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 19 869 suscriptores, ocupando la posición 6 592 en la categoría Tecnologías y Aplicaciones y el puesto 33 047 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 869 suscriptores.
Según los últimos datos del 05 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -13, y en las últimas 24 horas de 11, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 13.00%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 6.56% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 583 visualizaciones. En el primer día suele acumular 1 303 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 06 noviembre, 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.
KubeAdmiral is a multi-cluster management system for Kubernetes, developed from Kubernetes Federation v2. Kubernetes Federation v2 allows users to manage Kubernetes resources across multiple clusters through the use of federated types such as FederatedDeployment, FederatedReplicaSet, FederatedSecret, etc. KubeAdmiral extends the Kubernetes Federation v2 API, providing compatibility with the Kubernetes native API and more powerful resource management capabilities.https://github.com/kubewharf/kubeadmiral
*This article is for Terraform heavy users, who manage complex infrastructures.https://medium.com/@maximonyshchenko/the-secret-to-terraform-efficiency-a76140a5dfa1
At incident.io, we run an on-call product. Our customers need to be sure that when their systems go wrong, we’ll tell them about it—high availability is a core requirement for us. To achieve the level of reliability that’s essential to our customers, excellent observability (o11y) is one of the most important tools in our belt.https://incident.io/hubs/building-on-call/building-on-call-our-observability-strategy
We recently migrated all of our infrastructure metrics from StatsD to Prometheus and are very pleased with the results. The migration was a ton of work and we learned a lot along the way. This post aims to shed some light on why we migrated to Prometheus, as well as outline some of the technical challenges we faced during the process.https://engineering.mixpanel.com/how-we-migrated-from-statsd-to-prometheus-in-one-month-fb973af124f5
KubeVirt is a virtual machine management add-on for Kubernetes. The aim is to provide a common ground for virtualization solutions on top of Kubernetes.https://github.com/kubevirt/kubevirt
Are you considering migrating your PostgreSQL database from a service provider into Kubernetes, but you cannot afford downtime? Recipe #5 details step-by-step instructions, leveraging CloudNativePG and logical replication, to seamlessly transition from PostgreSQL 10+ to 16 using an imperative method. Learn how to set up initial configurations, execute migrations, and handle various use cases, such as transitioning from DBaaS to Kubernetes-managed databases and performing version upgrades. Emphasizing testing, learning, and compliance with regulations like the Data Act, this guide empowers users to maintain control over their data by migrating to Kubernetes.https://www.gabrielebartolini.it/articles/2024/03/cloudnativepg-recipe-5-how-to-migrate-your-postgresql-database-in-kubernetes-with-~0-downtime-from-anywhere
TLDR: Running Kubernetes on Hetzner offers cost-effective options, but handling production workloads, especially stateful ones like databases, raises concerns. Hetzner provides instance and cloud volume storage options with significant differences in IOPS performance. Longhorn, a distributed block storage system, can be used to leverage local volumes, but benchmarks show a slowdown compared to raw local files. Probably host a datatbase either on a dedicated host or use a hosted option instead.https://sveneliasson.de/benchmarking-hetzners-storage-classes-for-database-workloads-on-kubernetes
Balancing traffic across multiple Kubernetes clusters and achieving automatic disaster recovery switching has always been a headache. We have explored public clouds and Karmada Ingress, and have also tried manual DNS solutions, but these approaches often fell short in terms of cost, universality, flexibility, and automation. It was not until we discovered k8gb, a project initiated by South Africa’s Absa Group to provide banking-level multi-availability, that we realized the ingenuity of using various DNS protocols to deliver a universal and highly automated GSLB solution. This blog will briefly discuss the problems with other approaches and how k8gb cleverly uses DNS to implement GSLB.https://oilbeater.com/en/2024/04/18/k8gb-best-cloudnative-gslb
It’s possible to dynamically resize CPU on containers in k8s with the feature gate “InPlacePodVerticalScaling”. Before this feature gate, sizing CPU was error prone and, in reality, we would often put something too high, to not deal with latency. Too much CPU and precious resources are wasted, too few CPU and the app is slowed. Let’s explore the ways to dynamically resize CPU.https://medium.com/@mathieuces/how-to-calculate-cpu-for-containers-in-k8s-dynamically-47a89e3886eb
