deer-flow/docker/provisioner/README.md

DeerFlow Sandbox Provisioner

The Sandbox Provisioner is a FastAPI service that dynamically manages sandbox Pods in Kubernetes. It provides a REST API for the DeerFlow backend to create, monitor, and destroy isolated sandbox environments for code execution.

Architecture

┌────────────┐  HTTP  ┌─────────────┐  K8s API  ┌──────────────┐
│  Backend   │ ─────▸ │ Provisioner │ ────────▸ │  Host K8s    │
│  (gateway/ │        │   :8002     │           │  API Server  │
│ langgraph) │        └─────────────┘           └──────┬───────┘
└────────────┘                                          │ creates
                                                        │
                          ┌─────────────┐         ┌────▼─────┐
                          │   Backend   │ ──────▸ │  Sandbox │
                          │ (NodePort   │ or DNS  │  Pod(s)  │
                          │  /ClusterIP)│         └──────────┘
                          └─────────────┘

How It Works

1. Backend Request: When the backend needs to execute code, it sends a POST /api/sandboxes request with a sandbox_id, thread_id, and optional user_id.

2. Pod Creation: The provisioner creates a dedicated Pod in the deer-flow namespace with:

   • The sandbox container image (all-in-one-sandbox)
   • HostPath volumes mounted for:
     • /mnt/skills/{public,custom,legacy} → Read-only enabled-only skill projections
     • /mnt/user-data → Read-write access to thread-specific data
   • Resource limits (CPU, memory, ephemeral storage)
   • Readiness/liveness probes

3. Service Creation: A Service is created to expose the Pod. By default this is a NodePort Service for Docker Compose compatibility. Set SANDBOX_SERVICE_TYPE=ClusterIP when the backend runs inside the Kubernetes cluster.

4. Access URL: In NodePort mode, the provisioner returns http://{NODE_HOST}:{NodePort}. In ClusterIP mode, it returns a Kubernetes service DNS URL like http://sandbox-{sandbox_id}-svc.{namespace}.svc.cluster.local:8080.

5. Cleanup: When the session ends, DELETE /api/sandboxes/{sandbox_id} removes both the Pod and Service.

The sandbox business endpoints are implemented as synchronous FastAPI handlers because the Kubernetes Python client used here is synchronous. Starlette runs sync handlers in its worker pool, keeping create/read/list/delete K8s API calls and service access polling off the ASGI event-loop thread. Keep /health lightweight; do not move the sandbox CRUD handlers back to async def unless the K8s client path is also made async or explicitly offloaded.

Requirements

Host machine with a running Kubernetes cluster (Docker Desktop K8s, OrbStack, minikube, kind, etc.)

Enable Kubernetes in Docker Desktop

1. Open Docker Desktop settings
2. Go to "Kubernetes" tab
3. Check "Enable Kubernetes"
4. Click "Apply & Restart"

Enable Kubernetes in OrbStack

1. Open OrbStack settings
2. Go to "Kubernetes" tab
3. Check "Enable Kubernetes"

API Endpoints

GET /health

Health check endpoint.

Response:

{
  "status": "ok"
}

POST /api/sandboxes

Create a new sandbox Pod + Service.

Request:

{
  "sandbox_id": "abc-123",
  "thread_id": "thread-456",
  "user_id": "user-789"
}

user_id is optional for backwards compatibility and defaults to default. When USERDATA_PVC_NAME is set, the provisioner uses it to isolate PVC-backed user-data directories.

When the Gateway mounts that same storage at its DeerFlow home and the PVC subpaths align, set sandbox.thread_data_mounts: true in the Gateway's config.yaml to skip redundant upload-time sandbox acquire/sync. Leave the field unset when using unrelated storage or when the mount relationship is uncertain.

Response:

{
  "sandbox_id": "abc-123",
  "sandbox_url": "http://host.docker.internal:32123",
  "status": "Pending"
}

Idempotent: Calling with the same sandbox_id returns the existing sandbox info.

GET /api/sandboxes/{sandbox_id}

Get status and URL of a specific sandbox.

Response:

{
  "sandbox_id": "abc-123",
  "sandbox_url": "http://host.docker.internal:32123",
  "status": "Running"
}

Status Values: Pending, Running, Succeeded, Failed, Unknown, NotFound

DELETE /api/sandboxes/{sandbox_id}

Destroy a sandbox Pod + Service.

Response:

{
  "ok": true,
  "sandbox_id": "abc-123"
}

GET /api/sandboxes

List all sandboxes currently managed.

