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 19 760 suscriptores, ocupando la posición 6 512 en la categoría Tecnologías y Aplicaciones y el puesto 33 334 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 760 suscriptores.
Según los últimos datos del 30 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 135, y en las últimas 24 horas de 1, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 13.71%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 6.94% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 709 visualizaciones. En el primer día suele acumular 1 372 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 31 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.
There are books & many articles online, like this one arguing for using Postgres for everything. I thought I’d take a look at one use case - using Postgres instead of Redis for caching. I work with APIs quite a bit, so I’d build a super simple HTTP server that responds with data from that cache. I’d start from Redis as this is something I frequently encounter at work, switch it out to Postgres using unlogged tables and see if there’s a difference.https://dizzy.zone/2025/09/24/Redis-is-fast-Ill-cache-in-Postgres/
This interactive article allows you to build an understanding of what Processes are, how they allow your computer to multitask, and how they differ from Threads.https://planetscale.com/blog/processes-and-threads
rk8s is a lightweight, Kubernetes-compatible container orchestration system built on top of Youki, implementing the Container Runtime Interface (CRI) with support for three primary workload types: single containers, Kubernetes-style pods, and Docker Compose-style multi-container applications.https://github.com/rk8s-dev/rk8s
Set kubectl contexts/namespaces per shell/terminal to manage multi Kubernetes clusters at the same time, like kubectx/kubens but per shell/terminal.https://github.com/DevOpsHiveHQ/kubech
Реклама. ООО «Отус онлайн-образование», ОГРН 1177746618576, erid: 2Vtzqvv2r6yMany, many pixels have been burned on the topic of sidecars of late. If you’ve been paying any attention at all to the cloud-native ecosystem, you’ve doubtless run across discussions about the merits - or lack thereof - of sidecars. In a lot of ways, this is kind of silly: sidecars are a fairly low-level implementation pattern, and it would probably make sense to see them considered an implementation detail rather than the latest hot marketing topic. In other ways, though, we live in an imperfect world and we often do have to pull back the curtains to take a look at the technology underneath the tools we use: understanding the tradeoffs made by our tool choices is often critical to getting the most out of those tools, and architectural decisions are always about tradeoffs. For various reasons, I ended up being the one to take on the job of pulling back the curtain on both Linkerd’s choice to use the sidecar pattern and Istio Ambient’s choice to avoid it, and look into the ramifications of those choices. I did this in the obvious way: I ran both meshes under load and measured things about them. It was simultaneously frustrating and fascinating, often in surprising ways.https://linkerd.io/2025/05/21/behind-the-great-sidecar-debate/index.html
kubectl get <resource> -n <namespace> -o yaml \
| kubectl-neat \
| yq eval '.items[] | split_doc' - > resources.yaml
kubectl apply -f resources.yaml
2⃣ kubedump
Автоматизирует сохранение/восстановление по проектам:
kubedump dump <namespace> --resources <resource> --project <project-name>
kubedump restore --project <project-name>
Что выбрать?
— kubectl-neat + yq: лёгкий, гибкий, для разовых задач.
— kubedump: для регулярных бэкапов и больших кластеров.
Бонус:
➡ Лимиты ресурсов в Kubernetes
➡ Как настроить basicAuth в Traefik
➡ Больше лайфхаков и практичных утилит для инженеров DevOps — в CORTEL
Реклама ООО "Кортэл"
ИНН: 7816246925From Utilization Confusion to PSI Clarity in Kuberneteshttps://blog.zmalik.dev/p/from-utilization-to-psi-rethinking
Flagr is an open source Go service that delivers the right experience to the right entity and monitors the impact. It provides feature flags, experimentation (A/B testing), and dynamic configuration. It has clear swagger REST APIs for flags management and flag evaluation.https://github.com/openflagr/flagr
OCI registry client - managing content like artifacts, images, packageshttps://github.com/oras-project/oras
Mantis is a next-generation Infrastructure as Code (IaC) tool that reimagines how we manage cloud and Kubernetes resources. Built as a fork of OpenTofu and powered by CUE, Mantis combines the best of Terraform and Helm while solving their limitations. To manage cloud resources, Mantis compiles CUE configurations into Terraform compatible json and leverages the Opentofu engine to orchestrate it. To manage K8s resources, Mantis compiles CUE configurations yaml manifests which can be deployed either using mantis or via integrations with Gitops tools like ArgoCD or FluxCDhttps://github.com/augur-ai/mantis
