Available now! Telegram Research 2025 — the year's key insights 
DevOps&SRE Library
Open in Telegram
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 19 410 subscribers, ranking 6 891 in the Technologies & Applications category and 34 582 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 19 410 subscribers.
According to the latest data from 26 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 64 over the last 30 days and by 9 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 14.66%. Within the first 24 hours after publication, content typically collects 7.20% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 844 views. Within the first day, a publication typically gains 1 397 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 27 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.
19 410
Subscribers
+924 hours
-127 days
+6430 days
Posts Archive
19 416
Kubernetes Storage Classes | In-Depth Tutorial
Storage Classes are an essential part of Kubernetes, and can provide a great deal of flexibility and control over how your data is stored. In this guide, we provide an in-depth tutorial on using storage classes effectively.https://www.containiq.com/post/kubernetes-storage-classes
19 416
Kubernetes Audit Logs - Best Practices And Configuration
https://signoz.io/blog/kubernetes-audit-logs
19 416
PushProx
PushProx is a client and proxy that allows transversing of NAT and other similar network topologies by Prometheus, while still following the pull model.https://github.com/prometheus-community/PushProx
19 416
Kubernetes Controllers, Custom Resources, and Operators Explained
https://faun.pub/kubernetes-controllers-custom-resources-and-operators-explained-8e92f46829f6
19 416
badrobot
Badrobot is a Kubernetes Operator audit tool. It statically analyses manifests for high risk configurations such as lack of security restrictions on the deployed controller and the permissions of an associated clusterole. The risk analysis is primarily focussed on the likelihood that a compromised Operator would be able to obtain full cluster permissions.https://github.com/controlplaneio/badrobot
19 416
Autoscale large images faster using Longhorn (distributed storage)
https://aesher9o1.medium.com/autoscale-large-images-faster-using-longhorn-distributed-storage-618d0cf01ba2
19 416
signoz
Monitor your applications and troubleshoot problems in your deployed applications, an open-source alternative to DataDog, New Relic, etc.https://github.com/signoz/signoz
19 416
So you need to wait for some Kubernetes resources?
https://vadosware.io/post/so-you-need-to-wait-for-some-kubernetes-resources
19 416
konf-go
konf is a lightweight kubeconfig manager. With konf you can use different kubeconfigs at the same time. And because it does not need subshells, konf is blazing fast!https://github.com/simontheleg/konf-go
19 416
Halving Kubernetes Compute Costs With Vertical Pod Autoscaler
https://medium.com/compass-true-north/halving-kubernetes-compute-costs-with-vertical-pod-autoscaler-df658c043301
19 416
🔥 6 причин начать внедрять DevSecOps:🔥
1. Проактивная интеграция информационной безопасности на всех этапах разработки.
2. Снижение вероятности выпуска в продакшен уязвимого продукта.
3. Повышение престижности компании и продукта.
4. Снижение времени внедрения новых возможностей.
5. Повышение квалификации сотрудников в области ИБ.
6. Вероятное введение оборотных штрафов в 2023 году за утечки персональных данных.
⁉️Где можно освоить DevSecOps подход? На онлайн-курсе «Внедрение и работа в DevSecOps» от OTUS.
👉 Пройдите тест на знание подхода DevSecOps: https://otus.pw/Roqh/
Сможете пройти успешно тест — пройдёте на курс «Внедрение и работа в DevSecOps» по специальной цене.
🎄 Сейчас действуют новогодние скидки! Возможна оплата в рассрочку!
19 416
dumb-init
dumb-init is a simple process supervisor and init system designed to run as PID 1 inside minimal container environments (such as Docker). It is deployed as a small, statically-linked binary written in C.https://github.com/yelp/dumb-init
19 416
kube-no-trouble
Easily check your clusters for use of deprecated APIshttps://github.com/doitintl/kube-no-trouble
19 416
Google Cloud: Best practices for using Terraform
https://cloud.google.com/docs/terraform/best-practices-for-terraform
19 416
Reloader
A Kubernetes controller to watch changes in ConfigMap and Secrets and do rolling upgrades on Pods with their associated Deployment, StatefulSet, DaemonSet and DeploymentConfighttps://github.com/stakater/Reloader
19 416
Anatomy of an Incident
Google’s Approach to Incident Management for Production Services
Ayelet Sachto and Adrienne Walcer, with Jessie Yang
2022
19 416
acorn
A simple application deployment framework for Kubernetes.https://github.com/acorn-io/acorn
19 416
predictive-horizontal-pod-autoscaler
Predictive Horizontal Pod Autoscalers (PHPAs) are Horizontal Pod Autoscalers (HPAs) with extra predictive capabilities baked in, allowing you to apply statistical models to the results of HPA calculations to make proactive scaling decisions.https://github.com/jthomperoo/predictive-horizontal-pod-autoscaler
19 416
Write Your Kubernetes Infrastructure as Go Code — Getting Started With Cdk8s
https://betterprogramming.pub/write-your-kubernetes-infrastructure-as-go-code-getting-started-with-cdk8s-989725f8af73
