Cube Core MicroK8s Operator

A production-oriented Kubernetes operator for self-hosted Cube Core, with Proxmox/MicroK8s infrastructure, selectable Go and Kopf controllers, and a reproducible Kind telemetry demo. Go/controller-runtime is the default production implementation. The Python/Kopf implementation is a separately packaged, single-replica alternative for the same CubeCluster CRD.

One controller only: never run the Go and Kopf controllers against the same cluster or resource at the same time. They own identical resources and status fields, so concurrent operation causes reconciliation races.

The API is platform.cube.dev/v1alpha1; test upgrades and recovery procedures before production use.

System architecture

Proxmox, MicroK8s, operator, and Cube

Terraform preserves the original Proxmox/MicroK8s infrastructure boundary. Application deployment remains a separate Kubernetes lifecycle.

flowchart TB
  Internet((Consumers)) -->|HTTPS / REST| Edge[Router / firewall / TLS ingress]
  DNS[ESDDNS-managed DNS] -. resolves .-> Edge
  Edge --> LB[MetalLB service IP]

  subgraph PVE[Proxmox VE]
    TF[Terraform + cloud-init] --> VM1[MicroK8s VM 1]
    TF --> VM2[MicroK8s VM 2]
    TF --> VM3[MicroK8s VM 3]
    VM1 <-->|dqlite HA| VM2
    VM2 <-->|dqlite HA| VM3
    VM3 <-->|dqlite HA| VM1
  end

  LB --> API[Cube API service]
  OP[Go controller-runtime<br/>or Python/Kopf] -->|reconciles| API
  OP --> RW[Refresh worker]
  OP --> CS[Cube Store router/workers]
  API --> DB[(Data source)]
  API --> CS
  RW --> DB
  RW --> CS
  CS --> RS[(S3 or shared PVC)]

MetalLB provides LAN reachability, not automatic public exposure. DNS, edge port forwarding, ingress, certificates, and firewall policy remain explicit operator responsibilities.

Reconciliation and ownership

Both controller implementations enforce the same desired topology and owner references. The Ready condition requires API, refresh worker, and Cube Store replicas to be ready.

flowchart LR
  CR[CubeCluster] --> V{Validate references,<br/>storage, replicas}
  CM[Model ConfigMap] --> V
  SEC[Configuration Secret] --> V
  PVC[Existing PVC / S3 Secret] --> V
  V -->|valid| R[Reconcile desired objects]
  V -->|invalid| F[Ready=False<br/>InvalidConfiguration]
  R --> API[API Deployment + Service + PDB]
  R --> REF[Refresh Deployment]
  R --> STORE[Cube Store Deployment<br/>or router/worker StatefulSets]
  R --> NP[Cube Store NetworkPolicy]
  API --> S{All expected<br/>replicas ready?}
  REF --> S
  STORE --> S
  S -->|yes| T[Ready=True]
  S -->|no| P[Ready=False<br/>Progressing]
  CR -. ownerReference / GC .-> API
  CR -. ownerReference / GC .-> REF
  CR -. ownerReference / GC .-> STORE
  CR -. ownerReference / GC .-> NP

Cube query and refresh data flow

sequenceDiagram
  participant Client as REST client
  participant API as Cube API
  participant DB as Data source
  participant Refresh as Refresh worker
  participant Store as Cube Store
  participant Remote as S3 / shared remote storage

  Client->>API: GET /cubejs-api/v1/meta
  API-->>Client: cubes, measures, dimensions
  Client->>API: POST /cubejs-api/v1/load
  API->>Store: read pre-aggregation/cache
  alt cache or pre-aggregation hit
    Store-->>API: query result
  else source query required
    API->>DB: generated SQL
    DB-->>API: source rows
  end
  API-->>Client: JSON data
  loop refresh schedule
    Refresh->>DB: build/refresh data
    Refresh->>Store: ingest pre-aggregation
    Store->>Remote: persist metadata/data
  end

Build and verify

Prerequisites:

Go 1.24+, Python 3, Kustomize, and Terraform 1.7+.
Docker, Kind, kubectl, curl, and jq for the demo.
Either an amd64 or Apple Silicon arm64 Docker host. kind-up.sh detects the Kind node architecture and selects the matching digest-pinned Cube Store image (v1.7.20 for amd64, arm64v8 for arm64).

make verify                 # Go tests/vet, Python tests, manifests, TF, shellcheck
make build                  # Go production-default binary
make test                   # Go and focused Kopf resource tests
make manifests-go           # render default Go installation
make manifests-kopf         # render optional Kopf installation

docker build -t cube-operator:v0.1.0 .
docker build -f python/Dockerfile -t cube-operator-kopf:v0.1.0 .

