Kubernetes Ontology Access

Kubernetes Ontology Access

Guide users from zero to useful diagnosis with kubernetes-ontology.

This skill is the repository's onboarding playbook for three connected modes:

1. AI-agent automatic troubleshooting through stable daemon-backed queries.
2. CLI-driven topology and diagnostic inspection.
3. Human visual intervention through the topology viewer.

Prefer read-only, daemon-backed workflows. The project observes Kubernetes objects and builds an in-memory graph; it must not mutate observed workloads.

Operating Posture

Do not merely summarize the docs. Drive the user toward the next useful action:

• Identify the user's current state: no setup, existing daemon, CLI-only query, diagnostic request, viewer handoff, or source development.
• Choose the shortest path that satisfies the request.
• Give concrete commands the user or agent can run next, with safe defaults named inline.
• When command output is needed, ask for or run that command before moving to later steps.
• Keep cluster-changing actions explicit: ask for confirmation before running helm upgrade --install or any command that changes cluster resources.
• Do not require a repository checkout for CLI-only diagnostics against an already running daemon.

First Response Checklist

When this skill triggers, quickly establish:

• Whether the user is inside a local checkout of this repository.
• Target cluster context and logical cluster name.
• Desired namespaces for collection (contextNamespaces).
• Deployment path: release binary server + client for private clusters or short-lived local diagnosis, Helm + release CLI when cluster nodes can pull the image, source build for development.
• Whether the environment can reach GitHub Releases and whether cluster nodes can pull ghcr.io or an internal mirror.
• Diagnostic entry, if known: Pod or Workload, namespace, and name.
• Whether they want the viewer opened for human inspection.

If values are missing and a safe default exists, proceed with the default and name it. Ask only for values that are required and cannot be inferred, such as the target namespace/name for a diagnostic query.

Safety Model

Explain this once when onboarding a new user:

• Runtime collection is read-only against observed Kubernetes resources.
• Helm installs this project's own Deployment, Service, ServiceAccount, ConfigMap, viewer, and read-only RBAC.
• Release binary mode installs nothing in the cluster. It starts kubernetes-ontologyd on the host that has kubeconfig access, and optionally starts kubernetes-ontology-viewer on that host.
• The default RBAC includes get, list, and watch; Secret reads are enabled so uses_secret edges can be collected. Use --set rbac.readSecrets=false when Secret collection is not acceptable.
• Keep the HTTP API and viewer behind kubectl port-forward or a controlled private network. Do not expose them directly to the public internet.
• For short-lived diagnosis, tell the user exactly how to stop port-forwards, host-local binaries, and Helm resources after use.

Repository Pointers

When working from a checkout, read only the files needed for the current task:

• README.md or README.zh-CN.md for project overview.
• QUICKSTART.md for end-to-end setup and commands.
• AI_CONTRACT.md for downstream agent consumption rules.
• charts/kubernetes-ontology/values.yaml for Helm values.
• Makefile for local build, server, CLI, and viewer targets.

Recommended Onboarding Flow

Choose the deployment path from network constraints first:

• Use release binary server + client when the cluster is private, air-gapped, cannot pull public images, or the user wants no in-cluster footprint.
• Use Helm + release CLI when the cluster can pull the configured image, or the image has been mirrored to an internal registry.
• Use source build only for contributors or local code changes.

Only guide the user to clone the repository when the current path needs files from the checkout, such as the local Helm chart under charts/kubernetes-ontology, source development, or local viewer development. If the user only needs CLI queries against an existing daemon, skip the clone.

When a checkout is needed and the user does not already have one, use:

git clone https://github.com/Colvin-Y/kubernetes-ontology.git
cd kubernetes-ontology

If the user is not ready to deploy yet, first verify prerequisites and collect the target cluster, logical cluster name, and namespaces. Then return to the checkout step only when deploying the chart or using source-local commands.

1. Verify Prerequisites

Check or ask the user to check:

kubectl config current-context
kubectl get namespace

Check helm version only for the Helm path. For private environments, explicitly ask whether cluster nodes can pull ghcr.io/colvin-y/kubernetes-ontology or an internal mirror. If they cannot, prefer the release binary path.

If the user expects the agent to run commands, confirm before using any command that changes cluster resources, including helm upgrade --install.

2. Release Binary Server + Client

Use this path when the user wants a simple binary workflow or the cluster cannot pull the published image. A GitHub Release archive contains:

• kubernetes-ontologyd: the read-only server that talks to the Kubernetes API.
• kubernetes-ontology: the CLI client that talks to the server.
• kubernetes-ontology-viewer: optional local viewer.
• local/kubernetes-ontology.yaml.example: a config template.

