Functions user guide on CloudFerro Cloud
A webhook, an uploaded dataset, or a recurring check may need only a small piece of processing code. Functions runs that code when an HTTP request arrives, a message is received, or a scheduled time is reached. You choose the runtime, resources, and scaling settings; the service runs the deployed function.
Functions can serve HTTP requests without a messaging service. RabbitMQ and NATS integrations require the matching messaging product in the same region. Resources are regional and are not replicated between regions automatically.
Understand Functions
Start with the introduction for practical uses and a tour from the product catalogue to a working Python function. You will see the request and its HTTP 200 response before setting up your own example. The terminology page then explains the namespace, function, version, and endpoint shown in that tour.
Prepare, deploy, and test
The preparation article gets your portal session, region, Python files, and example settings ready. Then create sum-numbers, deploy its first version, and send [10, 20, 30] to receive total: 60. Building a version does not deploy it automatically. If you already have a deployed function, continue with the testing guide.
Work through an example
Translate dataset descriptions with Sherlock, save the results in Object Storage, and use a Message Broker trigger to process one job per language. Start with a direct HTTP test, then connect the services into a queued application.
Operate and troubleshoot
Build and deploy later versions, roll back to an earlier version, or remove resources when they are no longer needed. Logs, metrics, audit entries, and quota information help explain failures. The CLI guide covers the same function lifecycle from a terminal.
