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DevOps & SRE notes

DevOps & SRE notes

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Helpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19

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📈 Análisis del canal de Telegram DevOps & SRE notes

El canal DevOps & SRE notes (@devops_sre_notes) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 12 681 suscriptores, ocupando la posición 10 048 en la categoría Tecnologías y Aplicaciones y el puesto 2 966 en la región EEUU.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 12 681 suscriptores.

Según los últimos datos del 14 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 228, y en las últimas 24 horas de 6, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 15.90%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 4.81% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 2 016 visualizaciones. En el primer día suele acumular 610 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 5.
  • Intereses temáticos: El contenido se centra en temas clave como kubernete, cluster, author, engineering, monitoring.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
Helpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 15 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.

12 681
Suscriptores
+624 horas
+517 días
+22830 días
Archivo de publicaciones
Logging operator for Kubernetes https://github.com/kube-logging/logging-operator

Tools for building Kubernetes disk images https://github.com/kubernetes-sigs/image-builder

In this article, you'll explore the complexities of Kubernetes network management, iptables, and port forwarding and discover how Kubernetes hides service ports from traditional tools like netstat. https://journal.hexmos.com/kube-network/

🦭 Run and operate MariaDB in a cloud native way https://github.com/mariadb-operator/mariadb-operator

Open-source observability for microservices. Thanks to eBPF you can gain comprehensive insights into your system within minutes. https://github.com/coroot/coroot

The article by Luca Cavallin titled "barco: Linux Containers From Scratch in C" is a comprehensive guide on creating a simple container runtime in C. It focuses on utilizing Linux kernel features like namespaces, seccomp, capabilities, and cgroups. The project, named 'barco', serves as a learning tool for understanding containerization in Linux and is not intended for production use. The article also details the development process, including the environment setup and the structure of the C project. https://www.lucavall.in/barco-linux-containers-from-scratch-in-c

Self-hosted Jira - RIP. Support for Server products ended on Feb. 15, 2024 Server products and apps no longer receive technical support, security updates, and bug fixes for vulnerabilities. https://www.atlassian.com/migration/assess/journey-to-cloud

This driver allows Kubernetes to access NFS server on Linux node. https://github.com/kubernetes-csi/csi-driver-nfs

m9sweeper is a free and easy kubernetes security platform. https://github.com/m9sweeper/m9sweeper

Watches k8s cluster events and logs them to stdout in JSON https://github.com/max-rocket-internet/k8s-event-logger

https://nateb.xyz/a/self-managed-kubernetes The article by Nate Buckareff on "Self-Managed Kubernetes" is a detailed tutorial on setting up a self-managed Kubernetes cluster using QEMU, a Linux virtual machine environment. It covers steps like setting up a local test environment, creating virtual network interfaces, bootstrapping nodes, and installing Kubernetes with k0s. The guide also addresses network configurations using dnsmasq and iptables, and emphasizes the importance of understanding Kubernetes intricacies for successful self-management.

🦥 Easy and simple Prometheus SLO (service level objectives) generator https://github.com/slok/sloth

zot - A production-ready vendor-neutral OCI-native container image registry (purely based on OCI Distribution Specification) https://github.com/project-zot/zot

Define sleep & wake up cycles for your Kubernetes resources. Automatically schedule to shutdown Deployments, CronJobs, StatefulSets and HorizontalPodAutoscalers that occupy resources in your cluster and wake them up only when you need them, reducing that way the overall power consumption. https://github.com/rekuberate-io/sleepcycles

https://povilasv.me/how-to-monitor-kubelet/ The article on Povilas Versockas' blog provides a comprehensive guide on monitoring Kubelet, a key component in Kubernetes. It explains Kubelet's role in managing pods and nodes, details its operation, and discusses how to monitor it effectively using methods like the RED approach. The article also outlines the Kubernetes Service Level Objectives for Kubelet and introduces the Kubernetes Monitoring Mixin, which includes a dashboard and alerts for monitoring Kubelet. This resource is particularly useful for those looking to understand and improve their monitoring of Kubelet in a Kubernetes environment.

A kubectl plugin to visualize network policies rules. https://github.com/runoncloud/kubectl-np-viewer

Kepler (Kubernetes-based Efficient Power Level Exporter) uses eBPF to probe performance counters and other system stats, use ML models to estimate workload energy consumption based on these stats, and exports them as Prometheus metrics https://github.com/sustainable-computing-io/kepler