Download or transfer the archive for the selected version and platform:

export KO_VERSION=v0.1.7
curl -LO "https://github.com/Colvin-Y/kubernetes-ontology/releases/download/${KO_VERSION}/kubernetes-ontology_${KO_VERSION}_linux_amd64.tar.gz"
tar -xzf "kubernetes-ontology_${KO_VERSION}_linux_amd64.tar.gz"
cd "kubernetes-ontology_${KO_VERSION}_linux_amd64"

Use linux_amd64, linux_arm64, darwin_amd64, darwin_arm64, or windows_amd64.zip for other hosts. If the private environment cannot access GitHub, tell the user to download the archive elsewhere and transfer it through their approved internal channel.

Release CLI binaries check GitHub Releases with a short best-effort timeout during normal use when version metadata is present. When a release CLI is already installed, prefer checking before longer troubleshooting sessions:

./kubernetes-ontology --version
./kubernetes-ontology --check-update

If a newer release is available and the environment permits downloading from GitHub, the user can update the CLI in place:

./kubernetes-ontology --update

Use --no-update-check or KUBERNETES_ONTOLOGY_SKIP_UPDATE_CHECK=1 for offline or tightly controlled scripts.

Create or adapt kubernetes-ontology.yaml:

cp local/kubernetes-ontology.yaml.example kubernetes-ontology.yaml

Then edit the kubeconfig path, logical cluster name, namespace scope, and any cluster-specific workload, controller, or CSI rules:

kubeconfig: /absolute/path/to/kubeconfig.yaml
cluster: your-logical-cluster
contextNamespaces:
  - default
  - kube-system
server:
  addr: 127.0.0.1:18080
bootstrapTimeout: 2m
streamMode: informer

Run the server in the foreground unless the user explicitly wants a background process:

./kubernetes-ontologyd --config ./kubernetes-ontology.yaml

If a background process is useful for a short session:

nohup ./kubernetes-ontologyd --config ./kubernetes-ontology.yaml > kubernetes-ontologyd.log 2>&1 &
echo $! > kubernetes-ontologyd.pid

Confirm readiness from another terminal:

./kubernetes-ontology --server "http://127.0.0.1:18080" --status

Optional local viewer:

./kubernetes-ontology-viewer --server "http://127.0.0.1:18080"

When done, stop foreground processes with Ctrl-C. For background processes:

kill "$(cat kubernetes-ontologyd.pid)"

If the viewer was backgrounded, kill that PID too. Remind the user to remove temporary logs, pid files, and copied kubeconfigs according to their local security policy.

3. Deploy The Helm Chart

Use a release version and image. If the user did not specify one, use the latest project release they selected or the version already present in the repository docs. Do not invent a future version.

export KO_VERSION=v0.1.7
export KO_IMAGE=ghcr.io/colvin-y/kubernetes-ontology

helm upgrade --install kubernetes-ontology ./charts/kubernetes-ontology \
  --namespace kubernetes-ontology \
  --create-namespace \
  --set image.repository="${KO_IMAGE}" \
  --set image.tag="${KO_VERSION}" \
  --set cluster="your-logical-cluster" \
  --set contextNamespaces='{default,kube-system}'

For private clusters, mirror the image to an internal registry and set KO_IMAGE to that mirror. If image mirroring is not available, use the release binary path instead.

For all namespaces, remove the --set contextNamespaces=... line and use the chart default empty list. For no Secret collection:

helm upgrade --install kubernetes-ontology ./charts/kubernetes-ontology \
  --namespace kubernetes-ontology \
  --reuse-values \
  --set rbac.readSecrets=false

Wait for rollout:

kubectl -n kubernetes-ontology rollout status deploy/kubernetes-ontology

The viewer rollout exists when viewer.enabled=true, which is the chart default:

kubectl -n kubernetes-ontology rollout status deploy/kubernetes-ontology-viewer

3. Port-Forward Server And Viewer

Use separate terminals or background sessions:

kubectl -n kubernetes-ontology port-forward svc/kubernetes-ontology 18080:18080

The viewer service exists when viewer.enabled=true, which is the chart default:

kubectl -n kubernetes-ontology port-forward svc/kubernetes-ontology-viewer 8765:8765

If the user disabled the viewer, expose only the server or re-enable the viewer later.