All upstream runtime images are versioned and digest-pinned. Local operator tags identify builds from this tree; publish them to a trusted registry and set the corresponding Kustomize image before deploying outside Kind.

Deploy or switch controllers

Deploy Go (default)

Set the registry image in an overlay or update config/default/kustomization.yaml, then render and review before applying:

kustomize build config/default > /tmp/cube-operator-go.yaml
kubectl apply --server-side --dry-run=server -f /tmp/cube-operator-go.yaml
kubectl apply -f /tmp/cube-operator-go.yaml
kubectl -n cube-system rollout status deployment/cube-operator

The Go manager uses Kubernetes Lease leader election and is the recommended production path.

Deploy Kopf instead

First stop the Go manager; wait for deletion before creating Kopf:

kubectl -n cube-system delete deployment cube-operator --ignore-not-found --wait=true
kustomize build config/kopf > /tmp/cube-operator-kopf.yaml
kubectl apply --server-side --dry-run=server -f /tmp/cube-operator-kopf.yaml
kubectl apply -f /tmp/cube-operator-kopf.yaml
kubectl -n cube-system rollout status deployment/cube-operator-kopf

Kopf runs one replica with --standalone. It does not provide the Go manager's multi-replica leader-election path.

Switch safely back to Go

kubectl -n cube-system delete deployment cube-operator-kopf --ignore-not-found --wait=true
kubectl apply -f /tmp/cube-operator-go.yaml
kubectl -n cube-system rollout status deployment/cube-operator
kubectl -n cube-system get deploy cube-operator cube-operator-kopf --ignore-not-found

stateDiagram-v2
  [*] --> NoController
  NoController --> GoActive: apply config/default
  NoController --> KopfActive: apply config/kopf
  GoActive --> NoController: delete Go Deployment and wait
  KopfActive --> NoController: delete Kopf Deployment and wait
  GoActive --> GoActive: leader-elected reconciliation
  KopfActive --> KopfActive: standalone reconciliation
  state "FORBIDDEN: reconciliation race" as GoAndKopf
  GoActive --> GoAndKopf: do not apply Kopf concurrently
  KopfActive --> GoAndKopf: do not apply Go concurrently

Configure Cube Core

Namespace, model, and configuration Secret

The operator reads references but never creates credentials. The following creates a minimal PostgreSQL configuration without committing a Secret:

kubectl create namespace cube --dry-run=client -o yaml | kubectl apply -f -
kubectl -n cube create configmap cube-model \
  --from-file=KubernetesTelemetry.yml=demo/kind/model/KubernetesTelemetry.yml \
  --dry-run=client -o yaml | kubectl apply -f -

read -rsp 'Database password: ' CUBE_DB_PASS; echo
read -rsp 'Cube API signing secret: ' CUBE_API_SECRET; echo
kubectl -n cube create secret generic cube-configuration \
  --from-literal=CUBEJS_DB_TYPE=postgres \
  --from-literal=CUBEJS_DB_HOST=postgres.example.internal \
  --from-literal=CUBEJS_DB_PORT=5432 \
  --from-literal=CUBEJS_DB_NAME=analytics \
  --from-literal=CUBEJS_DB_USER=cube \
  --from-literal=CUBEJS_DB_PASS="$CUBE_DB_PASS" \
  --from-literal=CUBEJS_API_SECRET="$CUBE_API_SECRET" \
  --dry-run=client -o yaml | kubectl apply -f -
unset CUBE_DB_PASS CUBE_API_SECRET

Use External Secrets, Sealed Secrets, or your platform's secret manager in production. Do not put values in Git, shell history, Terraform variables, or shared state.

