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DevOps & SRE notes

DevOps & SRE notes

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Helpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19

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πŸ“ˆ Analytical overview of Telegram channel DevOps & SRE notes

Channel DevOps & SRE notes (@devops_sre_notes) in the English language segment is an active participant. Currently, the community unites 12 689 subscribers, ranking 10 003 in the Technologies & Applications category and 2 952 in the USA region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 12 689 subscribers.

According to the latest data from 18 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 238 over the last 30 days and by -1 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 15.17%. Within the first 24 hours after publication, content typically collects 4.62% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 925 views. Within the first day, a publication typically gains 587 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
  • Thematic interests: Content is focused on key topics such as kubernete, cluster, author, engineering, monitoring.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œHelpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19”

Thanks to the high frequency of updates (latest data received on 19 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.

12 689
Subscribers
-124 hours
+357 days
+23830 days
Posts Archive
Helmwave is helm3-native tool for deploy your Helm Charts. HelmWave is like docker-compose for helm. https://github.com/helmwave/helmwave

Comparison managed and self hosted ci/cd https://dzone.com/articles/managed-vs-self-hosted-cicd

Instant K8s service dependency map, right to your Grafana. https://github.com/groundcover-com/caretta

Good article about securing your pipelines https://dzone.com/articles/securing-your-cicd-pipeline

Test all the CloudFormation things! (with TaskCat) https://github.com/aws-ia/taskcat

Interesting article about memory for containers https://blog.devgenius.io/k8s-container-memory-87c6a2a98bef

An a half hour video about creating own k8s operator https://www.youtube.com/watch?v=FHjLL5e7h00

Discounts for linux foundation exams and bundles Save up to 50% Invest in Yourself & Take Home Best in Class Awards ⚠️ Offer ends February 28 https://training.linuxfoundation.org/february-2023

Github actions become more and more popular, there is a good article about autoscaling them https://dgraph.io/blog/post/20230217_dynamic-autoscaling-of-github-runners/

100 questions about k8s - helpful for passing interview and certification. https://medium.com/@AceTheCloud-Abhishek/the-kubernetes-handbook-a-comprehensive-guide-of-100-q-a-e680199e6e22

In this post, you’ll learn how Kubernetes CPU limits and throttling work, including the core concepts, uses, how to assign resources to containers and pods, and how to troubleshoot issues. https://www.containiq.com/post/kubernetes-cpu-limits-and-throttling

If you manage a selfhosted k8s and have a question about storage this article will be helpful https://refaktory.net/blog/posts/self-hosted-kubernetes-solving-the-storage-problem

KSOPS - A Flexible Kustomize Plugin for SOPS Encrypted Resources https://github.com/viaduct-ai/kustomize-sops

If you have a ML microservices, it's article can help with their scaling https://semaphoreci.com/blog/machine-learning-microservice