Default endpoints:

• Server: http://127.0.0.1:18080
• Viewer: http://127.0.0.1:8765

4. Download The CLI

Download kubernetes-ontology from GitHub Releases for the selected KO_VERSION. The repository release workflow packages kubernetes-ontology, kubernetes-ontologyd, and kubernetes-ontology-viewer under an archive root named kubernetes-ontology_${KO_VERSION}_${GOOS}_${GOARCH}. Choose the archive suffix by platform:

• macOS Apple Silicon: darwin_arm64.tar.gz
• macOS Intel: darwin_amd64.tar.gz
• Linux x86_64: linux_amd64.tar.gz
• Linux ARM64: linux_arm64.tar.gz
• Windows x86_64: windows_amd64.zip

Example for macOS Apple Silicon:

curl -LO "https://github.com/Colvin-Y/kubernetes-ontology/releases/download/${KO_VERSION}/kubernetes-ontology_${KO_VERSION}_darwin_arm64.tar.gz"
tar -tzf "kubernetes-ontology_${KO_VERSION}_darwin_arm64.tar.gz" | head
tar -xzf "kubernetes-ontology_${KO_VERSION}_darwin_arm64.tar.gz"
sudo install "kubernetes-ontology_${KO_VERSION}_darwin_arm64/kubernetes-ontology" /usr/local/bin/kubernetes-ontology

If the user is installing from a fork or custom release, inspect the archive contents first and adjust the install path to the actual extracted directory. If the user cannot use sudo, keep the binary in a local directory and invoke it by path.

After installation, run kubernetes-ontology --check-update when network access to GitHub Releases is allowed. Normal CLI calls also do this with a short best-effort timeout and print a stderr notice when a newer release exists.

5. Confirm The Daemon Is Ready

kubernetes-ontology --server "http://127.0.0.1:18080" --status

Continue only when status shows Ready: true or Phase: ready. List, entity, relation, expand, and diagnostic responses include lowercase freshness.ready metadata that agents can use after the daemon is serving queries. If the daemon is not ready, inspect rollout logs and retry status.

6. Cleanup For Short-Lived Use

For Helm path:

# Stop any foreground port-forward terminals with Ctrl-C first.
helm uninstall kubernetes-ontology --namespace kubernetes-ontology

Only delete the namespace if it was created exclusively for this install:

kubectl delete namespace kubernetes-ontology

For release binary path, stop kubernetes-ontologyd and any viewer process on the host. The binary path leaves no cluster-side resources to uninstall.

AI-Agent Automatic Troubleshooting

Use this flow when the user asks the agent to diagnose a workload or pod.

Pod Entry

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --machine-errors \
  --diagnose-pod \
  --namespace default \
  --name my-pod

Workload Entry

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --machine-errors \
  --diagnose-workload \
  --namespace default \
  --name my-deployment

Agent Reasoning Rules

• Treat the response as a bounded evidence graph, not complete cluster truth.
• Check schemaVersion, recipe, lanes, partial, warnings, degradedSources, budgets, rankedEvidence, and conflicts before forming a conclusion.
• Use managed_by_helm_release and installs_chart edges as Helm/package provenance when present, but describe them as label-derived evidence unless future exact manifest evidence is explicitly available.
• For "helm upgrade failed" requests, diagnose current cluster state even if the user lacks Helm CLI output. Say clearly that template, values, repository, client, hook, and --atomic rollback causes need user-provided Helm stderr/status/history.
• When helm_cli_output_not_observed or helm_manifest_evidence_not_collected appears, include it in the answer before naming a root cause.
• Index nodes by canonicalId; join edges by from and to.
• Prefer edge/node attributes and provenance over explanation text for hard conclusions.
• Use rankedEvidence first for suspicion ranking, then explanation text for narrative.
• If budgets.truncated=true, say which budget was hit and suggest narrowing namespace/depth before raising graph caps.
• If evidence is missing, report that it is missing from the current graph slice rather than claiming the object does not exist anywhere.
• Prefer asserted and observed facts before inferred shortcuts.
• Preserve conflicts in the user-facing answer instead of choosing one owner or cause silently.
• For contract details, consult AI_CONTRACT.md.

Current limits to keep visible in agent reasoning:

• rankedEvidence currently starts with Event evidence; not every signal type is ranked yet.
• explanation content is useful but best-effort narrative.
• Traversal policy can hide valid facts outside the selected graph slice.
• Diagnostic budgets can intentionally truncate the graph. Treat partial=true as a correctness constraint, not a cosmetic warning.
• CSI component correlation is configurable with csiComponentRules; no driver-specific component inference runs unless a matching rule is configured.
• A missing edge in one diagnostic response should be treated as missing evidence in that slice, not global absence.

Agent Output Template

For diagnostic answers, respond with:

## Summary
[1-3 sentence diagnosis]

## Evidence
- [partial/warning/budget/conflict status, if present]
- [rankedEvidence item, if present]
- [node/edge/provenance fact]
- [node/edge/provenance fact]

## Next Queries
```bash
[one or two targeted CLI commands]
```

## Human Viewer
Open http://127.0.0.1:8765 and load the same Pod or Workload diagnostic graph.

Avoid recommending cluster mutations unless the user explicitly asks for remediation and the evidence supports it.

