DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Show more📈 Analytical overview of Telegram channel DevOps&SRE Library
Channel DevOps&SRE Library (@devopslibrary) in the English language segment is an active participant. Currently, the community unites 19 420 subscribers, ranking 6 935 in the Technologies & Applications category and 34 746 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 19 420 subscribers.
According to the latest data from 16 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 151 over the last 30 days and by -4 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 15.05%. Within the first 24 hours after publication, content typically collects 7.12% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 923 views. Within the first day, a publication typically gains 1 383 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
- Thematic interests: Content is focused on key topics such as kubernete, cluster, infrastructure, storage, configuration.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Thanks to the high frequency of updates (latest data received on 17 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
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
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