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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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📈 Аналітичний огляд Telegram-каналу DevOps & SRE notes

Канал DevOps & SRE notes (@devops_sre_notes) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 12 903 підписників, посідаючи 9 745 місце в категорії Технології та додатки та 2 849 місце у регіоні США.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 12 903 підписників.

За останніми даними від 13 липня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 230, а за останні 24 години на 8, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 15.81%. Протягом перших 24 годин після публікації контент зазвичай збирає 4.58% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 2 040 переглядів. Протягом першої доби публікація в середньому набирає 591 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 5.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як kubernete, cluster, author, engineering, monitoring.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
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

Завдяки високій частоті оновлень (останні дані отримано 14 липня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Технології та додатки.

12 903
Підписники
+824 години
+287 днів
+23030 день
Архів дописів
A userspace out-of-memory killer https://github.com/facebookincubator/oomd

Repost from N/a
Hands-on comparison against a deliberately broken cluster, with real outputs and failure-mode differences. Practical for deciding where AI Kubernetes tools fit: scanner, agent framework, or natural-language kubectl layer. https://decodeops.substack.com/p/k8sgpt-vs-kagent-vs-kubectl-ai-what

The 10-step playbook to reduce K8s bills by 40-60%, focusing heavily on bridging the gap between requested and actually used resources. https://leanopstech.com/blog/kubernetes-cost-optimization-guide-2026/

Deep-dive technical guide into the exact mechanics of pod restarts and configuration updates in Kubernetes https://www.cncf.io/blog/2026/03/17/when-kubernetes-restarts-your-pod-and-when-it-doesnt/

kubectl debugging plugin to collect full or partial cluster state and serve via an api server. Kubernetes time machine https://github.com/crust-gather/crust-gather

Pull Request-like Review/Approval flow for database queries. For compliant but smooth Engineering access to production. https://github.com/kviklet/kviklet

This article provides an insightful, framework-driven overview of automated post-mortem generation, defining how AI transforms incident retrospectives from manual reconstruction into automated drafting based on existing artifacts. It introduces a structural model for evaluating tools rather than just summarizing vendor features. https://www.arvoai.ca/blog/automated-post-mortem-generation

Operator to streamline renovate executions in Kubernetes https://github.com/mogenius/renovate-operator

🤦‍♂️ Tech is fundamentally broken. Microsoft's brilliant new fix to make the Windows 11 Start menu feel snappy is just spiking your CPU to maximum frequency for three seconds every time you click it, rather than optimizing the UI. What a world. https://www.windowslatest.com/2026/06/10/windows-11s-performance-boost-released-today-enable-it-using-these-steps/

Repost from N/a
Practical walkthrough of running kAgent against a Kubernetes cluster, using MCP tools to investigate common workload failures. Useful for thinking about safe AI copilots for day-2 ops, not just chat-based kubectl wrappers. https://andamp.io/insights/blog/hands-on-with-kagent-ai-assisted-kubernetes-troubleshooting-with-mcp

Technical postmortem detailing a sophisticated supply-chain compromise of the TanStack ecosystem on May 11, 2026 https://tanstack.com/blog/npm-supply-chain-compromise-postmortem

CloudGoat is Rhino Security Labs' "Vulnerable by Design" AWS deployment tool https://github.com/RhinoSecurityLabs/cloudgoat

Shopify discovered that deeply nested, high-cardinality GraphQL queries were bottlenecking not on I/O, but on CPU-bound field resolver execution driven by GraphQL’s standard depth-first traversal model. To solve this, Shopify built "GraphQL Cardinal," a breadth-first execution engine that resolves each field once across all objects rather than recursively per object, vastly reducing platform overhead and resolving N+1 issues more efficiently. https://shopify.engineering/faster-breadth-first-graphql-execution

A utility for fetching Kubernetes Manifest documents from a running cluster. This utility can be run inside or outside a Kubernetes cluster, and utilizes a config file to determine what kind of objects to detect. Manifests files are stored in an output directory in the format: <outputDir>/<kind>/<namespace>/<name>.yaml https://github.com/grafana/k8s-manifest-tail

Airbnb migrated its high-volume metrics infrastructure to adopt the OpenTelemetry Protocol (OTLP) and Prometheus. To do so without massive disruption, they implemented a dual-emit strategy in their shared metrics libraries. They encountered and solved specific performance bottlenecks regarding high-cardinality data and replaced their legacy Veneur aggregator with a custom-sharded vmagent setup. Crucially, they developed a "zero injection" technique to solve systemic undercounting issues when translating StatsD-style counters into Prometheus cumulative counters. https://medium.com/airbnb-engineering/building-a-high-volume-metrics-pipeline-with-opentelemetry-and-vmagent-c714d6910b45

The article explores the newly introduced CloudWatch Logs delivery feature for Amazon EKS Auto Mode. https://shinyaz.com/en/blog/2026/03/19/eks-auto-mode-enhanced-logging

The primary bottleneck in software delivery is no longer writing code (thanks to AI-assisted development) but rather post-commit infrastructure operations, which are traditionally built for human interaction rather than machine autonomy. It positions Crossplane and Kubernetes-native control planes as the necessary solution, advocating for "API-first infrastructure." https://www.cncf.io/blog/2026/03/20/crossplane-and-ai-the-case-for-api-first-infrastructure/

ING tackled developer portal sprawl (60+ disparate tools) by adopting Backstage.io as their unified front-end standard. The talk outlines their specific architectural choices and governance models to scale Backstage without it becoming a monolithic bottleneck or crashing due to community plugins. - To prevent a single bad plugin from crashing the portal, ING separates core services (like the software catalog, which handles hundreds of thousands of entities and has dedicated DB tuning) from community/external plugins, running them on separate instances. - To avoid costly rewrites of legacy services, internal teams can use a backend proxy plugin to connect existing backend tools into the Backstage UI. - Built a custom plugin to solve ownership issues in complex, cross-domain workflows. - Because anyone can contribute, ING enforces a "Contribution Plugin" workflow - They drove adoption by focusing heavily on Developer Experience (local setups, playgrounds) while simultaneously having their Technology Standards Board mandate Backstage for all new internal UI initiatives. https://tldrecap.tech/posts/2026/backstagecon-europe/ing-backstage-scaling-developer-platform/

CLI tool for linting and testing Helm charts https://github.com/helm/chart-testing

The new DNSTracking feature in the Red Hat network observability operator 1.11, which now captures DNS query names directly via eBPF without additional configuration. https://developers.redhat.com/articles/2026/04/09/how-dns-name-tracking-enhances-network-observability#