> For the complete documentation index, see [llms.txt](https://docs.tensorwave.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tensorwave.com/observability/kubernetes.md).

# Kubernetes

TensorWave's managed Kubernetes offering is designed to make it seamless to run and scale your clusters without the operational overhead. The Kubernetes tab gives you complete, real-time visibility into every layer of your cluster, from node health and pod status to deployments and scheduled workloads. Whether you're scaling a training run, debugging a degraded node, or auditing what's running across namespaces, everything you need is surfaced in one place without touching the terminal.

This level of visibility means your team spends less time diagnosing and more time shipping. Problems are easier to catch early, incidents are faster to resolve, and you always have a clear picture of your cluster's state at any scale.

#### Namespace filter

The **Namespace** dropdown at the top of the page filters all resource views simultaneously. Select a specific namespace to narrow your focus, or choose **All Namespaces** for a full picture of everything running across your cluster.

#### Overview

The Kubernetes overview gives you an instant read on the health of your entire cluster across three summary cards:

**Node Health** shows the number of ready and not-ready nodes, overall readiness percentage, and total node count at a glance.

**Pod Status** provides a real-time breakdown of all pods running across the cluster, categorized by state (e.g. Running, Succeeded) and visualized as a live donut chart.

**Deployments** shows total deployments and how many are available, with a clear healthy/degraded indicator so you can confirm your workloads are running as expected.

#### Nodes

Drill into the Nodes view for a granular per-node breakdown, no kubectl required.

**Summary cards** at the top surface the metrics that matter most:

* **Ready** nodes in a healthy, schedulable state
* **Not Ready** nodes that are unavailable or degraded
* **Control Plane** number of control plane nodes managing cluster state
* **Workers** number of worker nodes available for workloads

**Node table** breaks down every node in the cluster:

* **Hostname** node identifier, with one-click copy
* **Status** live node state (e.g. Ready, Unknown)
* **Role** whether the node is a `worker` or `control-plane`
* **Version** Kubernetes version running on the node
* **GPU** number of GPUs attached, where applicable
* **CPU** total CPU count
* **Memory** total memory provisioned
* **More Info** expands to show the node's internal IP, OS image, kernel version, and container runtime

#### Pods, Deployments, and other resources

The same namespace-scoped table interface is available for Pods, Deployments, StatefulSets, DaemonSets, Jobs, and CronJobs, giving you consistent visibility across every layer of your Kubernetes workloads without leaving the console.

#### Kubeconfig

Download your cluster's kubeconfig directly from the cluster header by clicking **Kubeconfig**. Use it to connect kubectl or any Kubernetes-compatible tooling to your cluster instantly.

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