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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
Больше📈 Аналитический обзор Telegram-канала DevOps & SRE notes
Канал DevOps & SRE notes (@devops_sre_notes) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 12 684 подписчиков, занимая 10 040 место в категории Технологии и приложения и 2 960 место в регионе США.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 12 684 подписчиков.
Согласно последним данным от 15 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 232, а за последние 24 часа — 5, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 15.80%. В первые 24 часа после публикации контент обычно набирает 4.81% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 004 просмотров. В течение первых суток публикация набирает 610 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 5.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как kubernete, cluster, author, engineering, monitoring.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”
Благодаря высокой частоте обновлений (последние данные получены 16 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.
12 684
Подписчики
+524 часа
+497 дней
+23230 день
Архив постов
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