Response:

{
  "sandboxes": [
    {
      "sandbox_id": "abc-123",
      "sandbox_url": "http://host.docker.internal:32123",
      "status": "Running"
    }
  ],
  "count": 1
}

Configuration

The provisioner is configured via environment variables (set in docker-compose-dev.yaml):

Variable	Default	Description
K8S_NAMESPACE	deer-flow	Kubernetes namespace for sandbox resources
SANDBOX_IMAGE	enterprise-public-cn-beijing.cr.volces.com/vefaas-public/all-in-one-sandbox:latest	AIO-compatible container image for sandbox Pods
LARK_CLI_INIT_IMAGE	empty (feature off)	Optional lark-cli init image (Pattern A). When set, sandbox Pods requesting the lark-cli runtime get an init container + shared emptyDir that provisions lark-cli, instead of a hostPath/PVC runtime mount. See docker/lark-cli-init
LARK_CLI_BROKER_IMAGE	empty (feature off)	Optional lark-cli broker image (Pattern B, issue #4338). When set, sandbox Pods requesting the broker get a shim init container + a lark-cli-broker sidecar that holds the credentials; the plaintext config/data are mounted into the sidecar only, never the sandbox. Supersedes LARK_CLI_INIT_IMAGE when both are set. See docker/lark-cli-broker
THREADS_HOST_PATH	-	Host machine path to threads data directory (must be absolute)
DEER_FLOW_HOST_BASE_DIR	/.deer-flow	Host machine DeerFlow data root containing global and per-user skills_view projections
SKILLS_PVC_NAME	empty (use hostPath)	PVC name for skills volume; when set, sandbox Pods use PVC instead of hostPath
SKILLS_PVC_SUBPATH_TEMPLATE	empty	Optional subPath template for SKILLS_PVC_NAME. Supports {user_id} and {thread_id}. When empty, the skills PVC root is mounted unchanged
USERDATA_PVC_NAME	empty (use hostPath)	PVC name for user-data volume; when set, uses PVC with subPath: deer-flow/users/{user_id}/threads/{thread_id}/user-data
KUBECONFIG_PATH	/root/.kube/config	Path to kubeconfig inside the provisioner container
SANDBOX_SERVICE_TYPE	NodePort	Service type for sandbox access. Use ClusterIP when backend and provisioner run inside the same Kubernetes cluster
NODE_HOST	host.docker.internal	Hostname that backend containers use to reach host NodePorts; ignored when SANDBOX_SERVICE_TYPE=ClusterIP
K8S_API_SERVER	(from kubeconfig)	Override K8s API server URL (e.g., https://host.docker.internal:26443)

Custom sandbox image

Provisioner-created sandbox Pods use the provisioner's SANDBOX_IMAGE environment variable. This is separate from sandbox.image in config.yaml, which applies to local Docker or Apple Container mode.

For persistent dependencies, build an image that extends the default all-in-one-sandbox image and set SANDBOX_IMAGE to your published tag. A from-scratch image must remain compatible with the AIO sandbox HTTP API consumed by agent-sandbox, keep /mnt/user-data writable, and listen on the configured sandbox port.

See Building a Custom AIO Sandbox Image for the runtime contract and a minimal Dockerfile example.

Lark CLI sandbox runtime (Pattern A)

Agents run lark-cli inside the sandbox, so the binary must exist in the sandbox container. Instead of the Gateway downloading Linux binaries from GitHub at install time and mounting them via hostPath/PVC, the provisioner can inject lark-cli with an init container + shared emptyDir:

1. Publish a lark-cli init image (see docker/lark-cli-init) and set LARK_CLI_INIT_IMAGE on the provisioner.
2. When a sandbox is created with provision_lark_cli_runtime: true (the Gateway sends this automatically once the managed Lark skill pack is installed), the Pod gets a lark-cli-runtime emptyDir, an lark-cli-init init container that copies the runtime into it, and a read-only runtime mount on the sandbox container at /mnt/integrations/lark-cli/runtime. Any hostPath/PVC extra mount at that path is dropped (the init container supersedes it); the per-user config/data credential mounts are unchanged.

GET /api/capabilities returns {"lark_cli_init_image": true|false} so the Gateway can surface a sandbox-runtime readiness signal in /api/integrations/lark/status — a green UI can't then hide a chat-time lark-cli: command not found.

PVC User-Data Upgrade Note

Older provisioner versions mounted PVC user-data from threads/{thread_id}/user-data. The user-scoped layout mounts from deer-flow/users/{user_id}/threads/{thread_id}/user-data.

