kagent runs your agents where your workloads already live — on Kubernetes. Deploy, observe, and govern AI agents with the tools your platform team already trusts. Open source. Production grade. Built by the founders of Istio.

https://github.com/kagent-dev/kagent

When you have a special math to calculate your uptime, you always have 100%.

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#

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

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/

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/

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

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

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

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

CloudGoat is Rhino Security Labs' "Vulnerable by Design" AWS deployment tool

https://github.com/RhinoSecurityLabs/cloudgoat

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

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

🤦‍♂️ 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/

Operator to streamline renovate executions in Kubernetes

https://github.com/mogenius/renovate-operator

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

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

https://github.com/kviklet/kviklet

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

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/

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/