DevOps&SRE Library
前往频道在 Telegram
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
显示更多📈 Telegram 频道 DevOps&SRE Library 的分析概览
频道 DevOps&SRE Library (@devopslibrary) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 19 876 名订阅者,在 技术与应用 类别中位列第 6 610,并在 俄罗斯 地区排名第 33 156 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 19 876 名订阅者。
根据 28 十月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 1,过去 24 小时变化为 -8,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 13.25%。内容发布后 24 小时内通常能获得 6.75% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 2 633 次浏览,首日通常累积 1 341 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 主题关注点: 内容集中在 kubernete, cluster, infrastructure, storage, configuration 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
凭借高频更新(最新数据采集于 29 十月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
19 876
订阅者
-824 小时
-187 天
+130 天
帖子存档
19 874
Ephemeral Infrastructure: Why Short-Lived is a Good Thing
https://lukasniessen.medium.com/ephemeral-infrastructure-why-short-lived-is-a-good-thing-2cf26afd75ef
19 874
⚠️ Модель отлично работала на обучении, а в продакшене — начала ошибаться? Данные те же. Код тот же. Это data drift — одна из ключевых причин деградации ML-моделей в реальных системах.
25 февраля в 20:00 МСК на открытом уроке в преддверии старта курса «MLOps» разберём, почему даже хорошие модели со временем теряют качество, какие бывают типы смещения данных и как отличить реальную проблему от статистического шума. Покажем практические инструменты обнаружения data drift и разберём типовое решение задачи мониторинга на практике.
🦾 Вы поймёте, почему в продакшене недостаточно обучить модель один раз, и как выстроить контроль качества, чтобы ML-система оставалась полезной бизнесу.
Урок будет полезен тем, кто уже работает с моделями или готовится выводить их в продакшен и хочет понимать, что происходит с ML после деплоя.
➡️ Принять участие: https://vk.cc/cUzYYa
Реклама. ООО «Отус онлайн-образование», ОГРН 1177746618576, erid: 2VtzqwEUffa
19 874
Dynamic Istio Ingress Gateway Management with Kyverno
https://medium.com/devtopia/dynamic-istio-ingress-gateway-management-with-kyverno-a807b6e3f0f8
19 874
Tuckr
Tuckr is a dotfile manager inspired by Stow and Git. Tuckr aims to make dotfile management less painful. It follows the same model as Stow, symlinking files onto $HOME. It works on all the major OSes (Linux, Windows, BSDs and MacOS). Tuckr aims to bring the simplicity of Stow to a dotfile manager with a very small learning curve. To achieve that goal Tuckr tries to only cover what is directly needed to manage dotfiles and nothing else. We won't wrap git, rm, cp or reimplement the functionality that are perfeclty covered by other utilities in the system unless it greatly impacts usability.https://github.com/RaphGL/Tuckr
19 874
A Comprehensive Comparison of Cloud Backup Tools
This blog post is a comparison of personal, accessible, cloud backup options.https://www.ybrikman.com/blog/2026/02/03/computer-backup-options
19 874
Why the OpenTelemetry Batch Processor is Going Away (Eventually)
This article explains why OpenTelemetry no longer recommends the batch processor for production durability-sensitive pipelines. It compares in-memory batching with exporter-level persistent queues and shows how the newer approach improves recovery during collector restarts.https://www.dash0.com/blog/why-the-opentelemetry-batch-processor-is-going-away-eventually
19 874
Create readable terraform plans for pull request reviews with tfplan2md
This article introduces tfplan2md, a tool that converts Terraform JSON plans into clearer markdown summaries for pull request reviews. It focuses on making plan output easier to understand in Azure DevOps and GitHub workflows.https://levelup.gitconnected.com/create-readable-terraform-plans-for-pull-request-reviews-with-tfplan2md-ea646e00e59b
19 874
Scaling Terraform Across many Teams: A Native Framework for Platform Engineering
This write-up presents a pure Terraform framework where 50+ teams deploy infrastructure using simple tfvars while platform teams maintain reusable building blocks. It highlights native lookup patterns, automated PR updates, and significant boilerplate reduction without adding preprocessing layers.https://dev.to/jverhoeks/-scaling-terraform-across-many-teams-a-native-framework-for-platform-engineering-3n0b
19 874
Unconventional PostgreSQL Optimizations
Creative ideas for speeding up queries in PostgreSQLhttps://hakibenita.com/postgresql-unconventional-optimizations
19 874
OpenTelemetry Collector vs agent: How to choose the right telemetry approach
https://www.cncf.io/blog/2026/02/02/opentelemetry-collector-vs-agent-how-to-choose-the-right-telemetry-approach
19 874
“You Had One Job”: Why Twenty Years of DevOps Has Failed to Do it
I think the entire DevOps movement was a mighty, twenty year battle to achieve one thing: a single feedback loop connecting devs with prod. On those grounds, it failed.https://www.honeycomb.io/blog/you-had-one-job-why-twenty-years-of-devops-has-failed-to-do-it
19 874
Is the future of MySQL PostgreSQL (Or MariaDB, or TiDB, or ...)?
