Local Laptop Kubernetes Control with FastAPI

This guide uses your local manifest deploy/local-laptop.yaml and a lightweight server server/local_laptop_control.py.

1) Deploy local workloads

kubectl apply -f deploy/local-laptop.yaml
kubectl get deploy -n prod-sre

Expected deployments:

auth
cart
catalog
checkout
payments

2) Set required environment variables

The controller requires KUBECONFIG and ANTIATROPOS_WORKLOAD_MAP.

$env:KUBECONFIG = "$HOME/.kube/config"
$env:ANTIATROPOS_K8S_NAMESPACE = "prod-sre"
$env:ANTIATROPOS_MIN_REPLICAS = "1"
$env:ANTIATROPOS_MAX_REPLICAS = ""   # empty => unbounded scale-up
$env:ANTIATROPOS_SCALE_STEP = "3"
$env:ANTIATROPOS_WORKLOAD_MAP = '{"node-0":{"deployment":"payments","namespace":"prod-sre"},"node-1":{"deployment":"checkout","namespace":"prod-sre"},"node-2":{"deployment":"catalog","namespace":"prod-sre"},"node-3":{"deployment":"cart","namespace":"prod-sre"},"node-4":{"deployment":"auth","namespace":"prod-sre"}}'

If you already have these in .env, load them first.

3) Start lightweight FastAPI server

uvicorn server.local_laptop_control:app --host 0.0.0.0 --port 8010

4) Validate server health

Invoke-RestMethod http://localhost:8010/health

Check:

is_mock should be False
mapped_targets should include node-0..node-4

5) Let your agent execute actions

The server accepts POST /step with:

action_type: NO_OP | SCALE_UP | SCALE_DOWN | REROUTE_TRAFFIC | SHED_LOAD
target_node_id: node-*
parameter: float

Example:

Invoke-RestMethod -Method Post -Uri http://localhost:8010/step -ContentType "application/json" -Body '{"action_type":"SCALE_UP","target_node_id":"node-3","parameter":0.6}'

6) Verify Kubernetes effect

kubectl get deploy cart -n prod-sre
kubectl get deploy -n prod-sre

Notes

This controller is intentionally minimal and does not provide simulator rewards.
It is suitable for direct action execution tests from your agent.
If you need OpenEnv-compatible /reset + /step + reward loop, use server/app.py in aws mode.