Production S3 example

Prefer workload identity when available. If static S3 credentials are required, create the referenced Secret out of band:

kubectl -n cube create secret generic cubestore-s3 \
  --from-literal=CUBESTORE_AWS_ACCESS_KEY_ID="$AWS_ACCESS_KEY_ID" \
  --from-literal=CUBESTORE_AWS_SECRET_ACCESS_KEY="$AWS_SECRET_ACCESS_KEY" \
  --dry-run=client -o yaml | kubectl apply -f -

apiVersion: platform.cube.dev/v1alpha1
kind: CubeCluster
metadata: {name: analytics, namespace: cube}
spec:
  image: cubejs/cube:v1.7.20@sha256:7f14f4be9f3303afe48a16584480c8a9dc15f44c13daf66c2a5b31019025b71a
  modelConfigMap: cube-model
  configurationSecret: cube-configuration
  api: {replicas: 2}
  refreshWorker: {replicas: 1}
  cubeStore:
    mode: clustered
    image: cubejs/cubestore:v1.7.20@sha256:cd5fe68049204640704a6412a39e7a09eb391fc70890577dd21b5480d85cb219
    workers: 2
    remoteStorage:
      type: s3
      s3: {bucket: company-cube-prod, region: us-west-2, secretRef: cubestore-s3}
    scratch: {size: 100Gi}
  service: {type: LoadBalancer}

Tune resources from observed workload usage; the fuller starting point is config/samples/production.yaml.

Existing PVC example

PVC remote storage is most appropriate for a single Cube Store. A clustered topology requires a genuinely shared, concurrently mountable filesystem; a node-local or ordinary ReadWriteOnce claim is not sufficient.

apiVersion: v1
kind: PersistentVolumeClaim
metadata: {name: cubestore-remote, namespace: cube}
spec:
  accessModes: [ReadWriteOnce]
  storageClassName: durable-block
  resources: {requests: {storage: 100Gi}}
---
apiVersion: platform.cube.dev/v1alpha1
kind: CubeCluster
metadata: {name: analytics, namespace: cube}
spec:
  modelConfigMap: cube-model
  configurationSecret: cube-configuration
  api: {replicas: 2}
  refreshWorker: {replicas: 1}
  cubeStore:
    mode: single
    remoteStorage:
      type: persistentVolume
      persistentVolume: {existingClaim: cubestore-remote}
    scratch: {size: 20Gi}
  service: {type: ClusterIP}

Kind telemetry demo

The disposable demo samples Kubernetes Nodes and Pods, writes observations to PostgreSQL, and queries them through Cube Core.

flowchart LR
  KAPI[Kubernetes API] -->|read-only list Nodes/Pods| Collector[Telemetry collector]
  Collector -->|COPY observations| PG[(PostgreSQL)]
  Model[Generated model ConfigMap] --> Cube[Cube API]
  PG --> Cube
  Cube --> Store[Single Cube Store + PVC]
  Test[kind-e2e.sh] -->|/readyz + /livez| Cube
  Test -->|GET /cubejs-api/v1/meta| Cube
  Test -->|POST /cubejs-api/v1/load| Cube
  Cube -->|telemetry count| Test

Scripts always pass the kind-cube-demo context, generate credentials in Kubernetes Secrets, reuse an existing cluster safely, and select an amd64 or arm64 digest based on .status.nodeInfo.architecture.

make kind-up              # Go controller (default)
make kind-e2e
make kind-down

make kind-up-kopf         # same demo, Kopf controller
make kind-e2e
make kind-down

kind-e2e verifies /readyz, /livez, /cubejs-api/v1/meta, and POST /cubejs-api/v1/load, including bounded retries for Continue wait. Port 4000 is bound locally for the lifetime of the Kind cluster.

Use the Cube Core REST API

Health endpoints are unprefixed and unauthenticated. Core Data API calls use a Cube JWT directly in Authorization—there is no Bearer prefix.

kubectl -n cube port-forward service/analytics-api 4000:4000
# In another shell:
export CUBE_CORE_URL=http://127.0.0.1:4000
curl --fail --silent "$CUBE_CORE_URL/readyz" | jq .
curl --fail --silent "$CUBE_CORE_URL/livez" | jq .

