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The node page answers “what is this machine, is it healthy, and what can it run?” in one screen - including the accelerator on a GPU node.

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Accessing nodes

Navigate to your cluster and click Kubernetes → Nodes in the sidebar, then click a node. The same page is reachable from the cluster overview’s node table and the Command Palette (⌘+K). The CLI equivalents are ankra cluster get nodes for the list and ankra cluster describe node <name> for one node with its events.

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The node header

Chips carry state, the fact strip carries identity:
  • Readiness - Ready, NotReady or Unknown from the kubelet’s Ready condition, plus Scheduling disabled when the node is cordoned.
  • Role - Worker, Control Plane or any other node-role.kubernetes.io/* label.
  • Accelerator - on a GPU node, the GPU count and product (1× NVIDIA H100 80GB HBM3).
  • Age, instance type, location (provider · region · zone), node group, kubelet version and internal IP.
Everything that describes the host itself (operating system, kernel, runtime, architecture, addresses) lives in the Host card below. The ⋯ Actions menu holds cordon, uncordon, drain and delete.

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Overview tab

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Stat tiles

One figure per tile, always the allocatable amount: CPU, Memory, GPU (only on accelerator nodes), Storage and Pods - the last one counts the pods placed on the node against its pods capacity. Capacity and the kubelet’s reservation are in the Allocatable card.

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Accelerator

When a node advertises a GPU resource (nvidia.com/gpu, an nvidia.com/mig-* profile, amd.com/gpu, gpu.intel.com/*, habana.ai/gaudi) or carries NVIDIA GPU Feature Discovery labels, an Accelerator card appears under the tiles. On an NVIDIA node it reads the labels the GPU operator stamps on the node: The card leads with the five facts that decide what can run: GPU count × memory, CUDA driver, CUDA runtime, sharing strategy and (on MIG-capable parts) the MIG configuration. More details reveals MPS and vGPU capability, the driver-upgrade state, compute mode, machine type, when discovery last ran, the operator components deployed, and how many GPUs the device plugin currently advertises as allocatable. A node whose driver is still installing shows Not advertised yet - the labels are there but nvidia.com/gpu has no allocatable capacity, so nothing can be scheduled on it yet.

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Live telemetry

With a Prometheus metrics source connected, the Accelerator card reads the DCGM exporter the GPU operator ships and shows, per GPU: utilisation, framebuffer in use, temperature, power draw, SM clock, memory bandwidth, the last XID error if there is one, and the pod currently attached to the GPU. A GPU workloads list underneath names every pod on the node requesting a GPU resource, linked to its pod page. The queries match DCGM series on the node’s Hostname label (the GPU operator sets it from the node name), falling back to kubernetes_node and node for scrape configurations that relabel it. If Prometheus is connected but has no DCGM series for the node, the card says so rather than showing empty gauges - check that the exporter’s ServiceMonitor is being scraped.

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Conditions

One row per kubelet condition: a health dot, the condition, its reason and when it last changed. Pressure conditions (MemoryPressure, DiskPressure, PIDPressure, NetworkUnavailable) are healthy when False and a Problem when True; Ready is the other way round. Only a condition that needs attention shows its label and the kubelet’s message; the card’s subtitle says how many do.

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Host

Operating system, architecture, kernel and container runtime, every address the kubelet reports, the pod CIDR(s) and the cloud provider with its instance ID. Identifiers reveals the machine ID, system UUID, boot ID and full provider ID with one-click copy.

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Allocatable

Allocatable against capacity for every resource the node reports - CPU, memory, ephemeral storage, pods, huge pages and extended resources such as nvidia.com/gpu or MIG profiles - with a bar showing the share the scheduler can actually use.

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Scheduling

Whether the node is cordoned, and its taints with their effect (NoExecute is highlighted).

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Labels, annotations and cached images

Three collapsed panels at the end of the page, each with a count in its header:
  • Labels grouped by prefix (nvidia.com, feature.node.kubernetes.io, topology.kubernetes.io, …). Large groups start collapsed; type in Search labels to find a key or value across every group, and click a label to copy key=value.
  • Annotations, with copy and expand for long values.
  • Cached images - what the kubelet has pulled, largest first, with the total on disk in the header.

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Pods tab

Every pod scheduled on the node with phase, readiness, restarts and age, with bulk delete. The tab badge shows the pod count.

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Metrics tab

With a Prometheus metrics source connected: CPU, memory, disk and network usage over the selected time range. On a GPU node a GPU section follows with utilisation, memory used, power draw and temperature charts per GPU. Without a metrics source, the tab explains how to connect one.

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Manifest tab

The node’s full manifest, editable in place.