DevOps & SRE notes
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Helpful articles and tools for DevOps&SRE youtube: https://www.youtube.com/@DevOpsAndSRENotes
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DevOps & SRE notes (@devops_sre_notes) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 13 292 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 9 509-o'rinni va AQSH mintaqasida 2 720-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 13 292 obunachiga ega bo‘ldi.
04 Noyabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -43 ga, so‘nggi 24 soatda esa 0 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 14.83% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 4.82% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 1 971 marta ko‘riladi; birinchi sutkada odatda 641 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 10 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent kubernete, cluster, author, engineering, monitoring kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
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“Helpful articles and tools for DevOps&SRE
youtube: https://www.youtube.com/@DevOpsAndSRENotes”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 05 Noyabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
13 292
Obunachilar
Ma'lumot yo'q24 soatlar
-237 kun
-4330 kun
Postlar arxiv
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Pipedrive Infra manages numerous Kubernetes clusters across different clouds, including AWS and on-premise OpenStack. They had been experiencing intermittent failing pod health checks, which became more frequent over time. After an extensive investigation, the team discovered that Kubelet was initiating TCP sessions to pods using random source ports within the same range reserved by Kubernetes nodeports. This caused the TCP SYN-ACK to be redirected to other pods, leading to failed health checks. The solution was to disallow the use of the nodeport range as the source port for TCP sessions with a single line of code, effectively resolving the issue.
https://medium.com/pipedrive-engineering/solving-the-mystery-of-pods-health-checks-failures-in-kubernetes-55b375493d03
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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
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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
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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
13 292
Don't forget about security
https://dzone.com/articles/container-security-top-5-best-practices-for-devops
13 292
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
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🎨 Diagram as Code for prototyping cloud system architectures
https://github.com/mingrammer/diagrams
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🔥 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
13 292
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
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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
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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/
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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
13 292
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