For this example, mint a five-minute HS256 JWT from the Kubernetes Secret. Avoid putting production secrets or tokens on command lines or in logs:

API_SECRET=$(kubectl -n cube get secret cube-configuration \
  -o 'go-template={{index .data "CUBEJS_API_SECRET" | base64decode}}')
export CUBE_CORE_TOKEN=$(CUBE_API_SECRET="$API_SECRET" python3 <<'PY'
import base64, hashlib, hmac, json, os, time
enc = lambda b: base64.urlsafe_b64encode(b).rstrip(b"=")
head = enc(json.dumps({"alg":"HS256","typ":"JWT"}, separators=(",", ":")).encode())
body = enc(json.dumps({"iat":int(time.time()),"exp":int(time.time())+300}, separators=(",", ":")).encode())
signed = head + b"." + body
print((signed + b"." + enc(hmac.new(os.environ["CUBE_API_SECRET"].encode(), signed, hashlib.sha256).digest())).decode())
PY
)
unset API_SECRET

Inspect metadata, then query only member names returned by metadata:

curl --fail --silent --show-error --max-time 30 \
  -H "Authorization: $CUBE_CORE_TOKEN" \
  "$CUBE_CORE_URL/cubejs-api/v1/meta" | jq '.cubes[].name'

curl --fail --silent --show-error --max-time 95 \
  -H "Authorization: $CUBE_CORE_TOKEN" \
  -H 'Content-Type: application/json' \
  --data '{"query":{"measures":["KubernetesTelemetry.count"],"limit":10}}' \
  "$CUBE_CORE_URL/cubejs-api/v1/load" | jq .

unset CUBE_CORE_TOKEN

REST operational contract

flowchart LR
  Health[Unauthenticated health] --> Ready[/readyz/]
  Health --> Live[/livez/]
  Token[Short-lived Cube JWT<br/>Authorization: TOKEN] --> Core[Self-hosted Core Data API]
  Core --> Meta[/cubejs-api/v1/meta/]
  Core --> Load[/cubejs-api/v1/load/]
  Load --> Retry{Continue wait?}
  Retry -->|yes, bounded delay| Load
  Retry -->|no| Result[Consume .data or report .error]

Agent integrations

Local self-hosted Cube Core skill

The project-local operating-cube-core skill uses only the self-hosted Core Data REST API. Provide CUBE_CORE_URL and a short-lived CUBE_CORE_TOKEN, then use prompts such as:

“Use operating-cube-core to verify readiness and list available cubes.”
“Inspect metadata first, then query Kubernetes telemetry counts by namespace.”
“Diagnose this Continue wait response with bounded retries; do not print my token.”

It intentionally cannot deploy Cube, edit model files, administer users, or manage Cube Cloud content.

Optional official Cube Cloud skills

The official cube-js/cube-agent-skills drive the current cube CLI and Cube Cloud platform APIs. They do not operate local Cube Core. Use them only for a separate Cube Cloud tenant:

# Agent Skills-compatible clients; review upstream instructions before install.
npx skills add cube-js/cube-agent-skills

# Install the official Cube CLI, optionally pinning CUBE_VERSION in automation.
curl -fsSL https://raw.githubusercontent.com/cube-js/cube/master/install-cli.sh | sh
cube login --url https://TENANT.cubecloud.dev

# Headless Cloud alternative:
export CUBE_API_URL=https://TENANT.cubecloud.dev
export CUBE_API_KEY='sk-...'
cube deployments list

Do not point CUBE_API_URL at the local service expecting Cloud control-plane operations.

flowchart TB
  Agent[Coding agent]
  Agent --> LocalSkill[Project operating-cube-core skill]
  LocalSkill -->|Core JWT| LocalAPI[Self-hosted Cube Core<br/>meta + load only]
  Agent --> Official[Official cube-agent-skills]
  Official --> CLI[Cube CLI]
  CLI -->|Cloud API key / login| Cloud[Cube Cloud platform APIs]
  LocalAPI -. no Cloud control plane .- Cloud

See agent integration for the exact boundary.

