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 19 413 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 19 413 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.
A 5 slide formula with some advice.https://hross.substack.com/p/presenting-to-engineering-leadership
mlinfra is the swiss army knife for deploying scalable MLOps infrastructure. It aims to make MLOps infrastructure deployment easy and accessible to all ML teams by liberating IaC logic for creating MLOps stacks which is usually tied to other frameworks.https://github.com/mlinfra-io/mlinfra
Symphony is a framework and set of patterns and best practices for developing, testing, and deploying infrastructure on Azure using Infrastructure as Code (IAC.) It includes modern DevOps practices for IAC such as Main and Pull Request workflows, IaC Code Validation & Linting, Automated Testing, Security Scanning, Multi-environment deployments, modules dependencies and more.https://github.com/microsoft/symphony
As DoorDash experienced rapid growth over the last few years, we began to see the limits of our traditional methods of monitoring. Metrics, logs, and traces provide vital information about our service ecosystem. But these signals almost entirely rely on application-level instrumentation, which can leave gaps or conflicting semantics across different systems. We decided to seek potential solutions that could provide a more complete and unified picture of our networking topology. One of these solutions has been monitoring with eBPF, which allows developers to write programs that are injected directly into the kernel and can trace kernel operations. These programs, designed to provide lightweight access to most components of the kernel, are sandboxed and validated for safety by the kernel before execution. DoorDash was particularly interested in tracing network traffic via hooks called kprobes (kernel dynamic tracing) and tracepoints. With these hooks, we can intercept and understand TCP and UDP connections across our multiple Kubernetes clusters. By building at the kernel level, we can monitor network traffic at the infrastructure level, which gives us new insights into DoorDash’s backend ecosystem that’s independent of the service workflow. To run these eBPF probes, we have developed a Golang application called BPFAgent, which we run as a daemonset in all of our Kubernetes clusters. Here we will take a look at how we built BPFAgent, the process of building and maintaining its probes, and how various DoorDash teams have used the data collected.https://doordash.engineering/2023/08/15/bpfagent-ebpf-for-monitoring-at-doordash
Unleash is a powerful open source solution for feature management. It streamlines your development workflow, accelerates software delivery, and empowers teams to control how and when they roll out new features to end users. With Unleash, you can deploy code to production in smaller, more manageable releases at your own pace.https://github.com/Unleash/unleash
Learn how Vercel builds and deploys serverless applications.https://vercel.com/blog/behind-the-scenes-of-vercels-infrastructure
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