Four deployments on our test cluster run PHP below the PHP2Shell fix. A search of Trivy Operator's findings for CVE-2026-109618 finds one.
The other three use the official php or WordPress images, where PHP is compiled from source, so Trivy doesn't report the PHP runtime.
Radar's Rightsizing tab suggests Kubernetes CPU and memory requests from the Prometheus metrics you already collect. Nothing extra to install in the cluster.
It withholds CPU cuts when an autoscaler uses CPU utilization to decide how many replicas to run.
One of the best tips I remember from @ycombinator was that "a small group of customers who love you is better than a large group who kind of like you."
How about a rapidly growing group who loves us?
The love we're getting unprompted from random users of @RadarK8s is just so energizing ❤️
Nadav Erell retweeted
It's always really cool to see how the community uses #SREGym for different kinds of analysis. I find @RadarK8s 's analysis rather interesting. I always wanted to look into more SRE agent products beyond raw coding agents, but never found the time. They did it. The comparative analysis on speed ⏱️, effectiveness 🎯, and cost💰makes a lot of sense, and the discussion on the interface (MCP vs kubectl) is something my colleagues and I have had many deep discussions. I'd love to see more and deeper analysis!
Before you buy an Al SRE, find out what the Al you already pay for can do.
If you have Claude Code, you have half of an Al SRE already. We broke a live Kubernetes cluster 50 ways (public SREGym benchmark), then had the same coding agent investigate every failure under different setups.
One - with standard kubectl CLI access. It reached a correct diagnosis within two minutes 60% of the time. Already not bad.
Two - when we also gave it a clear view of the cluster, like what was failing and what had changed recently (with Radar MCP), it was 86%. Same model.
Three - tried a few Al SRE tools. Some of the common names you'd expect if you Google it (full details in radar site if you're curious). None of them reached the same accuracy as Claude Code with Radar MCP, and all of them were at least twice as slow, some much worse. They also burned a *lot* more tokens doing it.
When you have an outage, you don't want your agent spending 10 minutes gathering context, building the model of what is going on using tools that weren't designed for it and getting lost in piles of YAML. and not even getting a better result in the end.
So what does an Al SRE get you? Some general prompt on how to debug kubernetes, triggers on alerts, and maybe a nicer Ul than claude's terminal output (I'm exaggerating a bit, but you get the point).
Guess what? Radar Cloud now gives you all of this as well, and cheaper than any Al SRE tool out there that publishes pricing.
Before you buy an Al SRE, find out what the Al you already pay for can do.
If you have Claude Code, you have half of an Al SRE already. We broke a live Kubernetes cluster 50 ways (public SREGym benchmark), then had the same coding agent investigate every failure under different setups.
One - with standard kubectl CLI access. It reached a correct diagnosis within two minutes 60% of the time. Already not bad.
Two - when we also gave it a clear view of the cluster, like what was failing and what had changed recently (with Radar MCP), it was 86%. Same model.
Three - tried a few Al SRE tools. Some of the common names you'd expect if you Google it (full details in radar site if you're curious). None of them reached the same accuracy as Claude Code with Radar MCP, and all of them were at least twice as slow, some much worse. They also burned a *lot* more tokens doing it.
When you have an outage, you don't want your agent spending 10 minutes gathering context, building the model of what is going on using tools that weren't designed for it and getting lost in piles of YAML. and not even getting a better result in the end.
So what does an Al SRE get you? Some general prompt on how to debug kubernetes, triggers on alerts, and maybe a nicer Ul than claude's terminal output (I'm exaggerating a bit, but you get the point).
Guess what? Radar Cloud now gives you all of this as well, and cheaper than any Al SRE tool out there that publishes pricing.
Roy wrote up how we ran it and how to run the same test on your own setup:
radarhq.io/blog/ai-sre-give-…
On one fault, Claude Code with a shell took 11.7 minutes and 58 tool calls, ending with Helm's release Secret decoded by hand.
With read-only tools that return current failures and recent changes, the same model reached the same diagnosis in 35 seconds.
Kubernetes 1.34 reaches end of life Oct 27, and each managed provider acts on its own date:
EKS can upgrade the control plane without notice after extended support ends.
GKE upgrades paused clusters at end of support.
AKS 1.34 stops getting security patches Nov 30.
Using Kubernetes? You want to try Radar 🔥🔥
The new go-to interface for Kubernetes, for humans and agents. See why thousands of engineers are switching
🛠 DevOps Tool of the Week: Radar
When troubleshooting Kubernetes, you may use multiple tools like,
kubectl, Helm, Argo CD, network dashboards, and other tools just to understand what is happening inside the cluster.
Radar gives you a single place to see all of that.