Storage, network, and security

flowchart TB
  subgraph Public[External trust boundary]
    User[API client] -->|TLS| Ingress[Ingress / LoadBalancer]
  end
  subgraph Namespace[Cube namespace]
    Ingress --> API[Cube API :4000]
    Secret[Configuration Secret] --> API
    Secret --> Refresh[Refresh worker]
    Config[Model ConfigMap] --> API
    Config --> Refresh
    API -->|NetworkPolicy allowed| Store[Cube Store :3030/:9001/:9999]
    Refresh -->|NetworkPolicy allowed| Store
    Store --> Scratch[(Ephemeral /cube/data<br/>size-limited emptyDir)]
  end
  Store -->|restricted egress| S3[(S3 shared durable storage)]
  Store -->|alternative| SharedPVC[(Existing shared PVC)]
  API -->|restricted egress| DB[(Data source)]
  Refresh -->|restricted egress| DB
  Operator[Controller SA] -->|write owned workloads| Namespace
  Operator -->|read references only| Secret

Cube Store has no external Service. Its ingress NetworkPolicy allows only pods belonging to the same Cube instance.
Scratch space is ephemeral emptyDir; scratch.size is a limit, not durable capacity or a reservation.
The operator does not provision, encrypt, or back up remote storage.
Containers use RuntimeDefault seccomp, drop capabilities, and disable privilege escalation where compatible. Add admission policy and image verification for your environment.
Add default-deny egress with explicit DNS, database, S3, and monitoring destinations; terminate TLS at a controlled ingress.
RBAC permits writes to owned workload kinds, reads of referenced ConfigMaps/Secrets/PVCs, events, and Leases for Go leader election.

Proxmox and MicroK8s

cp terraform.tfvars.example terraform.tfvars
export TF_VAR_proxmox_api_token='terraform@pve!cube=REPLACE_ME'
terraform init
terraform validate
terraform plan -out=tfplan
terraform apply tfplan

export SSH_PRIVATE_KEY="$HOME/.ssh/id_ed25519"
export METALLB_ADDRESS_POOL="192.168.1.200-192.168.1.220"
./scripts/bootstrap-microk8s.sh
export KUBECONFIG="$PWD/kubeconfig"
kubectl get nodes -o wide

Bootstrap waits for cloud-init, joins missing nodes, enables DNS, hostpath storage, Helm and optional MetalLB, then writes a mode-0600 kubeconfig. Three nodes enable MicroK8s HA. VM deletion protection defaults on. Before deliberate destruction, back up data, set protect_vms=false, apply, and review a destroy plan. Hostpath volumes are not durable across node loss.

Publish through OperatorHub and OLM

This project is not currently published on OperatorHub. An OLM release should package the production-default Go controller; Kopf remains a separately selected deployment, not a second controller in the same installation.

For each release, use Operator SDK's bundle workflow to generate a CSV and CRD bundle from config/, then review rather than blindly accepting generated metadata:

operator-sdk generate kustomize manifests -q
make bundle IMG=ghcr.io/ORG/cube-operator:vX.Y.Z VERSION=X.Y.Z \
  CHANNELS=stable DEFAULT_CHANNEL=stable
operator-sdk bundle validate ./bundle
operator-sdk scorecard ./bundle
docker build -f bundle.Dockerfile -t ghcr.io/ORG/cube-operator-bundle:vX.Y.Z .

The CSV must include accurate alm-examples, categories, capabilities, containerImage, description, repository/support links, provider and named maintainers; add a base64 SVG or PNG icon with the matching media type. Declare only install modes actually tested (AllNamespaces is the intended Go manager mode), and keep owned CRD versions, permissions, image digests, channels, upgrade graph, and replacement metadata consistent.

Push the signed controller and bundle images to a public immutable registry, record digests, generate SBOM/provenance, and verify signatures in CI. Test the published bundle on a clean Kind cluster with OLM before submission:

kind create cluster --name cube-olm
operator-sdk olm install
docker push ghcr.io/ORG/cube-operator:vX.Y.Z
docker push ghcr.io/ORG/cube-operator-bundle:vX.Y.Z
operator-sdk run bundle ghcr.io/ORG/cube-operator-bundle:vX.Y.Z --timeout 10m
kubectl get csv -A
kubectl apply -f config/samples/production.yaml
operator-sdk cleanup cube-microk8s-operator
kind delete cluster --name cube-olm

For catalog testing, build and push a file-based catalog with opm init, opm render, opm validate, and opm generate dockerfile, then install a CatalogSource and Subscription on the same clean Kind/OLM environment. Finally fork the appropriate k8s-operatorhub/community-operators repository, add the validated version under its package directory, run that repository's required tests, and submit a PR with release and test evidence. Publication occurs only after the community review and merge.

