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 19 414 подписчиков, занимая 6 932 место в категории Технологии и приложения и 34 727 место в регионе Россия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 19 414 подписчиков.
Согласно последним данным от 19 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 123, а за последние 24 часа — -3, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 14.85%. В первые 24 часа после публикации контент обычно набирает 7.26% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 883 просмотров. В течение первых суток публикация набирает 1 409 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 1.
- 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 20 июня, 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.
Know enough to be dangerous in 10 minuteshttps://metoro.io/blog/distributed-tracing-whistle-stop-tour
While working on SLOs, SLAs and SLIs I have found that there are only so many ways to aggregate service metrics. I have not yet found somewhere that attempts to review the different aggregation methods and what their relative strengths and weaknesses are.https://hross.substack.com/p/different-ways-to-aggregate-nines
Everyone experiences stress at work—thankfully, it’s a topic folks aren’t shying away from anymore. But for on-call engineers, alert fatigue is a phenomenon closer to home. Unfortunately, like stress, it can be just as insidious and drastically impact those it affects. First discussed in the context of hospital settings, this phrase later entered engineering circles. Alert fatigue is when an excessive number of alerts overwhelms the individuals responsible for answering them, often over a prolonged period, resulting in missed or delayed responses, or them being ignored altogether The impact of this fatigue can have an effect beyond the individual and can create significant risks for your organization. But, if you approach on-call the right way, you can mitigate the impacts of alert fatigue or, better yet, avoid it altogether. Here, we'll dive into the tactics teams can implement to address alert fatigue and its underlying causes.https://incident.io/hubs/on-call/dealing-with-alert-fatigue-head-on
Introduction to the SLA in relation to SLI and SLOhttps://blog.alexewerlof.com/p/sla
Core principles of documentation-as-code tools - Treating documentation with the same rigor as code - Storing documentation in version control - Automation of documentation generation and deployment - Peer review processes for documentation updateshttps://www.tabnine.com/blog/documentation-as-code-principles-workflow-and-challenges
A key challenge of monitoring your CI/CD system is understanding how to optimize your workflows and create best practices that help you minimize pipeline slowdowns and better respond to CI issues. In addition to monitoring CI pipelines and their underlying infrastructure, your organization also needs to cultivate effective relationships between platform and development teams. Fostering collaboration between these two teams is a critical and equally valuable aspect of improving the reliability and performance of your CI. In this post, we’ll explore how platform teams can help developers visualize trends in CI test performance and notify them of new flaky tests, test failures, and performance regressions with dashboards and monitors. We’ll also detail best practices that can help developers identify, investigate, and remediate flaky tests.https://www.datadoghq.com/blog/best-practices-for-monitoring-software-testing
Kubernetes has been a great orchestrator of Jobs and CronJobs for over half a decade now, but if you had a need for running proxy containers or other secondary containers alongside the job, running things properly took a bit of work and decision-making to handle gracefully. This article introduces the easiest way to run Jobs with sidecars using the latest Kubernetes features, and has a complementary repository with complete example manifests you can try in your own cluster. The repository contains all the examples for earlier versions of K8s as well, so make sure to focus on the cronjob.sidecar.*.yaml examples.https://medium.com/teamsnap-engineering/properly-running-kubernetes-jobs-with-sidecars-in-2024-k8s-1-28-ad9b51d17d50
Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication features. Garnet can work with existing Redis clients.https://github.com/microsoft/garnet
Our nine month journey to horizontally shard Figma’s Postgres stack, and the key to unlocking (nearly) infinite scalability. Figma’s database stack has grown almost 100x since 2020. This is a good problem to have because it means our business is expanding, but it also poses some tricky technical challenges. Over the past four years, we’ve made a significant effort to stay ahead of the curve and avoid potential growing pains. In 2020, we were running a single Postgres database hosted on AWS’s largest physical instance, and by the end of 2022, we had built out a distributed architecture with caching, read replicas, and a dozen vertically partitioned databases. We split groups of related tables—like “Figma files” or “Organizations”—into their own vertical partitions, which allowed us to make incremental scaling gains and maintain enough runway to stay ahead of our growth.https://www.figma.com/blog/how-figmas-databases-team-lived-to-tell-the-scale
An open source virtual hand-drawn style whiteboard.https://github.com/excalidraw/excalidraw
GritQL is a declarative query language for searching and modifying source code.https://github.com/getgrit/gritql
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