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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

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📈 Telegram kanali DevOps&SRE Library analitikasi

DevOps&SRE Library (@devopslibrary) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 19 424 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 6 933-o'rinni va Rossiya mintaqasida 34 753-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 19 424 obunachiga ega bo‘ldi.

15 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 169 ga, so‘nggi 24 soatda esa 4 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 14.78% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.10% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 870 marta ko‘riladi; birinchi sutkada odatda 1 379 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 1 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 16 Iyun, 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.

19 424
Obunachilar
+424 soatlar
+537 kunlar
+16930 kunlar
Postlar arxiv
What does using AI for post-mortems actually mean? https://incident.io/blog/what-does-using-ai-for-post-mortems-actually-mean

Why LLMs Write Incorrect SQL (and What That Means for Your Database)
Most LLM-generated SQL doesn't fail. It runs and returns results, and that's exactly what makes it dangerous. The errors don't surface until they're already in your data.
https://readyset.io/blog/why-llms-write-incorrect-sql-and-what-that-means-for-your-database

The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale
In the three years since our first Live show, Chris Rock: Selective Outrage, we have witnessed an incredible expansion of our live content slate and the live operations that support it. From modest beginnings of streaming just one show per month, we are now capable of streaming over nine shows in a single day, reaching tens of millions of concurrent members. This post pulls back the curtain on the Live Operations teams that enable this rapid scale.
https://netflixtechblog.com/the-human-infrastructure-how-netflix-built-the-operations-layer-behind-live-at-scale-33e2a311c597

codeburn
CodeBurn tracks token usage, cost, and performance across 19 AI coding tools. It breaks down spending by task type, model, tool, project, and provider so you can see exactly where your budget goes.
https://github.com/getagentseal/codeburn

openhare
openhare is an AI-powered, cross-platform desktop SQL client with multi-database support, built for everyday development, data analysis, and DBA management workflows.
https://github.com/sjjian/openhare

eraser
Eraser helps Kubernetes admins remove a list of non-running images from all Kubernetes nodes in a cluster.
https://github.com/eraser-dev/eraser

Стартуем с Kubernetes без боли в Managed Kubernetes от MWS Cloud Platform. 27 мая в 16:00 Александр Курасов, технический влад
Стартуем с Kubernetes без боли в Managed Kubernetes от MWS Cloud Platform. 27 мая в 16:00 Александр Курасов, технический владелец продукта в MWS Cloud Platform, покажет, как развернуть кластер за минуты, на вебинаре «Быстрый старт с Managed Kubernetes в облаке MWS». Разберём архитектуру сервиса, его интеграцию с IAM, сетями и балансировщиками. Увидите, как управляемый сервис берёт на себя администрирование master-узлов и упрощает жизнь. Будет интересно: ♦DevOps-инженерам, которые хотят упростить работу с Kubernetes ♦Backend-разработчикам, которым нужно быстро задеплоить сервис ♦Platform-инженерам, строящим cloud-native инфраструктуру ♦Техлидам и архитекторам, выбирающим Kubernetes в облаке ➡ Зарегистрироваться

I Don’t Care if AI Wrote the Code. You Own It.
SREcon Chair Heinrich Hartmann on why the age of AI-assisted engineering demands a radical return to design rigor.
https://www.runllm.com/blog/i-dont-care-if-ai-wrote-the-code-you-own-it

Superficial Blamelessness
For many organizations, some form of blamelessness has become a more standard practice and blame-awareness has been gaining in popularity. However, there is an anti-pattern I have noticed as well, which I like to call superficial (or shallow) blamelessness that I think is important for people to be on the lookout for.
https://resilienceinsoftware.org/news/11502437

Not all index scans are equal: How we cut query latency by over 99% https://www.datadoghq.com/blog/detect-inefficient-index-scans-with-dbm

hunk
Hunk is a review-first terminal diff viewer for agent-authored changesets, built on OpenTUI and Pierre diffs.
https://github.com/modem-dev/hunk

chartpack
A single, opinionated Helm chart for deploying any Kubernetes application workload. Instead of maintaining separate charts per application, define your entire deployment through values.
https://github.com/cotzo/chartpack

kubebuilder
Kubebuilder is a framework for building Kubernetes APIs using custom resource definitions (CRDs).
https://github.com/kubernetes-sigs/kubebuilder

pii-shield
Zero-code log sanitization sidecar for Kubernetes. Prevents data leaks (GDPR/SOC2) by redacting PII from logs before they leave the pod.
https://github.com/aragossa/pii-shield

LLMs on Kubernetes: The Easy Way
Sometimes, you just want to run a Large Language Model (LLM)… no Jupyter notebook, no training pipeline, no fancy UI.
https://pittar.medium.com/llms-on-kubernetes-the-easy-way-f1ff6e0d47be

Orchestrating Secure AI Agents on Amazon EKS
How we went from scaling video analysis on EKS to running autonomous coding agents in a custom agent harness, and why Kubernetes was the obvious choice.
https://dev.to/mattcamp/orchestrating-secure-ai-agents-on-amazon-eks-50kh

What 6 Months of Tracking a Production OpenShift Cluster Revealed About Kubernetes Costs
Most Kubernetes teams track pod CPU and memory. Almost none track what the cluster actually costs to run.
https://blog.kubeledger.io/what-6-months-of-tracking-a-production-openshift-cluster-revealed-about-kubernetes-costs

Running Temporal.io on Kubernetes in Production — What Nobody Tells You
A practical guide to GKE deployment, Cassandra backups, Istio security, and surviving your first outage
https://medium.com/@devansh2054/running-temporal-io-on-kubernetes-in-production-what-nobody-tells-you-d1f336e99306