DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Mostrar más📈 Análisis del canal de Telegram DevOps&SRE Library
El canal DevOps&SRE Library (@devopslibrary) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 19 416 suscriptores, ocupando la posición 6 942 en la categoría Tecnologías y Aplicaciones y el puesto 34 783 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 416 suscriptores.
Según los últimos datos del 13 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 171, y en las últimas 24 horas de 9, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 14.76%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.06% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 866 visualizaciones. En el primer día suele acumular 1 371 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
- Intereses temáticos: El contenido se centra en temas clave como kubernete, cluster, infrastructure, storage, configuration.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 14 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
We jump into a hands-on exploration of Model Context Protocol (MCP), sharing our experiment using a MCP client to run terraform init, plan, apply. We share our take on where agents add value and highlight security considerations when adding MCPs to your workflow.https://masterpoint.io/blog/using-mcps-to-run-terraform
Rybbit is the modern open source and privacy friendly alternative to Google Analytics. It takes only a couple minutes to setup and is super intuitive to use.https://github.com/rybbit-io/rybbit
A Model Context Protocol (MCP) server that provides tools for interacting with the Terraform Registry API. This server enables AI agents to query provider information, resource details, and module metadata.https://github.com/thrashr888/terraform-mcp-server
Winter Soldier can be used to - cleans up (delete) Kubernetes resources - reduce workload pods to 0 at user defined time of the day and conditions. Winter Soldier is an operator which expects conditions to be defined using CRD hibernator.https://github.com/devtron-labs/winter-soldier
Wave watches Deployments, StatefulSets and DaemonSets within a Kubernetes cluster and ensures that their Pods always have up to date configuration. By monitoring mounted ConfigMaps and Secrets, Wave can trigger a Rolling Update of the Deployment when the mounted configuration is changed.https://github.com/wave-k8s/wave
A NetworkPolicy is a Kubernetes resource that defines rules for controlling the traffic flow to/from pods. It works at layer 3 (IP) and layer 4 (TCP/UDP) of the OSI model. The policies are namespaced and use labels to identify the target pods and define allowed traffic.https://medium.com/@umangunadakat/kubernetes-network-policies-41f288fa53fc
Tackle OOMs => reliable training => win !https://medium.com/better-ml/tackling-oom-strategies-for-reliable-ml-training-on-kubernetes-dcd49a2b83f9
Спикеры: • Эмиль Ибрагимов — о генерации CLI из OpenAPI • Валерий Локтаев — об автоматизации Terraform • Георгий Фатеев — о безопасности Go-кодаЭтот митап — классная возможность узнать, как строится облачная платформа изнутри, и задать вопросы топовым инженерам в неформальной обстановке. Go Up to the Cloud! Музей истории Екатеринбурга, 18:00. Регистрация
When we launched User Management along with a free tier of up to 1 million MAUs, we faced several challenges using Heroku: the lack of an SLA, limited rollout functionality, and inadequate data locality options. To address these, we migrated to Kubernetes on EKS, developing a custom platform called Terrace to streamline deployment, secret management, and automated load balancing.https://workos.com/blog/from-four-to-five-9s-of-uptime-by-migrating-to-kubernetes
This post is a deep dive into comparing different solutions for authenticating into a Kubernetes cluster. The goal of this post is to give you an idea of what the various solutions provide for a typical cluster deployment using production capable configurations. We're also going to walk through deployments to get an idea as to how long it takes for each project and look at common operations tasks for the each solution. This blog post is written from the perspective of an enterprise deployment. If you're looking to run a Kubernetes lab, or use Kubernetes for a service provider, I think you'll still find this useful. We're not going to do a deep dive in how either OpenID connect or Kubernetes authentication actually works.https://www.tremolo.io/post/kubernetes-authentication-comparing-solutions
Over the last year, the platform team here at Timescale has been working hard on improving the stability, reliability and cost efficiency of our infrastructure. Our entire cloud is run on Kubernetes, and we have spent a lot of engineering time working out how best to orchestrate its various parts. We have written many different Kubernetes operators for this purpose, but until this year, we always used StatefulSets to manage customer database pods and their volumes. StatefulSets are a native Kubernetes workload resource used to manage stateful applications. Unlike Deployments, StatefulSets provide unique, stable network identities and persistent storage for each pod, ensuring ordered and consistent scaling, rolling updates, and maintaining state across restarts, which is essential for stateful applications like databases or distributed systems. However, working with StatefulSets was becoming increasingly painful and preventing us from innovating. In this blog post, we’re sharing how we replaced StatefulSets with our own Kubernetes custom resource and operator, which we called PatroniSets, without a single customer noticing the shift. This move has improved our stability considerably, minimized disruptions to the user, and helped us perform maintenance work that would have been impossible previously.https://www.timescale.com/blog/replacing-statefulsets-with-a-custom-k8s-operator-in-our-postgres-cloud-platform
A reflection on our journey towards AWS Karpenter, improving our Upgrades, Flexibility, and Cost-Efficiency in a 2,000+ Nodes Fleethttps://medium.com/adevinta-tech-blog/the-karpenter-effect-redefining-our-kubernetes-operations-80c7ba90a599
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