If an existing deployment already has PVC-backed user-data under the legacy layout, migrate the DeerFlow data directory before relying on the new PVC subPath. Mount the same PVC path that the gateway uses as its DeerFlow base directory, then run the existing user-isolation migration script:

cd backend
PYTHONPATH=. python scripts/migrate_user_isolation.py --dry-run
PYTHONPATH=. python scripts/migrate_user_isolation.py --user-id <target-user-id>

This moves legacy threads/{thread_id}/user-data data under users/<target-user-id>/threads/{thread_id}/user-data, which matches the new provisioner PVC subPath when the gateway base directory is mounted at deer-flow/ on the PVC. Use default as the target user only when the legacy data should remain in the default no-auth user namespace. Run the migration while no gateway or sandbox Pods are writing to those paths.

In hostPath mode, the gateway materializes enabled-only views under skills_view/public and users/{user_id}/skills_view/{custom,legacy} beneath DEER_FLOW_HOST_BASE_DIR; the provisioner mounts those stable directories. When skills are materialized per thread on the same PVC, set SKILLS_PVC_NAME to that PVC and configure SKILLS_PVC_SUBPATH_TEMPLATE=deer-flow/users/{user_id}/threads/{thread_id}/skills. Leaving the template empty preserves the legacy behavior of mounting the skills PVC root at /mnt/skills. The gateway does not yet populate that PVC layout dynamically, so PVC-backed skills do not receive hostPath projection updates.

hostPath skills volumes require the gateway and the K8s node to see the same DEER_FLOW_HOST_BASE_DIR (single-node deployment, or NFS/shared storage mounted at that path on every node). The gateway writes the projection there before every sandbox acquire, so as long as that path is shared, the directory the provisioner mounts always exists by the time the Pod is scheduled — even a boot-time rebuild failure for one user self-heals on their next acquire, before the provisioner is called. skills-custom and skills-legacy use hostPath type Directory (not DirectoryOrCreate): if the shared-storage assumption is violated — the gateway wrote to a different node than the one the Pod lands on — Pod creation now fails visibly instead of silently mounting an empty directory. Use SKILLS_PVC_NAME instead of hostPath for genuinely multi-node clusters without shared storage.

Important: K8S_API_SERVER Override

If your kubeconfig uses localhost, 127.0.0.1, or 0.0.0.0 as the API server address (common with OrbStack, minikube, kind), the provisioner cannot reach it from inside the Docker container.

Solution: Set K8S_API_SERVER to use host.docker.internal:

# docker-compose-dev.yaml
provisioner:
  environment:
    - K8S_API_SERVER=https://host.docker.internal:26443  # Replace 26443 with your API port

Check your kubeconfig API server:

kubectl config view --minify -o jsonpath='{.clusters[0].cluster.server}'

Prerequisites

Host Machine Requirements

1. Kubernetes Cluster:

   • Docker Desktop with Kubernetes enabled, or
   • OrbStack (built-in K8s), or
   • minikube, kind, k3s, etc.

2. kubectl Configured:

   • ~/.kube/config must exist and be valid
   • Current context should point to your local cluster

3. Kubernetes Access:

   • The provisioner needs permissions to:
     • Create/read/delete Pods in the deer-flow namespace
     • Create/read/delete Services in the deer-flow namespace
     • Read Namespaces (to create deer-flow if missing)

4. Host Paths:

   • DEER_FLOW_HOST_BASE_DIR and THREADS_HOST_PATH must be absolute paths on the host machine
   • These paths are mounted into sandbox Pods via K8s HostPath volumes
   • The paths must exist and be readable by the K8s node

Docker Compose Setup

The provisioner runs as part of the docker-compose-dev stack:

# Start Docker services (provisioner starts only when config.yaml enables provisioner mode)
make docker-start

# Or start just the provisioner
docker compose -p deer-flow-dev -f docker/docker-compose-dev.yaml up -d provisioner

The compose file:

• Mounts your host's ~/.kube/config into the container
• Adds extra_hosts entry for host.docker.internal (required on Linux)
• Configures environment variables for K8s access

Testing

Manual API Testing

# Health check
curl http://localhost:8002/health

# Create a sandbox (via provisioner container for internal DNS)
docker exec deer-flow-provisioner curl -X POST http://localhost:8002/api/sandboxes \
  -H "Content-Type: application/json" \
  -d '{"sandbox_id":"test-001","thread_id":"thread-001","user_id":"user-001"}'

