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
نمایش بیشتر📈 تحلیل کانال تلگرام DevOps & SRE notes
کانال DevOps & SRE notes (@devops_sre_notes) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 12 907 مشترک است و جایگاه 9 723 را در دسته فناوری و برنامهها و رتبه 2 846 را در منطقه الولايات المتحدة الأمريكية دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 12 907 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 14 ژوئیه, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 231 و در ۲۴ ساعت گذشته برابر 7 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 16.11% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 4.57% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 2 079 بازدید دریافت میکند. در اولین روز معمولاً 590 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 5 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند kubernete, cluster, author, engineering, monitoring تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 15 ژوئیه, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
12 907
مشترکین
+724 ساعت
+317 روز
+23130 روز
آرشیو پست ها
12 907
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
12 907
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/
12 907
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/
12 907
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
12 907
Pull Request-like Review/Approval flow for database queries. For compliant but smooth Engineering access to production.
https://github.com/kviklet/kviklet
12 907
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
12 907
Operator to streamline renovate executions in Kubernetes
https://github.com/mogenius/renovate-operator
12 907
🤦♂️ 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/
12 907
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
12 907
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
12 907
CloudGoat is Rhino Security Labs' "Vulnerable by Design" AWS deployment tool
https://github.com/RhinoSecurityLabs/cloudgoat
12 907
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
12 907
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-tail12 907
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
12 907
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
12 907
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/
12 907
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/
12 907
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#
