DevOps & SRE notes
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Helpful articles and tools for DevOps&SRE

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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
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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/
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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
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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/
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Forwarded from AI Vibe Notes
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.
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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
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