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 19 395 subscribers, ranking 6 952 in the Technologies & Applications category and 34 902 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 19 395 subscribers.
According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 154 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 15.22%. 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 2 949 views. Within the first day, a publication typically gains 1 380 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 11 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.
AI agents are ready to do infrastructure work, but they can't touch prod: - Agents can install packages, configure services, write scripts—autonomously - But one mistake on production and you're getting paged at 3 AM to fix it - So we limit agents to chatbots instead of letting them do the workhttps://github.com/aspectrr/fluid.sh
At Tines, we recently faced a significant engineering challenge: our output_payloads table in PostgreSQL was rapidly approaching 17TB on our largest cloud cluster, with no signs of slowing down. Once a table reaches PostgreSQL’s 32TB table size limit, it will stop accepting writes. This table holds event data, in the form of arbitrary JSON, which is critical to powering Tines workflows. Given the criticality of the data, we couldn’t risk any disruptions to it. As our monitoring showed the table's growth, we began experiencing warning signs. Cleanup jobs on the table had begun to time out. The table was causing increased I/O pressure on our infrastructure, leading us to use more expensive hardware. The arbitrary JSON shape of the data meant massive autovacuum jobs on its TOAST table. When these autovacuums ran, they displaced other tables from the buffer cache, forcing disk reads in critical areas. As a bandaid, we modified the autovacuum parameters of the table so that the autovacuums would run more frequently, but have less tuples to process. With performance slowly degrading, and 32TB looming on the horizon, we knew we needed to act decisively.https://www.tines.com/blog/futureproofing-tines-partitioning-a-17tb-table-in-postgresql
How I manage 100+ infrastructure components across multiple products, environments, and regions without configuration duplicationhttps://devineer.medium.com/managing-terraform-at-scale-a-deep-dive-into-terragrunt-configuration-hierarchy-54f1f16e7c1f
Master the command line, in one pagehttps://github.com/jlevy/the-art-of-command-line
Being an excellent engineer helps you advance through the ranks to become a Staff Engineer; “quiet influence” keeps you there. I’ve learned the hard way that my architectural proposals didn’t fail on technical merits (mostly 😅); they failed because of the social strategy (or lack thereof) I had employed behind them. I’d have a vision on how things were going to be improved, but struggled to recruit others to get behind the idea. After a few painful misses, I started building a toolkit of approaches that actually get big changes through. In this post, I’ll share a technique I use: Nemawashi.https://hodgkins.io/blog/quiet-influence-a-guide-to-nemawashi-in-engineering
This text is for developers that have an intuitive knowledge of what database indexes are, but don’t necessarily know how they work internaly, what are the tradeoffs associated with indexes, what are the types of indexes provided by postgres and how you can use some of its more advanced options to make them more optimized for your use case.https://dlt.github.io/blog/posts/introduction-to-postgresql-indexes
This Ansible collection provides battle tested hardening for Linux, SSH, nginx, MySQLhttps://github.com/dev-sec/ansible-collection-hardening
Zedis is a next-generation Redis GUI client designed for developers who demand speed. Unlike Electron-based clients that can feel sluggish with large datasets, Zedis is built on GPUI (the same rendering engine powering the Zed Editor). This ensures a native, 60 FPS experience with minimal memory footprint, even when browsing millions of keys.https://github.com/vicanso/zedis
An on-device search engine for everything you need to remember. Index your markdown notes, meeting transcripts, documentation, and knowledge bases. Search with keywords or natural language. Ideal for your agentic flows.https://github.com/tobi/qmd
On January 8, 2026, a routine update to 1.1.1.1 aimed at reducing memory usage accidentally triggered a wave of DNS resolution failures for users across the Internet. The root cause wasn't an attack or an outage, but a subtle shift in the order of records within our DNS responses.https://blog.cloudflare.com/cname-a-record-order-dns-standards
The Terraform MCP Server is a Model Context Protocol (MCP) server that provides seamless integration with Terraform Registry APIs, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.https://github.com/hashicorp/terraform-mcp-server
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