Skip to main content Home Creators comeonoliver skillshub customerio-deploy-pipeline
customerio-deploy-pipeline Deploy Customer.io integrations to production cloud platforms.
Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes
with proper secrets management and health checks.
Trigger: "deploy customer.io", "customer.io cloud run",
"customer.io kubernetes", "customer.io lambda", "customer.io vercel".
Jump to install Skills Marketplace Discover and explore AI skills built by the community.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Show prompt details A direct command skips the review prompt. Inspect the source before running it.
npx skills add https://github.com/ComeOnOliver/skillshub --skill customerio-deploy-pipelineThe command stays on one line. Scroll horizontally to inspect it before copying.
Prefer a local copy? Download the files currently available to SkillsMP.
Download Zip Downloading... More from this repository Review product and feature risk before an AI coding agent starts implementation.
Use Xquik for X data and confirmation-gated X actions: tweet search, user lookup, follower export, media download, monitors, webhooks, MCP, and SDK workflows.
Canton Network open-source ecosystem guide covering DAML SDK, Canton runtime, and Splice applications. Use when working with Canton Network, DAML smart contracts, or building decentralized applications.
Related occupations SOC
Based on SOC occupation classification
name customerio-deploy-pipeline description Deploy Customer.io integrations to production cloud platforms.
Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes
with proper secrets management and health checks.
Trigger: "deploy customer.io", "customer.io cloud run",
"customer.io kubernetes", "customer.io lambda", "customer.io vercel".
allowed-tools Read, Write, Edit, Bash(npm:*), Bash(gcloud:*), Bash(kubectl:*), Glob, Grep version 1.0.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> compatible-with claude-code, codex, openclaw tags ["saas","customer-io","deployment","cloud-run","kubernetes"]
Customer.io Deploy Pipeline
Overview
Deploy Customer.io integrations to production: GCP Cloud Run with Secret Manager, Vercel serverless functions, AWS Lambda with SSM, Kubernetes with external secrets, plus health check endpoints and blue-green deployment scripts.
Prerequisites
CI/CD pipeline configured (see customerio-ci-integration)
Cloud platform credentials and access
Production Customer.io credentials in a secrets manager
Instructions
Step 1: Deploy to Google Cloud Run
name: Deploy to Cloud Run
on:
push:
branches: [main ]
jobs:
deploy:
runs-on: ubuntu-latest
permissions:
contents: read
id-token: write
steps:
- uses: actions/checkout@v4
- id: auth
uses: google-github-actions/auth@v2
with:
workload_identity_provider: ${{ secrets.WIF_PROVIDER }}
service_account: ${{ secrets.WIF_SA }}
- uses: google-github-actions/setup-gcloud@v2
-
name:
Build
and
push
run:
|
gcloud builds submit --tag gcr.io/${{ secrets.GCP_PROJECT }}/cio-service
-
name:
Deploy
run:
|
gcloud run deploy cio-service \
--image gcr.io/${{ secrets.GCP_PROJECT }}/cio-service \
--region us-central1 \
--set-secrets "CUSTOMERIO_SITE_ID=cio-site-id:latest,\
CUSTOMERIO_TRACK_API_KEY=cio-track-key:latest,\
CUSTOMERIO_APP_API_KEY=cio-app-key:latest" \
--set-env-vars "CUSTOMERIO_REGION=us,NODE_ENV=production" \
--min-instances 1 \
--max-instances 10 \
--memory 512Mi \
--cpu 1 \
--allow-unauthenticated
Step 2: Health Check Endpoint
import { TrackClient , RegionUS } from "customerio-node" ;
import { Router } from "express" ;
const router = Router ();
router.get ("/health" , async (_req, res) => {
const checks : Record <string , { status : string ; latency_ms ?: number }> = {};
const cio = new TrackClient (
process.env .CUSTOMERIO_SITE_ID !,
process.env .CUSTOMERIO_TRACK_API_KEY !,
{ region : RegionUS }
);
const start = Date .now ();
try {
await cio.identify ("health-check" , {