Troubleshooting

Symptom	Checks and corrective action
`Ready=False, InvalidConfiguration`	Run `kubectl describe cubecluster -n NAMESPACE NAME`; verify the model ConfigMap, configuration Secret, PVC/S3 fields, replica counts, and scratch quantity.
`Ready=False, Progressing`	Inspect the condition message, then `kubectl get pods -n NAMESPACE` and logs for API, refresh, and Cube Store. Every component must be ready.
API probe fails	Call `/readyz` and `/livez`; readiness includes the default data-source connection. Verify Secret values, DNS, NetworkPolicy, and database TLS.
Cube Store worker never becomes ready	Workers are probed on TCP 9001; routers/single stores on 3030. Check selected image architecture and Cube Store environment.
`exec format error` in Kind	Re-run `kind-up.sh`; it patches `arm64v8@sha256:d925…` for arm64 and `v1.7.20@sha256:cd5…` for amd64. Confirm with `kubectl -n cube-demo get cube telemetry -o jsonpath='{.spec.cubeStore.image}'`.
REST returns `403`	Supply a valid Cube JWT directly in `Authorization` without `Bearer`; check expiry and signing secret.
REST returns `Continue wait`	Retry the identical request with a bounded delay; inspect API/refresh/Cube Store logs if it never resolves.
Controller fields flap	Ensure only one of `cube-operator` and `cube-operator-kopf` exists. Stop both, then deploy exactly one.
Kind port 4000 is busy	Stop the conflicting process or delete the existing Kind cluster with `make kind-down`; the demo mapping is intentionally fixed.
Terraform destroy is blocked	Protection is intentional. Back up data, set and apply `protect_vms=false`, then review `terraform plan -destroy`.

Useful commands:

kubectl get cubeclusters -A
kubectl -n cube get cubecluster analytics -o yaml
kubectl -n cube get deploy,statefulset,service,pdb,networkpolicy
kubectl -n cube logs deployment/analytics-api
kubectl -n cube-system logs deployment/cube-operator       # Go
kubectl -n cube-system logs deployment/cube-operator-kopf  # Kopf

Name		Name	Last commit message	Last commit date
.agents/skills/operating-cube-core		.agents/skills/operating-cube-core
api/v1alpha1		api/v1alpha1
cmd/manager		cmd/manager
config		config
demo/kind		demo/kind
docs		docs
internal		internal
python		python
scripts		scripts
.gitignore		.gitignore
.terraform.lock.hcl		.terraform.lock.hcl
Dockerfile		Dockerfile
Makefile		Makefile
README.md		README.md
cloud-init.yaml.tftpl		cloud-init.yaml.tftpl
go.mod		go.mod
go.sum		go.sum
main.tf		main.tf
outputs.tf		outputs.tf
terraform.tfvars.example		terraform.tfvars.example
variables.tf		variables.tf
versions.tf		versions.tf

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Cube Core MicroK8s Operator

Contents

System architecture

Proxmox, MicroK8s, operator, and Cube

Reconciliation and ownership

Cube query and refresh data flow

Build and verify

Deploy or switch controllers

Deploy Go (default)

Deploy Kopf instead

Switch safely back to Go

Configure Cube Core

Namespace, model, and configuration Secret

Production S3 example

Existing PVC example

Kind telemetry demo

Use the Cube Core REST API

REST operational contract

Agent integrations

Local self-hosted Cube Core skill

Optional official Cube Cloud skills

Storage, network, and security

Proxmox and MicroK8s

Publish through OperatorHub and OLM

Troubleshooting

Production checklist

About

Releases

Packages

Contributors

Languages

Latest commit

History

Folders and files

Repository files navigation

Cube Core MicroK8s Operator

Contents

System architecture

Proxmox, MicroK8s, operator, and Cube

Reconciliation and ownership

Cube query and refresh data flow

Build and verify

Deploy or switch controllers

Deploy Go (default)

Deploy Kopf instead

Switch safely back to Go

Configure Cube Core

Namespace, model, and configuration Secret

Production S3 example

Existing PVC example

Kind telemetry demo

Use the Cube Core REST API

REST operational contract

Agent integrations

Local self-hosted Cube Core skill

Optional official Cube Cloud skills

Storage, network, and security

Proxmox and MicroK8s

Publish through OperatorHub and OLM

Troubleshooting

Production checklist

About

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