Learn IBM-CLOUD-FUNCTIONS with Real Code Examples

Serverless API endpoint

Data ingestion from cloud storage events

AI/ML model inference triggered by HTTP request

Cron-based periodic data processing

Webhook processing for CI/CD pipelines

Check function logs via CLI or web console

Ensure trigger and rule configuration is correct

Validate runtime compatibility

Monitor namespace and resource limits

Verify integration with external services and APIs

Invoke actions locally using CLI

Test triggers manually

Use sequences to test function chaining

Monitor logs for errors

Validate integration with IBM Cloud services

IBM Cloud managed serverless platform

Deploy via CLI, web console, or Git integration

Preview and production deployments supported

Use resource groups and namespaces for multi-tenant management

Integrate with CI/CD pipelines

IBM Cloud CLI

IBM Cloud Functions plugin

Web console for management

IBM Cloud monitoring and logging services

OpenWhisk open-source resources and SDKs

HTTP/REST endpoints

Cloud object storage events

Cloud Databases (PostgreSQL, Cloudant)

Watson AI services (NLP, Vision, Speech-to-Text)

Messaging systems (Kafka, Event Streams)

Use CLI for rapid deployments

Structure projects with actions, triggers, and sequences

Leverage sequences to compose complex workflows

Monitor metrics to optimize performance

Use environment variables and secrets efficiently

Cold start optimization

Function composition in sequences

Integrating multiple IBM Cloud services securely

Monitoring and logging at scale

Resource and quota management