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 19 415 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 19 415 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.
We're excited to share a new experimental feature for Platformatic: Skew Protection in the Intelligent Command Center (ICC). This brings Vercel-style deployment safety to Kubernetes, letting you deploy without downtime and avoid version-mismatch problems.https://blog.platformatic.dev/skew-protection-for-kubernetes
Why we moved capacity engineering into CI and started gating on prefix-cache efficiencyhttps://medium.com/@nroan/autoscaling-hid-our-llm-cost-regression-85-4-cache-hit-rate-b4beab5df240
Most LLM-generated SQL doesn't fail. It runs and returns results, and that's exactly what makes it dangerous. The errors don't surface until they're already in your data.https://readyset.io/blog/why-llms-write-incorrect-sql-and-what-that-means-for-your-database
In the three years since our first Live show, Chris Rock: Selective Outrage, we have witnessed an incredible expansion of our live content slate and the live operations that support it. From modest beginnings of streaming just one show per month, we are now capable of streaming over nine shows in a single day, reaching tens of millions of concurrent members. This post pulls back the curtain on the Live Operations teams that enable this rapid scale.https://netflixtechblog.com/the-human-infrastructure-how-netflix-built-the-operations-layer-behind-live-at-scale-33e2a311c597
CodeBurn tracks token usage, cost, and performance across 19 AI coding tools. It breaks down spending by task type, model, tool, project, and provider so you can see exactly where your budget goes.https://github.com/getagentseal/codeburn
openhare is an AI-powered, cross-platform desktop SQL client with multi-database support, built for everyday development, data analysis, and DBA management workflows.https://github.com/sjjian/openhare
Eraser helps Kubernetes admins remove a list of non-running images from all Kubernetes nodes in a cluster.https://github.com/eraser-dev/eraser
SREcon Chair Heinrich Hartmann on why the age of AI-assisted engineering demands a radical return to design rigor.https://www.runllm.com/blog/i-dont-care-if-ai-wrote-the-code-you-own-it
For many organizations, some form of blamelessness has become a more standard practice and blame-awareness has been gaining in popularity. However, there is an anti-pattern I have noticed as well, which I like to call superficial (or shallow) blamelessness that I think is important for people to be on the lookout for.https://resilienceinsoftware.org/news/11502437
Hunk is a review-first terminal diff viewer for agent-authored changesets, built on OpenTUI and Pierre diffs.https://github.com/modem-dev/hunk
A single, opinionated Helm chart for deploying any Kubernetes application workload. Instead of maintaining separate charts per application, define your entire deployment through values.https://github.com/cotzo/chartpack
Kubebuilder is a framework for building Kubernetes APIs using custom resource definitions (CRDs).https://github.com/kubernetes-sigs/kubebuilder
Zero-code log sanitization sidecar for Kubernetes. Prevents data leaks (GDPR/SOC2) by redacting PII from logs before they leave the pod.https://github.com/aragossa/pii-shield
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