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 19 420 suscriptores, ocupando la posición 6 935 en la categoría Tecnologías y Aplicaciones y el puesto 34 746 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 420 suscriptores.
Según los últimos datos del 16 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 151, y en las últimas 24 horas de -4, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 15.05%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.12% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 923 visualizaciones. En el primer día suele acumular 1 383 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 17 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.
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
A tool to easily tail Kubernetes container logshttps://github.com/atombender/ktail
Curated List of Kubernetes Toolshttps://github.com/collabnix/kubetools
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
Additional Networks on Kubernetes using Multus CNI.https://medium.datadriveninvestor.com/can-a-kubernetes-pod-have-more-than-one-network-attached-6d78456dbeb2
Understanding Terraform Variable Precedence: Which Value Wins?https://towardsaws.com/mastering-terraform-understanding-variable-precedence-for-optimal-configuration-control-59c98dcd1505
Реклама. ООО «Отус онлайн-образование», ОГРН 1177746618576, erid: 2VtzqwFfAuVThe CNCF candidate for observability visualisation.https://github.com/perses/perses
Recently, I was tasked with analyzing cross-AZ traffic in Kubernetes to identify opportunities for reduction, as it is a significant contributor to our AWS bill. The first step was to understand how traffic flows between services and what portion consistently crosses Availability Zones (AZs). To optimize cross-AZ traffic, I considered using topology-aware routing for services. However, before implementing this solution, I needed a method to effectively analyze inter-pod traffic at the AZ level. To achieve this, monitoring network traffic at the pod level is necessary. I decided to use eBPF (Extended Berkeley Packet Filter) technology, as it allows us to observe network interactions with minimal performance overhead. In this article, I will explain what eBPF is, explore the tools available for using it, and provide a step-by-step guide on implementing monitoring for inter-pod traffic using Retina, Kube State Metrics, Prometheus, and Grafana.https://medium.com/@j.aslanov94/monitoring-inter-pod-traffic-at-the-az-level-with-ebpf-based-tool-retina-7a79818e305b
Master Terraform modules for Azure infrastructure management. Learn to create, use, and optimize modules, build a multi-tier application, and implement best practices for large-scale projects. Ideal for DevOps engineers and cloud architects looking to enhance their Infrastructure as Code skills on Azure.https://www.iamachs.com/p/azure-terraform/part-7-modules-grand-finale
¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