https://stokerpostgresql.blogspot.com/2026/01/is-future-of-mysql-postgresql-or.html
19 874
Why Your HA Architecture is a Lie (And That's Okay)
https://mydbanotebook.org/posts/why-your-ha-architecture-is-a-lie-and-thats-okay
19 874
Introduction to Buffers in PostgreSQL
The work around RegreSQL led me to focus a lot on buffers. If you are a casual PostgreSQL user, you have probably heard about adjusting shared_buffers and followed the good old advice to set it to 1/4 of available RAM. But after we went a little bit too enthusiastic about them on a recent Postgres FM episode I've been asked what that's all about. Buffers are one of those topics that easily gets forgotten. And while they are a foundation block of PostgreSQL's performance architecture, most of us treat them as a black box. This article is going to attempt to change that.https://boringsql.com/posts/introduction-to-buffers
19 874
How OpenAI Scales Postgres to Power 800 Million ChatGPT Users
For years, PostgreSQL has been one of the most critical, under-the-hood data systems powering core products like ChatGPT and OpenAI’s API. As our user base grows rapidly, the demands on our databases have increased exponentially, too. Over the past year, our PostgreSQL load has grown by more than 10x, and it continues to rise quickly.https://openai.com/index/scaling-postgresql
19 874
10 Elasticsearch Production Issues (and How Postgres Avoids Them)
Elasticsearch may work great in initial testing and development but Production is a different story. This blog is about what happens after you ship: the JVM tuning, the shard math, the 3 AM pages, the sync pipelines that break silently. The stuff your ops team lives with. After years of teams running Elasticsearch in production, certain patterns keep emerging. The same issues show up in blog posts, Stack Overflow questions, and incident reports. We've compiled ten of the most common ones below, with references to the engineers who've documented them. We’ve also added images to make it easy to quickly skim through it and compare the challenges against Postgres. TLDR: With great power comes great operational complexity.https://www.tigerdata.com/blog/10-elasticsearch-production-issues-how-postgres-avoids-them
19 874
The future of software engineering is SRE
When code gets cheap operational excellence wins. Anyone can build a greenfield demo, but it takes engineering to run a service.https://swizec.com/blog/the-future-of-software-engineering-is-sre
19 874
prek
pre-commit is a framework to run hooks written in many languages, and it manages the language toolchain and dependencies for running the hooks.https://github.com/j178/prek
19 874
Hi! My good friend is looking for a colleague to join their team.
You can check the details of the position and apply here: https://jobs.ashbyhq.com/perplexity/7bce0fcf-eef6-41aa-9243-896f07a0316e
If you have additional questions about the position, you can send them to
alena@perplexity.ai.19 874
zerobrew
zerobrew applies uv's model to Mac packages. Packages live in a content-addressable store (by sha256), so reinstalls are instant. Downloads, extraction, and linking run in parallel with aggressive HTTP caching. It pulls from Homebrew's CDN, so you can swap brew for zb with your existing commands. This leads to dramatic speedups, up to 5x cold and 20x warm.https://github.com/lucasgelfond/zerobrew
