: May 19, 2026 - GCP Account Suspension
Railway experienced a platform-wide service disruption due to Google Cloud incorrectly placing our account in a suspended status.
https://blog.railway.com/p/incident-report-may-19-2026-gcp-account-outage