CLI Query Playbook

Status:

kubernetes-ontology --server "http://127.0.0.1:18080" --status

List entities:

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --list-entities \
  --entity-kind Pod \
  --namespace default \
  --limit 20

Resolve an entity and capture entity.entityGlobalId:

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --resolve-entity \
  --entity-kind Pod \
  --namespace default \
  --name my-pod

Diagnose a Helm release after a failed upgrade:

Use this Incident Context Pack flow only with v0.1.6 or newer.

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --diagnose-helm-release \
  --namespace default \
  --name my-release \
  --recipe helm-upgrade-runtime-failure

Use this when the user knows the release name but does not have the original Helm CLI output. Follow the returned rankedEvidence, warnings, degradedSources, and release-owned Workload/Pod nodes. If the response only shows Helm metadata and no rollout blocker, ask for helm upgrade stderr, helm status, or helm history.

Expand one entity:

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --expand-entity \
  --entity-id 'your/entityGlobalId' \
  --expand-depth 1 \
  --limit 100

List filtered relations:

kubernetes-ontology \
  --server "http://127.0.0.1:18080" \
  --list-filtered-relations \
  --from 'your/entityGlobalId' \
  --relation-kind scheduled_on \
  --limit 50

Common stable relation kinds include:

• controlled_by
• owns_pod
• scheduled_on
• selects_pod
• uses_config_map
• uses_secret
• uses_service_account
• bound_by_role_binding
• mounts_pvc
• bound_to_pv
• managed_by_helm_release
• installs_chart
• reported_by_event
• affected_by_webhook
• managed_by_csi_controller
• served_by_csi_node_agent

Human Visual Troubleshooting

Use the viewer when the user wants to inspect topology manually, validate an agent conclusion, compare graph branches, or export a visible subgraph.

Steps:

1. Port-forward the viewer service.
2. Open http://127.0.0.1:8765.
3. Load live topology or a focused Pod/Workload diagnostic graph.
4. Select nodes to inspect attributes, provenance, and edge kinds.
5. Expand one hop when a relation needs more context.
6. Export the visible graph as JSON when the agent needs to continue from the exact human-inspected state.

The Helm chart enables the viewer by default. If the user installed with viewer.enabled=false, skip the viewer rollout and port-forward commands, or enable it with:

helm upgrade --install kubernetes-ontology ./charts/kubernetes-ontology \
  --namespace kubernetes-ontology \
  --reuse-values \
  --set viewer.enabled=true

If using the local development viewer instead of Helm:

make visualize

Or use the dependency-free release viewer:

kubernetes-ontology-viewer --server "http://127.0.0.1:18080"

Runtime Footprint And Cleanup

Always make the runtime footprint explicit during onboarding:

• Release binary path starts kubernetes-ontologyd on the host, and optionally kubernetes-ontology-viewer. It creates no Kubernetes resources.
• Helm path creates Kubernetes Deployments for the server and viewer, Services, a ServiceAccount, a ConfigMap, and read-only ClusterRole/ClusterRoleBinding resources. It may also require kubectl port-forward processes on the user's workstation.
• Source path starts local make serve and optional make visualize processes from the checkout.

For short-lived use, tell the user how to clean up before ending the session:

# Binary path, when backgrounded:
kill "$(cat kubernetes-ontologyd.pid)"

# Helm path:
helm uninstall kubernetes-ontology --namespace kubernetes-ontology

# Source path:
# stop the foreground make serve / make visualize terminals with Ctrl-C

Only suggest deleting the kubernetes-ontology namespace when it was created solely for this install and the user confirms no other resources should remain.

Source Development Path

Use this path for contributors or local code changes:

make build build-daemon build-viewer
cp local/kubernetes-ontology.yaml.example local/kubernetes-ontology.yaml

Edit local/kubernetes-ontology.yaml, then run in separate terminals:

make serve
make visualize

CLI checks:

make status-server
make list-entities-server ENTITY_KIND=Pod NAMESPACE=default LIMIT=20
make diagnose-pod-server NAMESPACE=default NAME=my-pod

For code changes, verify:

make verify
make live-check NAMESPACE=default NAME=my-pod

Troubleshooting The Onboarding

If entry not found:

• Check exact namespace/name.
• List available entities in the namespace.
• Confirm contextNamespaces includes the target namespace, or is empty for all namespaces.

If status is not ready:

• Check the server rollout and pod logs.
• Confirm the ServiceAccount has read access to the needed resources.
• Increase bootstrapTimeout for large or slow clusters.

If graph evidence seems too small:

• Increase diagnostic depth with --max-depth or --storage-max-depth.
• Use --expand-terminal-nodes for deliberate fan-out.
• Expand selected viewer nodes one hop instead of loading the whole cluster.

If the viewer cannot load data:

• Confirm both port-forwards are running.
• Check http://127.0.0.1:18080/status.
• Restart the viewer port-forward and reload the page.

Source: Colvin-Y/kubernetes-ontology — distributed by TomeVault.