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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
Mostrar más📈 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 12 684 suscriptores, ocupando la posición 10 040 en la categoría Tecnologías y Aplicaciones y el puesto 2 960 en la región EEUU.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 12 684 suscriptores.
Según los últimos datos del 15 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 232, y en las últimas 24 horas de 5, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 15.80%. 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 2 004 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 16 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.
12 684
Suscriptores
+524 horas
+497 días
+23230 días
Archivo de publicaciones
12 684
In this post, the author discusses potential PostgreSQL pitfalls that may not affect small databases, but can cause issues when databases grow.
https://philbooth.me/blog/nine-ways-to-shoot-yourself-in-the-foot-with-postgresql
12 684
Streaming alert evaluation offers better scalability than traditional polling time-series databases, overcoming high dimensionality/cardinality limitations. This enables engineers to have more reliable and real-time alerting systems. The transition to the streaming path has opened doors for supporting more exciting use-cases and has allowed multiple platform teams at Netflix to generate and maintain alerts programmatically without affecting other users. The streaming paradigm may help tackle correlation problems in observability and offer new opportunities for metrics and events verticals, such as logs and traces.
https://netflixtechblog.com/improved-alerting-with-atlas-streaming-eval-e691c60dc61e
12 684
A new terraform version has been released. Import already existed infrastructure to the terraform state become easier.
https://www.hashicorp.com/blog/terraform-1-5-brings-config-driven-import-and-checks
12 684
Don't forget about security
https://dzone.com/articles/container-security-top-5-best-practices-for-devops
12 684
In the second part of the DevOps project, the focus is on deploying monitoring tools like ArgoCD, Prometheus, and Grafana to a Kubernetes cluster. The blog post covers installing ArgoCD, deploying Prometheus using Helm charts, setting up monitoring for ArgoCD, visualizing ArgoCD metrics using Grafana dashboards, and continuous deployment of applications using ArgoCD. A useful tool, K8sgpt, is recommended to analyze the cluster for errors and potential issues. The next blog post will discuss configuring Alert Manager for notifications, setting up Slack alerts, and installing Loki for logs, enhancing the monitoring solution.
https://blog.devgenius.io/optimizing-kubernetes-deployments-with-argocd-and-prometheus-aa86c11e2bba
12 684
🎨 Diagram as Code for prototyping cloud system architectures
https://github.com/mingrammer/diagrams
12 684
🔥 Open source static (serverless) status page. Uses hyperfast Go & Hugo, minimal HTML/CSS/JS, customizable, outstanding browser support (IE8+), preloaded CMS, read-only API, badges & more.
https://github.com/cstate/cstate
12 684
Nothin can be free forever or the story how Oracle take back a free cloud vms
https://armin.su/oracle-cloud-and-loss-of-data-in-kubernetes-cluster-198d88181829
12 684
This post provides a guide to configuring and installing a multi-cluster observability solution for cloud computing environments like AWS, Azure, and Google Cloud. The solution includes Grafana, Prometheus, Thanos, and Loki for monitoring applications and microservices in multi-cluster environments. The guide assumes prior experience with AWS S3, Policy, IAM, EKS, and Kubernetes. It covers the creation of IAM policies and roles, the installation of Helm, Bitnami's Helm charts, and EKS, AWS CLI, eksctl, and kubectl tools. The guide details the process of setting up multi-cluster observability with metrics monitoring using kube-prometheus and Thanos and log monitoring using Grafana Loki and Promtail.
https://medium.com/@bahungxt/multi-cluster-observability-solution-with-prometheus-thanos-loki-and-grafana-5d5be42635e8
12 684
K8sGPT gives Kubernetes Superpowers to everyone
k8sgpt is a tool for scanning your kubernetes clusters, diagnosing and triaging issues in simple english. It has SRE experience codified into it’s analyzers and helps to pull out the most relevant information to enrich it with AI.
https://k8sgpt.ai/
12 684
This article explores Kubernetes Resource Manager and the Google Config Connector, comparing them to Terraform, a popular infrastructure orchestration tool. Kubernetes, an open-source container orchestration tool, has gained market dominance with its Custom Resource Definitions (CRDs), which allows managing Google Cloud resources through Kubernetes using CRDs. Config Connector, an add-on to Kubernetes, can potentially replace Terraform in some workflows. However, the author's experiment shows that while Config Connector can be used to deploy a Google Cloud landing zone, it has limitations compared to Terraform, particularly in handling interdependencies based on values unknown until a resource is created.
In conclusion, the author suggests a hybrid approach, with Terraform for platform-centric deployments and Config Connector for application-centric deployments. While Terraform's flexibility and provider support make it useful for organizations operating in multiple clouds, Config Connector has a compelling place in application-centric deployments where small amounts of infrastructure are deployed in support of Kubernetes-based services.
https://medium.com/cts-technologies/are-terraforms-days-numbered-a9a15ec0435a
12 684
This blog post discusses the growing trend of Large Language Models (LLMs) and their impact on various use cases. One specific application discussed is K8sGPT, an AI-based Site Reliability Engineer (SRE) that runs inside Kubernetes clusters. It scans, diagnoses, and triages issues using SRE experience codified into its analyzers. LocalAI, another project, is a drop-in replacement API for local CPU inferencing. Combining K8sGPT and LocalAI enables powerful SRE capabilities without relying on expensive GPUs.
https://itnext.io/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65
12 684
Jan Kammerath, discusses the potential pitfalls of using Kubernetes and Kafka in a medium-sized software company. The author shares a consulting experience where the CEO of a software company called for advice due to low availability (87%) and rising operational costs. The company had Kubernetes and Kafka implemented in its infrastructure, but it struggled to manage them efficiently.
https://medium.com/@jankammerath/how-kubernetes-and-kafka-will-get-you-fired-a6dccbd36c77
12 684
In a recent Dev Interrupted article, Kubernetes co-founder Brendan Burns discussed the origins and growth of the open-source project. Kubernetes, a container orchestrator, was born out of the need to simplify the process of building, deploying, and maintaining distributed systems. Burns, along with co-founders Joe Beda and Craig McLuckie, were inspired by Google's internal system called Borg and wanted to create something similar for the larger development community. Docker played a crucial role in popularizing the concept of containers, which then paved the way for Kubernetes' success.
https://devinterrupted.substack.com/p/how-open-source-enabled-kubernetes
12 684
This is a place for various problem detectors running on the Kubernetes nodes.
https://github.com/kubernetes/node-problem-detector