It is an open-source Kubernetes UI that can run locally as a single binary and connect directly to your cluster.
Here is what it does 👇
• Visualize how Kubernetes resources are connected
• See events and resource changes on a timeline
• Manage Helm releases, revisions, upgrades, and rollbacks
• Check Argo CD and Flux sync/drift status
• Visualize live service traffic using Hubble, Caretta, Istio, or Beyla
• Run built-in security, reliability, and efficiency checks
• Inspect RBAC permissions
• Connect AI tools such as Claude and Cursor through its built-in MCP server
You can start locally without deploying another agent into the cluster.
For teams, Radar can also run inside Kubernetes with authentication.
𝗦𝘁𝗮𝗿𝘁 𝗛𝗲𝗿𝗲: github.com/skyhook-io/radar
#devopstools
Nadav Erell retweeted
🛠 DevOps Tool of the Week: Radar
When troubleshooting Kubernetes, you may use multiple tools like,
kubectl, Helm, Argo CD, network dashboards, and other tools just to understand what is happening inside the cluster.
Radar gives you a single place to see all of that.
It is an open-source Kubernetes UI that can run locally as a single binary and connect directly to your cluster.
Here is what it does 👇
• Visualize how Kubernetes resources are connected
• See events and resource changes on a timeline
• Manage Helm releases, revisions, upgrades, and rollbacks
• Check Argo CD and Flux sync/drift status
• Visualize live service traffic using Hubble, Caretta, Istio, or Beyla
• Run built-in security, reliability, and efficiency checks
• Inspect RBAC permissions
• Connect AI tools such as Claude and Cursor through its built-in MCP server
You can start locally without deploying another agent into the cluster.
For teams, Radar can also run inside Kubernetes with authentication.
𝗦𝘁𝗮𝗿𝘁 𝗛𝗲𝗿𝗲: github.com/skyhook-io/radar
#devopstools
While adding Karpenter support to Radar, we mapped where Karpenter failures leave their evidence.
One that catches people out: a NodePool can stay Ready while every node it launches fails to register, because registration health sits on its own condition outside Ready.
Nadav Erell retweeted
Your agent can dump kubectl all day and still miss why the cluster is on fire.
You paste pod logs into chat, lose Helm context, and the GitOps tree stays in another tab. A generic desktop console does not make Kubernetes topology agent-native.
Radar is a local-first Kubernetes UI and kubectl plugin with a built-in MCP server for cluster topology, findings, Helm, and GitOps.
When the agent can ask Radar about broken pods and recent events instead of eating raw YAML dumps, triage gets shorter.
github.com/skyhook-io/radar
Nadav Erell retweeted
🤖 You can trigger an AI investigation directly from Radar.
Radar provides the context through its MCP tools, allowing the agent to investigate the Kubernetes environment, gather evidence, explain its findings, and provide remediation recommendations.
youtube.com/watch?v=xgVTudkY…
Nadav Erell retweeted
🚨 What happens to the Kubernetes dashboard when your environment grows from one cluster to 40+, and AI agents become part of the operations team?
In CloudNativeFM Episode 147, Nadav Erell about where Radar fits into the evolving K8s operations landscape.
youtube.com/watch?v=xgVTudkY…
Nadav Erell retweeted
🚨 K8s dashboards are evolving.
What happens when you have 40+ clusters AND AI agents operating your infra?
In Ep 147 @NadavErell explains how Radar Cloud brings:
🔹 Fleet-wide visibility
🔹 Cross-cluster search & checks
🔹 Centralized MCP for AI agents
youtube.com/shorts/yeBPffdD-…
Nadav Erell retweeted
Awesome software is awesome- radarhq.io/ detected that I was running @ciliumproject in one of my clusters and suggested that I enable its inbuiit Hubble eBPF-based network observability to populate its Live Traffic section. Incidentally if I’m not using K9S I’m using Radar and if you’re not, you should check it out.
Nadav Erell retweeted
🚀 Is the Kubernetes UI about to change?
Our latest @cloudnativefm episode will explore Radar🤔
💬 What should we discuss in upcoming CloudNativeFM episodes?
Drop your Kubernetes, DevOps, Platform Engineering, GitOps, AI or MCP questions below 👇
🔗 github.com/skyhook-io/radar
Kubernetes 1.37 is out today, and @RadarK8s already supports it.
If your kubelet config still has SidecarContainers: true from the 1.28 days, that node won't start on 1.37. It's one of 25 gates removed in this release.
What else breaks, and the kubectl one-liners to check: radarhq.io/blog/kubernetes-1…
Nadav Erell retweeted
🔗 GitHub: github.com/skyhook-io/radar
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