Kubernetes Explorer Is Now Generally Available

We’re thrilled to announce that Kubernetes Explorer is now generally available—ready for every SRE, DevOps, and platform engineer who needs a deeper, faster way to understand and troubleshoot Kubernetes workloads at scale. Since our private preview, we’ve refined features, boosted performance, and taken heaps of feedback from early adopters, all to make Kubernetes Explorer an essential tool for operating containerized applications.

Below, we’ll walk through how to get started and start sending data to Kubernetes Explorer from your clusters. We’ll also share how Kubernetes Explorer makes life easier for everyone who’s on-call, tuning resource limits, or hunting down those elusive production issues.

Add Kubernetes data

When you visit Kubernetes Explorer from the left navigation pane for the first time, you will be prompted to add Kubernetes data. After you create an ingest token, pick what types of telemetry data you want to capture, make sure to change the cluster name to something more specific to your environment. The Installation wizard will create appropriate ‘kubectl’ and ‘helm’ commands with appropriate parameters for you to execute on the Kubernetes cluster.

Note: Only those users who have an Observe admin role can add data from Kubernetes clusters. Once you execute commands, you can click on Check Status and if data is being received, click on Kubernetes in the left navigation panel to start exploring Kubernetes components.

Built to simplify Kubernetes complexity

It’s no secret that Kubernetes can be complicated—even for seasoned SREs. Clusters can consist of hundreds or thousands of nodes, running everything from microservices to AI inference workloads. Traditional tooling often falls short when dealing with this scale, leaving teams to cobble together multiple dashboards, logs, and metrics sources just to understand a single issue.

Kubernetes Explorer solves that pain by presenting a unified view of your clusters, so you can see exactly what’s going on across clusters– namespaces, pods, containers, and more. You’ll have a single place to visualize the state of all your services and quickly identify anomalies. Whether you’re chasing down performance problems, resource bottlenecks, or container restarts, Kubernetes Explorer cuts through the noise and helps you zero in on root causes.

 

Historical analysis with Kubernetes Hindsight

It can be frustrating while troubleshooting a problem you can’t recreate. You’ve probably heard the dreaded line: “It was working fine five hours ago!” Now you can travel back in time with Kubernetes Hindsight. This feature captures historical states of your deployments, letting you visualize and inspect how pods, nodes, or even entire clusters looked before trouble started.

This is especially useful when you’re investigating transient spikes or ephemeral pods. Instead of relying on incomplete logs or guesswork, you can see exactly what changed between 2 p.m. and 2:10 p.m.—like a new version of a microservice or a memory limit that was accidentally lowered. Kubernetes Hindsight peels back the curtain so you can definitively say, “That’s where things went off track,” and move on to fixing it rather than sleuthing.

Deeper visibility and easy drills-downs

Large Kubernetes environments can get chaotic. With hundreds of pods spread across multiple namespaces, you need more than just a top-level dashboard. Kubernetes Explorer offers instant drill-down: a single click from a cluster-level view takes you right to the specific workload, node, or pod that’s showing anomalies. From there, you can pivot into logs or traces, which come pre-filtered for the resource you’re analyzing—no more rummaging around different UIs or manually correlating timestamps.

Another perk is how the Explorer tracks lifecycle events. If a deployment fails to roll out, you’ll see exactly which step of the process got stuck. Or maybe you have a container that keeps crashing during initialization. Kubernetes Explorer provides context on each crash loop, flags potential resource constraints, and highlights configuration changes all in one place, making it a breeze to isolate and troubleshoot the problem.

Resource Requests, Limits, and Cost Optimizations

Kubernetes is great at orchestrating containers, but it can quickly burn through money if you’re over-allocating CPU and memory to pods. Since the private preview, we’ve added more robust resource management and cost insights. Kubernetes Explorer correlates resource Requests and Limits with actual usage, highlighting workloads that are chronically underutilized or starved for CPU.

If your pods consistently consume only 50% of the CPU Requests you’ve specified, that’s a clue you could scale back—without risking performance. Over time, these optimizations can save a bundle in cloud costs and free up cluster capacity for other workloads. Kubernetes Explorer helps you visualize where you can dial things back or ramp them up, all while ensuring critical services have room to breathe. 

Ready to Explore?

With the general availability of Kubernetes Explorer, we’re lowering the barrier to effective Kubernetes troubleshooting and observability. We’ve listened to feedback from the private preview and expanded on what worked best—making it simpler, more flexible, and faster. Whether you’re an SRE meticulously tuning resource limits or a DevOps engineer spinning up new deployments, we want you to spend less time digging through logs and more time delivering value to your customers.

Curious to see it in action? Sign up for a free trial to see how Kubernetes Explorer can transform the way you monitor and maintain your clusters. We can’t wait to show you around.

Thanks for all your support in our journey from private preview to GA. We’re excited to see what you’ll do with Kubernetes Explorer now that it’s in your hands. Happy exploring!