# Check sandbox status
docker exec deer-flow-provisioner curl http://localhost:8002/api/sandboxes/test-001

# List all sandboxes
docker exec deer-flow-provisioner curl http://localhost:8002/api/sandboxes

# Verify Pod and Service in K8s
kubectl get pod,svc -n deer-flow -l sandbox-id=test-001

# Delete sandbox
docker exec deer-flow-provisioner curl -X DELETE http://localhost:8002/api/sandboxes/test-001

Verify from Backend Containers

Once a sandbox is created, the backend containers (gateway, langgraph) can access it:

# Get sandbox URL from provisioner
SANDBOX_URL=$(docker exec deer-flow-provisioner curl -s http://localhost:8002/api/sandboxes/test-001 | jq -r .sandbox_url)

# Test from gateway container
docker exec deer-flow-gateway curl -s $SANDBOX_URL/v1/sandbox

Troubleshooting

Issue: "Kubeconfig not found"

Cause: The kubeconfig file doesn't exist at the mounted path.

Solution:

• Ensure ~/.kube/config exists on your host machine
• Run kubectl config view to verify
• Check the volume mount in docker-compose-dev.yaml

Issue: "Kubeconfig path is a directory"

Cause: The mounted KUBECONFIG_PATH points to a directory instead of a file.

Solution:

• Ensure the compose mount source is a file (e.g., ~/.kube/config) not a directory
• Verify inside container:

  docker exec deer-flow-provisioner ls -ld /root/.kube/config
  

• Expected output should indicate a regular file (-), not a directory (d)

Issue: "Connection refused" to K8s API

Cause: The provisioner can't reach the K8s API server.

Solution:

1. Check your kubeconfig server address:

   kubectl config view --minify -o jsonpath='{.clusters[0].cluster.server}'
   

2. If it's localhost or 127.0.0.1, set K8S_API_SERVER:

   environment:
     - K8S_API_SERVER=https://host.docker.internal:PORT
   

Issue: "Unprocessable Entity" when creating Pod

Cause: HostPath volumes contain invalid paths (e.g., relative paths with ..).

Solution:

• Use absolute paths for DEER_FLOW_HOST_BASE_DIR and THREADS_HOST_PATH
• Verify the paths exist on your host machine:

  ls -la /path/to/skills
  ls -la /path/to/backend/.deer-flow/threads
  

Issue: Pod stuck in "ContainerCreating"

Cause: Usually pulling the sandbox image from the registry.

Solution:

• Pre-pull the image: make docker-init
• Check Pod events: kubectl describe pod sandbox-XXX -n deer-flow
• Check node: kubectl get nodes

Issue: Cannot access sandbox URL from backend

Cause: The backend cannot resolve or reach the sandbox ClusterIP Service DNS. This usually means the backend is not running inside the same Kubernetes cluster/network or cluster DNS/network policy is blocking access.

Solution:

• Verify the Service exists: kubectl get svc -n deer-flow
• In NodePort mode, test from the backend container: curl http://$NODE_HOST:NODE_PORT/v1/sandbox
• In ClusterIP mode, test from the backend Pod: curl http://sandbox-XXX-svc.deer-flow.svc.cluster.local:8080/v1/sandbox
• Check NODE_HOST for NodePort deployments, or cluster DNS / NetworkPolicy / service mesh rules for ClusterIP deployments

Security Considerations

1. HostPath Volumes: The provisioner mounts host directories into sandbox Pods by default. Ensure these paths contain only trusted data. For production, prefer PVC-based volumes (set SKILLS_PVC_NAME and USERDATA_PVC_NAME) to avoid node-specific data loss risks.

2. Resource Limits: Each sandbox Pod has CPU, memory, and storage limits to prevent resource exhaustion.

3. Network Isolation: Sandbox Pods run in the configured namespace and are exposed through NodePort or ClusterIP Services. Prefer ClusterIP with NetworkPolicies for in-cluster deployments.

4. kubeconfig Access: The provisioner has full access to your Kubernetes cluster via the mounted kubeconfig. Run it only in trusted environments.

5. Image Trust: The sandbox image should come from a trusted registry. Review and audit the image contents.

Future Enhancements

• Support for custom resource requests/limits per sandbox
• PersistentVolume support for larger data requirements
• Automatic cleanup of stale sandboxes (timeout-based)
• Metrics and monitoring (Prometheus integration)
• Multi-cluster support (route to different K8s clusters)
• Pod affinity/anti-affinity rules for better placement
• NetworkPolicy templates for sandbox isolation