21 stories
We ran the same agent and model on 50 live Kubernetes faults. With read-only cluster context it reached the answer about three times faster, and was slightly more accurate. Here's what it did without that context, and how to run the same test before you buy an AI SRE.
Nadav Erell took Radar through a live broken cluster on Cloud Native FM. The short version: why a cluster is a graph, and what MCP actually changes.
Kubernetes 1.37 removes 25 feature gates, an alpha scheduling API, and 18 kubelet flags, and starts the nftables transition. What breaks, and how to check your cluster.
Pods Ready, Service green, curl times out. Radar's Reachability tab traces the declared network path and live-probes it, naming the first hop that breaks.
Two sentences get said in every meeting where a team wires an AI agent into a cluster: it's read-only, and just use the service account. Both are wrong later.
The honest bear case against our own product: if agents operate the cluster, who needs the UI? Here's what actually dies, and the job that gets bigger.
The same model diagnosed 50 live Kubernetes faults 3x faster on average through Radar's MCP server than through raw kubectl, with slightly higher accuracy. What we measured, why it happens, and where Radar still loses.
Kubernetes already fixes things at 3am without asking. Six levels for deciding what an AI agent gets to do in your cluster - and what should still wake you.
Radar v1.8 adds an Applications view, rebuilt navigation and search, richer Helm operations, large-cluster performance improvements, and Prometheus over MCP.
Pointing an AI at raw kubectl works, badly. Radar's built-in MCP server gives Claude, Cursor, and friends a token-optimized, RBAC-aware view of your cluster.
A practical migration guide for Lens and OpenLens users: what changed, when to move, and how to switch to Freelens, Headlamp, k9s, or Radar.
Seven Kubernetes UIs ranked by use case, plus a sourced capability matrix covering sixteen - by a team that builds one of them. Every claim dated and linked.
Most multi-cluster dashboards copy your cluster state into a backend cache. Radar Cloud doesn't. Here's why the reverse-proxy model is the right call.
Kubernetes ops spans three surfaces: CLI, UI, and AI agent. kubectl is fine, but a live cluster graph deserves better than raw YAML - for humans and agents alike.
How Radar's in-cluster install works: outbound-only TLS, read-only RBAC by default, ~32MB RSS. The five questions every platform team asks, answered.
The most common question in our GitHub issues: do I need Radar Cloud, or is OSS enough? Here's the honest answer, with the five questions that actually decide it.
Radar Cloud is the team layer on top of Radar OSS: fleet views, Google and GitHub sign-in on every plan, K8s-native RBAC via impersonation. Current cluster state is read live, not replicated.
kubectl hands you one object at a time, as raw YAML. Here are five questions - relationships, isolation, image contents, history, posture - where that runs out of road.
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