Azure Functions runs small units of code in response to HTTP requests, timers, queues, events, and service changes. You choose a supported hosting plan that controls scaling, networking, execution limits, and cost. Functions reduces server management; it does not remove the need for idempotency, dependency control, security, monitoring, and recovery.
Lab: 45 minutes · Cost: consumption, storage, networking, logs, and downstream services can charge · Creates: function app, required storage, and monitoring resources.
A function has one trigger. Bindings connect supported inputs and outputs without hand-writing all client plumbing. An HTTP trigger handles a request; a queue trigger handles messages; a timer trigger runs on a schedule. Treat binding configuration as application code and test it.
Current Azure Functions hosting choices evolve. Compare the Flex Consumption, Premium, dedicated App Service, container, and other currently supported options for:
Use the current Functions hosting comparison rather than relying on old SKU advice.
Ways to build
Choose the Azure tool you want to use. The underlying resource stays the same.
Search Function App → Create, choose hosting, runtime, version, region, storage, networking, monitoring, and deployment. Enable system-assigned identity and replace connection strings with identity-based connections where supported.
At-least-once delivery is common. Design for duplicates instead of pretending they cannot occur.
Durable Functions coordinates stateful workflows with orchestrator, activity, and entity patterns. Use it for fan-out/fan-in, human approval, long-running sequences, and durable timers. Orchestrator code must be deterministic because the framework replays it.
Compare it with Logic Apps for connector-rich workflows and Container Apps jobs for containerized batch work.
Bicep or Terraform should declare the hosting plan, function app, storage, identity, role assignments, private networking, diagnostic settings, and alerts. Application packages should be built once, scanned, signed where required, and promoted through environments. Do not create resources implicitly during application deployment.
Use Application Insights distributed tracing, structured logs, function execution metrics, queue length, failure rate, duration percentiles, and dead-letter count. Sample noisy success traces carefully but retain errors and correlation.
Delete the isolated lab resource group to remove the app, storage, and monitoring dependencies.