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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تُعد قناة DevOps & SRE notes (@devops_sre_notes) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 13 258 مشتركاً، محتلاً المرتبة 9 374 في فئة التكنولوجيات والتطبيقات والمرتبة 2 784 في منطقة الولايات المتحدة.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 13 258 مشتركاً.
بحسب آخر البيانات بتاريخ 25 أغسطس, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 254، وفي آخر 24 ساعة بمقدار 3، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 16.60%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 4.52% من ردود الفعل نسبةً إلى إجمالي المشتركين.
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- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 3.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل kubernete, cluster, author, engineering, monitoring.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“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”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 26 أغسطس, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
13 258
المشتركون
+324 ساعات
+267 أيام
+25430 أيام
أرشيف المشاركات
13 259
🛡 Open-source and cloud-native Web Application Firewall (WAF)
https://github.com/bunkerity/bunkerweb
13 259
The article challenges the traditional "three pillars" of observability (metrics, logs, traces), arguing that they are insufficient for modern, distributed architectures. Through three real-world incident examples at a large financial institution, the author demonstrates that application-level telemetry often fails to reveal actual customer impact. Instead of siloed data, the author advocates for "single threads"—clear, end-to-end distributed traces of individual customer requests—enriched with business context and measured by customer-facing Service Level Objectives (SLOs).
https://www.honeycomb.io/blog/you-dont-need-three-pillars-you-need-single-threads
13 259
A command-line tool for Jira workflow management. Quickly select issues, track your current work, and generate consistent branch names.
https://github.com/tutunak/jcli
13 259
Repost from N/a
Agentic CI/CD: Kubernetes Deployment Gates with Elastic MCP Server — Elastic Observability Labs
https://www.elastic.co/observability-labs/blog/agentic-cicd-kubernetes-mcp-server
13 259
From Silos to Service Topology: Why Netflix Built a Real-Time Service Map
https://netflixtechblog.com/from-silos-to-service-topology-why-netflix-built-a-real-time-service-map-0165ba13a7bc
13 259
How GitHub uses eBPF to improve deployment safety
https://github.blog/engineering/infrastructure/how-github-uses-ebpf-to-improve-deployment-safety/
13 259
Repost from N/a
https://www.cncf.io/blog/2026/06/25/building-a-cluster-aware-ai-agent-with-kubernetes-argo-cd-and-gitops/
Practical walkthrough for a self-hosted, read-only cluster AI agent with GitHub Actions, Argo CD Image Updater, and no cluster data leaving the network. Good pattern material for safe “AI assistant inside the cluster” experiments.
13 259
Morgan Stanley presented their journey scaling Flux to manage over 500 clusters and tens of thousands of resources. They detailed their transition from push-based CI/CD pipelines to a pull-based, continuous reconciliation model using Flux to eliminate configuration drift. The article outlines their strategy for handling enterprise-grade security, performance tuning for scale, and adapting architecture (like moving from Git to S3) to meet high availability and compliance needs.
https://fluxcd.io/blog/2026/03/stairway-to-gitops-morgan-stanley/
13 259
Trusted builds made easy! A cloud-native software factory for building, testing, and releasing trusted software artifacts
Konflux is an open-source, Kubernetes-native CI/CD platform that manages the full software delivery lifecycle for software artifacts — with supply chain trust built in from the start. Built on Tekton and the Conforma policy framework, it brings together best-in-class open source projects into a single, integrated software factory. Managed by a Kubernetes operator, Konflux runs on Kind, OpenShift, and any conformant Kubernetes cluster.
https://github.com/konflux-ci/konflux-ci
13 259
A lightweight tool for deploying and managing containerised applications across a network of Docker hosts. Bridging the gap between Docker and Kubernetes ✨
https://github.com/psviderski/uncloud
13 259
Deep dive into Prometheus’s
use-uncached-io work and why page cache behavior can make Kubernetes container memory metrics misleading. Useful for anyone running Prometheus at scale: covers memory predictability, compaction writes, OOM risk, and tradeoffs around direct I/O.
https://prometheus.io/blog/2026/03/05/uncached-io/13 259
Ministack: Free, open-source local AWS emulator - 55+ services, Terraform compatible, real databases. Free forever. MIT licensed.
https://github.com/ministackorg/ministack
13 259
Kubernetes configuration tracking controller.
Wave watches Deployments, StatefulSets and DaemonSets within a Kubernetes cluster and ensures that their Pods always have up to date configuration.
By monitoring mounted ConfigMaps and Secrets, Wave can trigger a Rolling Update of the Deployment when the mounted configuration is changed.
https://github.com/wave-k8s/wave
13 259
Repost from N/a
Hands-on vendor-neutral instrumentation for GenAI spans, tool calls, token metrics, and trace exploration. Worth reading if you want AI-agent debugging to fit existing OTel/Grafana/Loki-style observability rather than a separate black box.
https://opentelemetry.io/blog/2026/genai-observability/
13 259
Lessons from Moving a Live Production Database describes the complex process of migrating a massive dataset while keeping the service available to users.
The case study covers specific strategies for achieving zero downtime during a high-risk infrastructure change.
But is zero downtime always worth the engineering effort?
Imagine that you have two options:
1. Spend several weeks preparing and testing a zero-downtime migration.
2. Schedule 20 minutes of downtime during a low-traffic period.
Considering that 99.9% availability allows approximately 43 minutes of downtime per month, which option would you choose?
What factors would change your decision: revenue loss, SLA penalties, customer expectations, rollback complexity, or the size of the engineering team?
https://www.tines.com/blog/zero-downtime-database-migrations-lessons-from-moving-a-live-production/
13 259
Containerlab focuses on the containerized Network Operating Systems which are typically used to test network features and designs
https://github.com/srl-labs/containerlab
13 259
The article explores how integrating these two prominent tools can accelerate and enhance platform engineering initiatives.
https://platformengineering.org/blog/platform-engineering-with-crossplane-and-argocd
