DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Mostrar más📈 Análisis del canal de Telegram DevOps&SRE Library
El canal DevOps&SRE Library (@devopslibrary) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 19 414 suscriptores, ocupando la posición 6 932 en la categoría Tecnologías y Aplicaciones y el puesto 34 727 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 414 suscriptores.
Según los últimos datos del 19 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 123, y en las últimas 24 horas de -3, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 14.85%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.26% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 883 visualizaciones. En el primer día suele acumular 1 409 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
- Intereses temáticos: El contenido se centra en temas clave como kubernete, cluster, infrastructure, storage, configuration.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 20 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
Know enough to be dangerous in 10 minuteshttps://metoro.io/blog/distributed-tracing-whistle-stop-tour
While working on SLOs, SLAs and SLIs I have found that there are only so many ways to aggregate service metrics. I have not yet found somewhere that attempts to review the different aggregation methods and what their relative strengths and weaknesses are.https://hross.substack.com/p/different-ways-to-aggregate-nines
Everyone experiences stress at work—thankfully, it’s a topic folks aren’t shying away from anymore. But for on-call engineers, alert fatigue is a phenomenon closer to home. Unfortunately, like stress, it can be just as insidious and drastically impact those it affects. First discussed in the context of hospital settings, this phrase later entered engineering circles. Alert fatigue is when an excessive number of alerts overwhelms the individuals responsible for answering them, often over a prolonged period, resulting in missed or delayed responses, or them being ignored altogether The impact of this fatigue can have an effect beyond the individual and can create significant risks for your organization. But, if you approach on-call the right way, you can mitigate the impacts of alert fatigue or, better yet, avoid it altogether. Here, we'll dive into the tactics teams can implement to address alert fatigue and its underlying causes.https://incident.io/hubs/on-call/dealing-with-alert-fatigue-head-on
Introduction to the SLA in relation to SLI and SLOhttps://blog.alexewerlof.com/p/sla
Core principles of documentation-as-code tools - Treating documentation with the same rigor as code - Storing documentation in version control - Automation of documentation generation and deployment - Peer review processes for documentation updateshttps://www.tabnine.com/blog/documentation-as-code-principles-workflow-and-challenges
A key challenge of monitoring your CI/CD system is understanding how to optimize your workflows and create best practices that help you minimize pipeline slowdowns and better respond to CI issues. In addition to monitoring CI pipelines and their underlying infrastructure, your organization also needs to cultivate effective relationships between platform and development teams. Fostering collaboration between these two teams is a critical and equally valuable aspect of improving the reliability and performance of your CI. In this post, we’ll explore how platform teams can help developers visualize trends in CI test performance and notify them of new flaky tests, test failures, and performance regressions with dashboards and monitors. We’ll also detail best practices that can help developers identify, investigate, and remediate flaky tests.https://www.datadoghq.com/blog/best-practices-for-monitoring-software-testing
Kubernetes has been a great orchestrator of Jobs and CronJobs for over half a decade now, but if you had a need for running proxy containers or other secondary containers alongside the job, running things properly took a bit of work and decision-making to handle gracefully. This article introduces the easiest way to run Jobs with sidecars using the latest Kubernetes features, and has a complementary repository with complete example manifests you can try in your own cluster. The repository contains all the examples for earlier versions of K8s as well, so make sure to focus on the cronjob.sidecar.*.yaml examples.https://medium.com/teamsnap-engineering/properly-running-kubernetes-jobs-with-sidecars-in-2024-k8s-1-28-ad9b51d17d50
Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication features. Garnet can work with existing Redis clients.https://github.com/microsoft/garnet
Our nine month journey to horizontally shard Figma’s Postgres stack, and the key to unlocking (nearly) infinite scalability. Figma’s database stack has grown almost 100x since 2020. This is a good problem to have because it means our business is expanding, but it also poses some tricky technical challenges. Over the past four years, we’ve made a significant effort to stay ahead of the curve and avoid potential growing pains. In 2020, we were running a single Postgres database hosted on AWS’s largest physical instance, and by the end of 2022, we had built out a distributed architecture with caching, read replicas, and a dozen vertically partitioned databases. We split groups of related tables—like “Figma files” or “Organizations”—into their own vertical partitions, which allowed us to make incremental scaling gains and maintain enough runway to stay ahead of our growth.https://www.figma.com/blog/how-figmas-databases-team-lived-to-tell-the-scale
An open source virtual hand-drawn style whiteboard.https://github.com/excalidraw/excalidraw
GritQL is a declarative query language for searching and modifying source code.https://github.com/getgrit/gritql
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