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DevOps&SRE Library

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

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📈 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 19 395 名订阅者,在 技术与应用 类别中位列第 6 952,并在 俄罗斯 地区排名第 34 902

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 19 395 名订阅者。

根据 10 六月, 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 154,过去 24 小时变化为 7,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 15.22%。内容发布后 24 小时内通常能获得 7.12% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 949 次浏览,首日通常累积 1 380 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 1
  • 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 11 六月, 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。

19 395
订阅者
+724 小时
+67
+15430
帖子存档
Enroll
Enroll inspects a Debian-like or RedHat-like system, harvests the state that matters, and generates Ansible roles/playbooks so you can bring snowflakes under management fast.
https://enroll.sh

ch-vmm
ch-vmm is a Kubernetes add-on for running Cloud Hypervisor virtual machines. By using Cloud Hypervisor as the underlying hypervisor, ch-vmm enables a lightweight and secure way to run fully virtualized workloads in a canonical Kubernetes cluster.
https://github.com/nalajala4naresh/ch-vmm

clickhouse-operator
The Altinity Kubernetes Operator for ClickHouse creates, configures and manages ClickHouse clusters running on Kubernetes.
https://github.com/Altinity/clickhouse-operator

kexa
Kexa is an open-source compliance management tool that simplifies security and compliance across multiple cloud platforms including Azure, Google Cloud, AWS, and more.
https://github.com/kexa-io/kexa

build
Shipwright is an extensible framework for building container images on Kubernetes.
https://github.com/shipwright-io/build

Strengthen Kubernetes Security with Vault Agent Injector https://hackernoon.com/strengthen-kubernetes-security-with-vault-agent-injector

Intelligent Kubernetes Load Balancing at Databricks
Real-Time, Client-Side Load Balancing for Internal and Ingress Traffic in Kubernetes
https://www.databricks.com/blog/intelligent-kubernetes-load-balancing-databricks

Extracting JVM Data from Crash-Looping Java Containers in Kubernetes https://medium.com/@zelldon91/getting-data-out-of-burning-java-containers-6e0c8bb53eec

Karpenter at Beekeeper by LumApps: Fun Stories
At the beginning of this year, we (Beekeeper by LumApps Engineering) decided to adopt Karpenter for our EKS (Kubernetes/K8s) workloads, replacing our previous node autoscaling setup that used cluster-autoscaler with a managed autoscaling group (ASG). We made this decision before the release and hype of EKS Auto Mode, which is why we chose to implement a self-managed Karpenter solution.
https://medium.com/beekeeper-technology-blog/karpenter-at-beekeeper-by-lumapps-fun-stories-7c55656f02b8

It works on my cluster: a tale of two troubleshooters https://octopus.com/blog/verifying-and-troubleshooting-kubernetes-deployments

How we deploy the largest GitLab instance 12 times daily
Take a deep technical dive into GitLab.com's deployment pipeline, including progressive rollouts, Canary strategies, database migrations, and multiversion compatibility.
https://about.gitlab.com/blog/continuously-deploying-the-largest-gitlab-instance

Pulse
Pulse is a modern, unified dashboard for monitoring your infrastructure across Proxmox, Docker, and Kubernetes. It consolidates metrics, alerts, and AI-powered insights from all your systems into a single, beautiful interface.
https://github.com/rcourtman/Pulse

notifuse
The open-source alternative to Mailchimp, Brevo, Mailjet, Listmonk, Mailerlite, and Klaviyo, Loop.so, etc. Notifuse is a modern, self-hosted emailing platform that allows you to send newsletters and transactional emails at a fraction of the cost. Built with Go and React, it provides enterprise-grade features with the flexibility of open-source software.
https://github.com/Notifuse/notifuse

databasus
Databasus is a free, open source and self-hosted tool to backup databases. Make backups with different storages (S3, Google Drive, FTP, etc.) and notifications about progress (Slack, Discord, Telegram, etc.).
https://github.com/databasus/databasus

ente
Ente is a service that provides a fully open source, end-to-end encrypted platform for you to store your data in the cloud without needing to trust the service provider. On top of this platform, we have built two apps so far: Ente Photos (an alternative to Apple and Google Photos) and Ente Auth (a 2FA alternative to the deprecated Authy).
https://github.com/ente-io/ente

arcane
Modern Docker Management, Designed for Everyone
https://github.com/getarcaneapp/arcane

pgedge-postgres-mcp
The pgEdge Postgres Model Context Protocol (MCP) server enables SQL queries against PostgreSQL databases through MCP-compatible clients like Claude Desktop. The Natural Language Agent provides supporting functionality that allows you to use natural language to form SQL queries.
https://github.com/pgEdge/pgedge-postgres-mcp

pg_textsearch
PostgreSQL extension for BM25 relevance-ranked full-text search. Postgres OSS licensed.
https://github.com/timescale/pg_textsearch

KISS vs DRY in Infrastructure as Code: Why Simple Often Beats Clever
Every Infrastructure as Code tutorial starts the same way: provision a single S3 bucket, create one EC2 instance, deploy a basic load balancer. The examples are clean, simple, and elegant. You follow along, everything works, and you feel like you understand Terraform. Then you get to your actual production environment, and everything changes. You’re not starting from scratch with a blank AWS account. You’ve got existing resources that were manually created two years ago by someone who left the company. There’s brownfield infrastructure everywhere with no clear documentation. You need to import existing state, figure out what’s actually running, and somehow wrangle it all into code without breaking production. On top of that, you need to manage 200 instances across dev, staging, and production environments. Multiple AWS accounts with different configurations and permissions. Three regions for disaster recovery. Azure for the legacy workloads that nobody wants to touch. GCP running your GKE clusters for the containerized applications. Suddenly that elegant tutorial code becomes a nightmare of orchestration, state management, environment-specific configurations, and brownfield complexity. You’re not just writing infrastructure code anymore. You’re trying to organize, orchestrate, and maintain it at scale while dealing with the reality that infrastructure is messy, evolving, and full of historical baggage. This is the scale gap, and it’s where the KISS vs DRY debate stops being theoretical and starts costing real time, money, and engineering effort.
https://rosesecurity.dev/2025/11/14/kiss-versus-dry-iac.html