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 19 758 suscriptores, ocupando la posición 6 527 en la categoría Tecnologías y Aplicaciones y el puesto 33 399 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 758 suscriptores.
Según los últimos datos del 27 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 137, y en las últimas 24 horas de 7, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 14.01%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.00% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 768 visualizaciones. En el primer día suele acumular 1 382 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
- 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 28 agosto, 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.
Hunk is a review-first terminal diff viewer for agent-authored changesets, built on OpenTUI and Pierre diffs.https://github.com/modem-dev/hunk
A single, opinionated Helm chart for deploying any Kubernetes application workload. Instead of maintaining separate charts per application, define your entire deployment through values.https://github.com/cotzo/chartpack
Kubebuilder is a framework for building Kubernetes APIs using custom resource definitions (CRDs).https://github.com/kubernetes-sigs/kubebuilder
Zero-code log sanitization sidecar for Kubernetes. Prevents data leaks (GDPR/SOC2) by redacting PII from logs before they leave the pod.https://github.com/aragossa/pii-shield
Sometimes, you just want to run a Large Language Model (LLM)… no Jupyter notebook, no training pipeline, no fancy UI.https://pittar.medium.com/llms-on-kubernetes-the-easy-way-f1ff6e0d47be
How we went from scaling video analysis on EKS to running autonomous coding agents in a custom agent harness, and why Kubernetes was the obvious choice.https://dev.to/mattcamp/orchestrating-secure-ai-agents-on-amazon-eks-50kh
Most Kubernetes teams track pod CPU and memory. Almost none track what the cluster actually costs to run.https://blog.kubeledger.io/what-6-months-of-tracking-a-production-openshift-cluster-revealed-about-kubernetes-costs
A practical guide to GKE deployment, Cassandra backups, Istio security, and surviving your first outagehttps://medium.com/@devansh2054/running-temporal-io-on-kubernetes-in-production-what-nobody-tells-you-d1f336e99306
If you've ever stared at `ImagePullBackOff` in your cluster at 2 PM on a Tuesday, you know — Docker Hub rate limits hit, your pods can't pull, and a perfectly fine deployment is stuck.https://tinysystems.io/blog/registry-mirror-automation
I have been recommending pgBackRest as the best backup tool for PostgreSQL for years.https://mydbanotebook.org/posts/pgbackrest-is-dead.-now-what
Waffle is a CLI utility that automates AWS Well-Architected Framework Reviews by analyzing Terraform infrastructure using Amazon Bedrock foundation models via direct API invocation in AWS. The Well-Architected Framework questions are then being analyzed by Amazon Bedrock and answered and posted directly to the Well-Architected tool in AWS.https://github.com/partly-notes/waffle
The more I look at how we actually build systems now, the more it looks like Terraform is dead.https://grahamgilbert.com/blog/2026/04/20/terraform-is-dead
A simple command line SSH tunnel manager that just works.https://github.com/alebeck/boring
This is the story of why and how we built PGKeeper, a scalable and reliable service to support Figma’s rapidly growing products and database workload.https://www.figma.com/blog/pgkeeper-building-the-bouncer-we-needed-for-postgres
deepsec an agent-powered vulnerability scanner that you can run in your own infrastructure, optimized to perform on-demand review of all code in existing large-scale repos.https://github.com/vercel-labs/deepsec
honker is a SQLite extension + language bindings that add Postgres-style NOTIFY/LISTEN semantics to SQLite, with built-in durable pub/sub, task queue, and event streams, without client polling or a daemon/broker. Any language that can SELECT load_extension('honker') gets the same features.https://github.com/russellromney/honker
When you're running a system that processes hundreds of thousands of compaction jobs, even small inaccuracies in memory usage estimates compound into real operational pain.https://mixpanel.substack.com/p/how-we-reduced-median-memory-estimation
