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 19 389 subscribers, ranking 6 921 in the Technologies & Applications category and 34 722 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 19 389 subscribers.
According to the latest data from 22 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 81 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 14.62%. Within the first 24 hours after publication, content typically collects 7.25% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 837 views. Within the first day, a publication typically gains 1 407 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 23 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.
- Consulting - Embedded - Infra Teamhttps://certomodo.substack.com/p/sre-engagement-models
tfvar is a Terraform's variable definitions template generator. It scans your Terraform configurations or modules and extracts the variables into formats of your choice for editing, e.g., tfvar, environment variables, etc.https://github.com/shihanng/tfvar
This is an implementation of the Terraform registry protocol used to host a private Terraform registry.https://github.com/nrkno/terraform-registry
Terragrunt alternative to keep your Terraform code consistent and DRYhttps://github.com/refl3ction/tfgen
Leveraging Terraform to automate the setup and configuration of SSO resources, streamline user management, and enhance security.https://medium.com/cloud-native-daily/automate-aws-sso-using-terraform-2f219a45c16f
We investigated Crossplane at a deep level and found it wasn't for us. Read on to learn about our investigation and the issues we found.https://masterpoint.io/updates/passing-on-crossplane
TL:DR At Spotify, we run containerized workloads in production across our entire organization in five regions where our main production workloads are in Google Kubernetes Engine (GKE) on Google Cloud Platform (GCP). If we detect suspicious behavior in our workloads, we need to be able to quickly analyze it and determine if something malicious has happened. Today we leverage commercial solutions to monitor them, but we also do our own research to discover options and alternative methods. One such research project led to the discovery of a new method for conducting memory analysis on GKE by combining three open source tools, AVML, dwarf2json, and Volatility 3, the result being a snapshot of all the processes and memory activities on a GKE node. This new method empowers us and other organizations to use an open source alternative if we do not have a commercial solution in place or if we want to compare our current monitoring to the open source one. In this blog post, I’ll explain in detail how memory analysis works and how this new method can be used on any GKE node in production today.https://engineering.atspotify.com/2023/06/analyzing-volatile-memory-on-a-google-kubernetes-engine-node
The Saga pattern is often positioned as a better way to handle distributed transactions. I see no point in discussing Saga's disadvantages because the problem is that Saga should not be used in the microservices at all: If you need distributed transactions across a few microservices, most likely you incorrectly defined and separated domains. Below is a long explanation why.https://dev.to/siy/the-saga-is-antipattern-1354
Command line tool allowing to convert the barely usable output of the terraform graph command to something more meaningful and explanatory.https://github.com/pcasteran/terraform-graph-beautifier
A solution for versioning multiple Terraform module while preserving your Monorepohttps://medium.com/@hello_9187/managing-terraform-modules-in-a-monorepo-e7e89d124d4a
Available now! Telegram Research 2025 — the year's key insights 
