DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Больше📈 Аналитический обзор Telegram-канала DevOps&SRE Library
Канал DevOps&SRE Library (@devopslibrary) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 19 865 подписчиков, занимая 6 619 место в категории Технологии и приложения и 33 090 место в регионе Россия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 19 865 подписчиков.
Согласно последним данным от 30 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -7, а за последние 24 часа — -7, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 13.27%. В первые 24 часа после публикации контент обычно набирает 6.74% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 637 просмотров. В течение первых суток публикация набирает 1 339 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как kubernete, cluster, infrastructure, storage, configuration.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Благодаря высокой частоте обновлений (последние данные получены 01 ноября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
While migrating Pinterest’s search infrastructure — which powers core experiences for millions of users monthly — to Kubernetes, we faced a challenge in the new environment: one in every million search requests took 100x longer than usual. This post chronicles our investigation, uncovering an elusive interaction between our memory-intensive search system and a seemingly innocent monitoring process. The journey involves profiling search systems, debugging performance issues, Linux kernel features, and memory management.https://medium.com/pinterest-engineering/debugging-the-one-in-a-million-failure-migrating-pinterests-search-infrastructure-to-kubernetes-bef9af9dabf4
s3grep is a parallel CLI tool for searching logs and unstructured content in Amazon S3 buckets. It supports .gz decompression, progress bars, and robust error handling—making it ideal for cloud-native log analysis.https://github.com/dacort/s3grep
Strategies from SRE leaders fighting noisy alerts in complex system.https://rootly.com/blog/the-art-of-not-getting-woken-up-for-nothing
Terraform has two looping mechanisms for creating multiple resources, count and for_each. The count meta-argument has been around for a long time, but for_each is a relative newcomer (introduced in version 0.12). Each meta-argument allows you to create more than one resource or module with a single configuration block.https://nedinthecloud.com/2022/01/27/choosing-between-count-and-for-each
In this post I'm going to demonstrate 2 reasons I will be avoiding auto-increment fields in Postgres and MySQL in future. I'm going to prefer using UUID fields unless I have a very good reason not to.https://samwho.dev/blog/practical-problems-with-auto-increment
We're using AI to build an agentic product that works collaboratively with responders to improve incident investigations and resolve incidents faster. A bold claim, I know, and I think pretty impressive to land the word “agentic” so early on—I promise it’s the last time I use it. After six months of digging into this, I’m convinced: AI in incident response won’t just be helpful—it’ll be essential. As more software is built with, and increasingly by, AI, responders will have less and less context about the systems they’re operating. That shrinking understanding—combined with the ever-growing volume of software—only increases the need for tools that can assist. Done right, there's a huge upside in this approach too—faster incident resolution, reduced customer impact, and less cognitive burden on the folks putting out the fires. But with more automation comes a new shape of risk—much of which is captured in Lisanne Bainbridge’s 1983 paper, Ironies of automation. In the paper, Bainbridge explains that automation meant to help can paradoxically make things harder. As routine tasks get automated, human skills fade from lack of practice, so when the system fails (and they will!), responders are left underprepared and out of context. Working in tech companies, I’m yet to see these risks materialise seriously, but there are definite elements of truth here. Count the number of Kubernetes incidents where operators have no idea what’s happening and you’ll get the gist.https://incident.io/building-with-ai/avoiding-the-ironies-of-automation
Most guides to the finer aspects of managing databases like Postgres are… not great. The Postgres documentation is well-written, but it has too much information for most developers. On the other hand, most online Postgres optimization guides are essentially a repeated version of: “Run this command. Got it? Cool.” This should provide you with a relatively brief introduction to Postgres tuning, focusing on the most important knobs, while also describing how these knobs relate to Postgres’s overall functioning and internals.https://byteofdev.com/posts/tuning-postgres-intro
Реклама. ООО «Отус онлайн-образование», ОГРН 1177746618576, erid: 2VtzqwRoyoPThis article will teach you how to continuously promote application releases between environments on Kubernetes using the GitOps approach.https://piotrminkowski.com/2025/01/14/continuous-promotion-on-kubernetes-with-gitops
