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 19 885 suscriptores, ocupando la posición 6 593 en la categoría Tecnologías y Aplicaciones y el puesto 33 159 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 885 suscriptores.
Según los últimos datos del 26 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 23, y en las últimas 24 horas de -8, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 13.22%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 6.74% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 629 visualizaciones. En el primer día suele acumular 1 340 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- 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 27 octubre, 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.
OpenKruise Agents provides best practices for managing AI agent workloads in Kubernetes. It is a sub-project of the open-source workload project OpenKruise under the Cloud Native Computing Foundation (CNCF), specifically tailored for the AI agent domain. OpenKruise Agents accelerates AI agent deployment and makes it easily accessible to both AI algorithm scientists and infrastructure engineers.https://github.com/openkruise/agents
I'm starting a series of blog posts to explore CloudNativePG (CNPG), a Kubernetes operator for PostgreSQL that automates high availability in containerized environments.https://dev.to/franckpachot/cloudnativepg-install-218-and-first-test-transient-failure-4ml
If you've ever wanted to develop a command line client for a Kubernetes API, especially if you've considered making your client usable as a kubectl plugin, you might have wondered how to make your client feel familiar to users of kubectl. In fact, the Kubernetes project provides two libraries to help you handle kubectl-style command line arguments in Go programs: clientcmd and cli-runtime (which uses clientcmd). This article will show how to use the former.https://kubernetes.io/blog/2026/01/19/clientcmd-apiserver-access
Recently, in our daily operations, we took a deep dive into the inner workings of linkerd-destination, one of the most critical components of the Linkerd control plane.https://medium.com/@bezarsnba/deep-dive-the-linkerd-destination-service-en-19f6efd1b308
If Red Hat trusts OpenShift to run the control plane for their largest infrastructure orchestrator, the same pattern should apply to your smallest.https://hashicorpengineering.substack.com/p/nomad-on-openshift-the-control-plane
How I reduced pod startup times from minutes to seconds with intelligent image preloadinghttps://medium.com/@yyadid7/from-minutes-to-seconds-how-i-eliminated-kubernetes-image-pull-delays-16f166327576
So we built a pipeline that’s intentionally “boring”: GitHub pull requests, GitHub Actions, Kubernetes, and Argo CD — split across staging and production. This post is a walkthrough of how a feature goes from a developer’s machine to real users, and why we made the choices we did.https://medium.com/openmirai/from-push-to-production-our-deployment-pipeline-with-argo-cd-00e55b3feee9
Argo CD Diff Preview is a tool that renders the diff between two branches in a Git repository. It is designed to render manifests generated by Argo CD, providing a clear and concise view of the changes between two branches. It operates similarly to Atlantis for Terraform, creating a plan that outlines the proposed changes.https://github.com/dag-andersen/argocd-diff-preview
A lightweight, extensible Kubernetes Operator that probes any endpoint—HTTP/JSON, TCP, DNS, ICMP, Trino, OpenSearch, and more—and routes alerts to Slack or e-mail with a simple Custom Resource.https://github.com/iam404/endpoint-monitoring-operator
Netfence runs as a daemon on your VM/container hosts and automatically injects eBPF filter programs into cgroups and network interfaces, with a built-in DNS server that resolves allowed domains and populates the IP allowlist.https://github.com/danthegoodman1/netfence
This blog aims to provide a practical example of how core tools like Kubernetes, Terraform, and DevContainers can be combined to build a local data platform in a structured and maintainable way.https://blog.dataengineerthings.org/building-a-local-data-platform-with-kubernetes-and-terraform-9547a4256a7f
Jenkins might feel like legacy tech, but it's still powering CI/CD at thousands of companies. Instead of ripping it out, here's how to modernize it with Kubernetes — solving cost tracking, resource isolation, and scalability problems along the way.https://blog.stackademic.com/modernizing-jenkins-from-static-agents-to-kubernetes-dynamic-pods-fbda3f897018
This article explains how Cosign, Kyverno, and Harbor can work together to enforce image signature verification in Kubernetes. The approach is well-suited for enterprise environments with private registries, custom TLS certificates, and restricted access to public transparency logs.https://medium.com/@hansakabiyon99/enforcing-signed-container-images-in-kubernetes-using-cosign-kyverno-helm-based-setup-646209ecb8ce
Operators make life easier, but they are not always an option. In this post, I'll walk through a practical way to deploy large language models on OpenShift without relying on the OpenShift AI or NVIDIA operators. The approach uses llama.cpp as a lightweight runtime engine and runs a quantized GGUF model to enable efficient inference with minimal dependencies.https://medium.com/@ahmeddraz/deploy-llm-models-on-openshift-84ecb014f09a
This article is about the patterns that actually work when you're managing real databases in Kubernetes, not hello-world demos: when your boss says "everything should be containerized" but your databases laugh in the face of ephemeral pods, and when GitOps meets a 200GB production database that absolutely cannot lose a single transaction.https://medium.com/@firaassboui/database-state-management-in-kubernetes-running-sql-server-on-aks-with-gitops-69286a87f8de
The Kubernetes story is one I hear often. Teams adopt K8s expecting operational simplicity, only to discover they've traded application complexity for infrastructure complexity. For a solo founder focused on content creation, maintaining a Kubernetes cluster was simply the wrong trade-off.https://dev.to/aws-builders/case-study-reducing-complexity-by-migrating-from-k8s-to-ecs-fargate-for-networklessons-3271
If you're running PostgreSQL on Kubernetes, chances are you've used Bitnami's popular Helm charts. They've been a go-to for many, but a significant change is on the horizon. As outlined in this GitHub issue, Bitnami is moving its production-ready charts and images to a commercial offering. For those of us who rely on and advocate for open-source solutions, this means it's time to find a robust alternative.https://k8scockpit.tech/posts/cloudnative-pg
