Deploy CAIPE with Helm

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

:::tip 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)