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Backend Connection Reference — Intel® AI for Enterprise Agent Toolkit

All shared backends are deployed into their own namespaces and are reachable from any workload namespace in the cluster.

Redis (Session Memory & Caching)

Instance Kubernetes Service URL Scope
Redis Stack (deploy_redis=on) redis-stack-server.redis.svc.cluster.local:6379 redis://redis-stack-server.redis.svc.cluster.local:6379 All namespaces 
# Quick connectivity test
kubectl exec -n redis redis-stack-server-0 -- redis-cli ping
# PONG

Agent Sandbox (Sandboxed Execution)

Enabled with deploy_agent_sandbox=on. See agent-sandbox.md for full details.

Resource Value
Namespace agent-sandbox
Router service sandbox-router-svc.agent-sandbox.svc.cluster.local:8080
SDK pip install k8s-agent-sandbox
Default template python-sandbox-template (namespace: agent-sandbox) 
# Quick health check (requires port-forward or in-cluster)
kubectl port-forward -n agent-sandbox svc/sandbox-router-svc 8080:8080 &
curl -s http://localhost:8080/healthz
# {"status":"ok"}

PostgreSQL + pgvector (Vector Store & Long-Term Memory)

Enabled with deploy_pgvector=on. See README.md for deployment details.

Resource Value
Namespace pgvector
Host pgvector.pgvector.svc.cluster.local
Port 5432
Database agentdb
User agentuser
Connection string postgresql://agentuser:<password>@pgvector.pgvector.svc.cluster.local:5432/agentdb
Credentials secret kubectl get secret pgvector-credentials -n pgvector -o jsonpath='{.data.DATABASE_URL}' | base64 -d

KubeRay (Distributed Computing)

Enabled with deploy_kuberay=on. Tuned via core/inventory/kuberay-config.yaml. See kuberay.md for the full guide.

Resource Value
Namespace ray-system (default; set via kuberay-config.yaml)
Ray Client API ray://ray-cluster-head-svc.ray-system.svc.cluster.local:10001
Ray Dashboard http://ray-cluster-head-svc.ray-system.svc.cluster.local:8265
Dashboard (local) kubectl port-forward svc/ray-cluster-head-svc 8265:8265 -n ray-system 
# Verify all Ray pods are Running
kubectl get pods -n ray-system

# Quick Python connectivity test (from inside the cluster or via port-forward)
python3 -c "
import ray
ray.init('ray://ray-cluster-head-svc.ray-system.svc.cluster.local:10001')
print(ray.cluster_resources())
"

Flowise (Agent Builder)

Enabled with deploy_flowise=on. See flowise.md for the full guide.

Resource Value
Namespace flowise
Flowise service flowise.flowise.svc.cluster.local:3000
Flowise admin UI https://flowise-<cluster_url> 
# Check pods
kubectl get pods -n flowise

# Retrieve the Flowise API key
grep '^flowise_api_key:' core/inventory/metadata/vault.yml | awk -F'"' '{print $2}'