email : "health@internal.example.com" ,
_health_check : true ,
});
checks.track_api = { status : "ok" , latency_ms : Date .now () - start };
} catch (err : any ) {
checks.track_api = { status : `error: ${err.statusCode} ` };
}
const allOk = Object .values (checks).every ((c ) => c.status === "ok" );
res.status (allOk ? 200 : 503 ).json ({
status : allOk ? "healthy" : "degraded" ,
checks,
version : process.env .npm_package_version ?? "unknown" ,
uptime_seconds : Math .floor (process.uptime ()),
timestamp : new Date ().toISOString (),
});
});
export default router;
Step 3: Vercel Serverless Functions
import type { VercelRequest , VercelResponse } from "@vercel/node" ;
import { TrackClient , RegionUS } from "customerio-node" ;
const cio = new TrackClient (
process.env .CUSTOMERIO_SITE_ID !,
process.env .CUSTOMERIO_TRACK_API_KEY !,
{ region : RegionUS }
);
export default async function handler (req : VercelRequest , res : VercelResponse if (req.method !== "POST" ) {
return res.status (405 ).json ({ error : "Method not allowed" });
}
const { userId, attributes } = req.body ;
if (!userId || !attributes?.email ) {
return res.status (400 ).json ({ error : "userId and attributes.email required" });
}
try {
await cio.identify (userId, {
...attributes,
last_seen_at : Math .floor (Date .now () / 1000 ),
});
return res.status (200 ).json ({ success : true });
} catch (err : any ) {
return res.status (err.statusCode ?? 500 ).json ({ error : err.message });
}
}
Step 4: Kubernetes Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: customerio-service
spec:
replicas: 2
selector:
matchLabels:
app: customerio-service
template:
metadata:
labels:
app: customerio-service
spec:
containers:
- name: app
image: gcr.io/my-project/cio-service:latest
ports:
- containerPort: 3000
env:
- name: CUSTOMERIO_SITE_ID
valueFrom:
secretKeyRef:
name: customerio-secrets
key: site-id
- name: CUSTOMERIO_TRACK_API_KEY
valueFrom:
secretKeyRef:
name: customerio-secrets
key: track-api-key
- name: CUSTOMERIO_APP_API_KEY
valueFrom:
secretKeyRef:
name: customerio-secrets
key: app-api-key
- name: CUSTOMERIO_REGION
value: "us"
- name: NODE_ENV
value: "production"
resources:
requests:
cpu: 100m
memory: 256Mi
limits:
cpu: 500m
memory: 512Mi
readinessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 5
periodSeconds: 10
livenessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 15
periodSeconds: 30
---
apiVersion: v1
kind: Service
metadata:
name: customerio-service
spec:
selector:
app: customerio-service
ports:
- port: 80
targetPort: 3000
Step 5: Blue-Green Deployment #!/usr/bin/env bash
set -euo pipefail
SERVICE="cio-service"
REGION="us-central1"
IMAGE="gcr.io/${GCP_PROJECT} /${SERVICE} :${COMMIT_SHA} "
echo "=== Blue-Green Deploy: ${SERVICE} ==="
gcloud run deploy "${SERVICE} " \
--image "${IMAGE} " \
--region "${REGION} " \
--no-traffic \
--tag "canary"
echo "Deployed canary. Running health check..."
CANARY_URL=$(gcloud run services describe "${SERVICE} " \
--region "${REGION} " --format 'value(status.url)' \
| sed 's|https://|https://canary---|' )
HEALTH=$(curl -s -o /dev/null -w "%{http_code}" "${CANARY_URL} /health" )
if [ "${HEALTH} " != "200" ]; then
echo "FAIL: Health check returned ${HEALTH} . Aborting."
exit 1
fi
for pct in 10 50 100; do
echo "Shifting ${pct} % traffic to canary..."
gcloud run services update-traffic "${SERVICE} " \
--region "${REGION} " \
--to-tags "canary=${pct} "
sleep 30
done
echo "Deploy complete. 100% traffic on new revision."
Deployment Checklist
Error Handling Issue Solution Secret not found Verify secret name in secrets manager Health check timeout Increase initialDelaySeconds, check CIO connectivity Cold start latency Set --min-instances 1 (Cloud Run) or keep-alive Memory OOM Increase memory limits, check for event queue buildup
Resources
Next Steps After deployment, proceed to customerio-webhooks-events for webhook handling.
