DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Больше📈 Аналитический обзор Telegram-канала DevOps&SRE Library
Канал DevOps&SRE Library (@devopslibrary) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 19 416 подписчиков, занимая 6 942 место в категории Технологии и приложения и 34 783 место в регионе Россия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 19 416 подписчиков.
Согласно последним данным от 13 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 171, а за последние 24 часа — 9, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 14.76%. В первые 24 часа после публикации контент обычно набирает 7.06% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 866 просмотров. В течение первых суток публикация набирает 1 371 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 1.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как kubernete, cluster, infrastructure, storage, configuration.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Благодаря высокой частоте обновлений (последние данные получены 14 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
Cardamon is a metric auditor for Prometheus. It identifies metrics that exist in your TSDB but are never actually queried by dashboards, alerting rules, recording rules, or any other consumer. You can then generate Prometheus drop rules to remove them and reduce storage need.https://github.com/dominikhei/cardamon
Log analytics in a single binary. No dependencies. Lynx Flow query language.https://github.com/lynxbase/lynxdb
Traceway is a self-hosted observability platform that ingests OpenTelemetry traces and metrics, groups exceptions automatically, and gives you endpoint performance, distributed tracing, and alerts — all in a single binary. No OTel Collector or separate time-series database required.https://github.com/tracewayapp/traceway
As part of an ongoing series, the Developer Experience SIG interviews organizations about their real-world OpenTelemetry Collector deployments to share practical lessons with the broader community. This post features Adobe, a global software company whose observability team has built an OpenTelemetry-based telemetry pipeline designed for simplicity at massive scale, with thousands of collectors running per signal type across the company’s infrastructure.https://opentelemetry.io/blog/2026/devex-adobe
Exports helm release, chart, and version statistics in the prometheus format.https://github.com/sstarcher/helm-exporter
The open-source, datacenter-scale inference stack. Dynamo is the orchestration layer above inference engines — it doesn't replace SGLang, TensorRT-LLM, or vLLM, it turns them into a coordinated multi-node inference system. Disaggregated serving, intelligent routing, multi-tier KV caching, and automatic scaling work together to maximize throughput and minimize latency for LLM, reasoning, multimodal, and video generation workloads.https://github.com/ai-dynamo/dynamo
This article explains how to use the In-Place Pod Resize feature in Kubernetes, combined with Kube Startup CPU Boost, to speed up Java application startup.https://piotrminkowski.com/2025/12/22/startup-cpu-boost-in-kubernetes-with-in-place-pod-resize/
This is a story about a tricky issue I resolved recently.https://dev.to/datton94/how-my-client-hit-linux-kernel-network-limits-on-aws-eks-3am5
More and more enterprises want the benefits of AI-assisted coding, automatic completions, suggestions, and inline generation, without sending their source code to external APIs. This has naturally increased interest in self-hosted coding assistants, where all inference runs on internal hardware and all models stay inside a controlled environment. We built a complete prototype of such a system. In this article, we walk through its architecture, explain how Kubernetes is used to deploy it, and how different system parameters interact to determine real-world performance. In a separate post, we study how the llama.cpp inference server behaves under increasing load.https://medium.com/@ferraricorneloup.teo/inside-a-self-hosted-ai-coding-assistant-architecture-kubernetes-deployment-and-llama-cpp-158330a12441
A personal knowledge base that turns markdown notes into a semantically-connected, AI-augmented knowledge graph. Atomic stores knowledge as atoms — markdown notes that are automatically chunked, embedded, tagged, and linked by semantic similarity. Your atoms can be synthesized into wiki articles, explored on a spatial canvas, and queried through an agentic chat interface.https://github.com/kenforthewin/atomic
Run multiple agents in parallel — each in its own container, with its own workspace, collaborating on your code or project files simultaneously.https://github.com/GoogleCloudPlatform/scion
A lightweight, single-binary OpenTelemetry viewer for local development. Visualize traces, logs, and metrics from your instrumented applications — no Docker, no databases, no complex setup.https://github.com/mesaglio/otel-front
DriftHound is a Rails WebApp that receives Terraform drift reports via API and provides visibility into infrastructure drift across your projects.https://github.com/drifthoundhq/drifthound
After successfully adopting Terraform for GitHub repository management, the next step in our Infrastructure as Code (IaC) journey was clear: dogfood our own product and manage our domains and DNS zones using the DNSimple Terraform provider.https://blog.dnsimple.com/2025/11/managing-domains-terraform-dnsimple
After a few years of writing open-source Terraform modules, I've picked up a few syntax tricks that make code safer, cleaner, and easier to maintain.https://rosesecurity.dev/2025/12/04/terraform-tips-and-tricks.html
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