Deploy CAIPE with Helm

Use the Helm chart to run CAIPE on any Kubernetes cluster — EKS, GKE, AKS, KinD, or self-managed.

Need a cluster first?

If you don't have a Kubernetes cluster yet, see Cluster Setup for KinD (local, no cloud account needed) and AWS EKS instructions. Return here once kubectl get nodes shows nodes in Ready state.

Prerequisites

Requirement	Notes
Kubernetes 1.28+	Set one up if needed
kubectl	Configured against your cluster
Helm 3	helm version to verify
LLM credentials	OpenAI, Azure OpenAI, or AWS Bedrock

---

Configure Secrets

Create the namespace and secrets before running the Helm install.

kubectl create namespace ai-platform-engineering

LLM credentials

Pick the provider you're using:

OpenAI

kubectl create secret generic llm-secret \
  -n ai-platform-engineering \
  --from-literal=LLM_PROVIDER=openai \
  --from-literal=OPENAI_API_KEY=<token> \
  --from-literal=OPENAI_MODEL_NAME=gpt-4o

Azure OpenAI

kubectl create secret generic llm-secret \
  -n ai-platform-engineering \
  --from-literal=LLM_PROVIDER=azure-openai \
  --from-literal=AZURE_OPENAI_API_KEY=<token> \
  --from-literal=AZURE_OPENAI_ENDPOINT=https://example.openai.azure.com \
  --from-literal=AZURE_OPENAI_API_VERSION=2025-03-01-preview \
  --from-literal=AZURE_OPENAI_DEPLOYMENT=gpt-4o

AWS Bedrock

kubectl create secret generic llm-secret \
  -n ai-platform-engineering \
  --from-literal=LLM_PROVIDER=aws-bedrock \
  --from-literal=AWS_ACCESS_KEY_ID=<access-key> \
  --from-literal=AWS_SECRET_ACCESS_KEY=<secret-key> \
  --from-literal=AWS_REGION=us-east-1 \
  --from-literal=AWS_BEDROCK_MODEL_ID=us.amazon.nova-pro-v1:0 \
  --from-literal=AWS_BEDROCK_PROVIDER=amazon

MCP server credentials

Create only the secrets for MCP servers you plan to enable:

kubectl create secret generic github-secret \
  -n ai-platform-engineering \
  --from-literal=GITHUB_PERSONAL_ACCESS_TOKEN=<token>

kubectl create secret generic argocd-secret \
  -n ai-platform-engineering \
  --from-literal=ARGOCD_TOKEN=<token> \
  --from-literal=ARGOCD_API_URL=https://argocd.example.com \
  --from-literal=ARGOCD_VERIFY_SSL=true

---

Install from OCI

Set the chart version:

export CAIPE_VERSION=<release-version>

Minimal install — UI, Dynamic Agents, MongoDB, and a starter MCP server:

helm install ai-platform-engineering oci://ghcr.io/cnoe-io/charts/ai-platform-engineering \
  --version "${CAIPE_VERSION}" \
  --namespace ai-platform-engineering \
  --create-namespace \
  --set-string tags.caipe-ui=true \
  --set-string tags.dynamic-agents=true \
  --set-string tags.mcp-netutils=true

With GitHub, ArgoCD, and RAG:

helm upgrade --install ai-platform-engineering oci://ghcr.io/cnoe-io/charts/ai-platform-engineering \
  --version "${CAIPE_VERSION}" \
  --namespace ai-platform-engineering \
  --create-namespace \
  --set-string tags.caipe-ui=true \
  --set-string tags.dynamic-agents=true \
  --set-string tags.mcp-github=true \
  --set-string tags.mcp-argocd=true \
  --set-string tags.rag-stack=true

Values file

tags:
  caipe-ui: true
  dynamic-agents: true
  mcp-github: true
  rag-stack: true

global:
  llmSecrets:
    secretName: llm-secret

mcp-github:
  agentSecrets:
    secretName: github-secret

# Optional: pre-seed model choices in the UI
caipe-ui:
  appConfig:
    models:
      - model_id: gpt-4o
        name: GPT-4o
        provider: openai
        enabled: true

helm upgrade --install ai-platform-engineering oci://ghcr.io/cnoe-io/charts/ai-platform-engineering \
  --version "${CAIPE_VERSION}" \
  --namespace ai-platform-engineering \
  --create-namespace \
  --values values.yaml

---

Chart Components

Component	Tag	Purpose
CAIPE UI	tags.caipe-ui=true	Web UI and BFF API
Dynamic Agents	tags.dynamic-agents=true	Chat, custom agents, workflows, checkpointed state
MCP servers	tags.mcp-<name>=true	Tool integrations exposed to agents
RAG stack	tags.rag-stack=true	Knowledge base and embeddings
Slack bot	tags.slack-bot=true	Slack integration
Webex bot	tags.webex-bot=true	Webex integration

Available MCP tags: mcp-argocd, mcp-aws, mcp-backstage, mcp-confluence, mcp-github, mcp-gitlab, mcp-jira, mcp-komodor, mcp-pagerduty, mcp-slack, mcp-splunk, mcp-victorops, mcp-webex, mcp-netutils.

---

Verify

helm list -n ai-platform-engineering
kubectl get pods -n ai-platform-engineering
kubectl logs -n ai-platform-engineering -l app.kubernetes.io/name=dynamic-agents

---

Troubleshooting

• Pods not starting: kubectl describe pod <pod> -n ai-platform-engineering
• Check rendered manifests: helm template ai-platform-engineering charts/ai-platform-engineering --values values.yaml
• Ensure tags.dynamic-agents=true is set when Dynamic Agents should run
• MCP tag names use mcp-* prefix (e.g. tags.mcp-github=true)