Customer.io Deploy Pipeline
Overview
Deploy Customer.io integrations to production cloud platforms (GCP Cloud Run, Vercel, AWS Lambda, Kubernetes) with health checks and blue-green deployments.
Prerequisites
- CI/CD pipeline configured
- Cloud platform access (GCP, AWS, Vercel, etc.)
- Production credentials ready
Instructions
Step 1: Deploy to Google Cloud Run
Set up GitHub Actions workflow with Workload Identity Federation, Docker build/push, and Cloud Run deployment with secrets from Secret Manager.
Step 2: Deploy to Vercel (if applicable)
Configure Vercel project with serverless API functions for identify, track, and webhook endpoints.
Step 3: Deploy to AWS Lambda (if applicable)
Use Serverless Framework with SSM parameter store for credentials and Lambda handlers for each API operation.
Step 4: Deploy to Kubernetes
Create Deployment with secrets from SecretKeyRef, resource limits, readiness/liveness probes, and Service.
Step 5: Implement Health Check
Build a health endpoint that tests Customer.io connectivity, reports status and latency, and includes version and uptime info.
Step 6: Set Up Blue-Green Deployment
Create a deployment script that deploys with no traffic, runs health checks, then gradually shifts 10% -> 50% -> 100%.
For detailed deployment manifests and scripts, load the reference guide: Read(${CLAUDE_SKILL_DIR}/references/implementation-guide.md)
Output
- Cloud Run deployment workflow
- Vercel serverless deployment
- AWS Lambda configuration
- Kubernetes deployment manifests
- Health check endpoint
- Blue-green deployment script
Error Handling
| Issue | Solution |
|---|---|
| Secret not found | Verify secret name and permissions |
| Health check failing | Check Customer.io credentials |
| Cold start timeout | Increase memory/timeout limits |
Resources
Next Steps
After deployment, proceed to customerio-webhooks-events for webhook handling.
Examples
Basic usage: Apply customerio deploy pipeline to a standard project setup with default configuration options.
Advanced scenario: Customize customerio deploy pipeline for production environments with multiple constraints and team-specific requirements.