Serverless Computing Pros Cons and Patterns

What is serverless? Serverless computing means you run code without managing servers. You write small functions that respond to events or HTTP requests. The platform handles provisioning, scaling, and fault tolerance. It is typically pay-per-use, which can save money when traffic is irregular.

Pros

• Cost efficiency: pay only for compute time; no idle servers.
• Automatic scaling: handles traffic spikes without manual tuning.
• Faster delivery: small, focused functions speed up experiments.
• Reduced operations: the cloud provider handles reliability and updates.

Cons

• Cold starts: the first invocation after idle time can be slower.
• Vendor lock-in: many features are not portable.
• Observability: tracing many small pieces needs good tooling.
• Limits on runtime and memory: long tasks or heavy workloads may not fit.

Common patterns

• HTTP API with a gateway: a function handles requests on the web.
• Asynchronous processing: events go to a queue; workers process jobs.
• Scheduled jobs: cron-like tasks run at set times.
• Fan-out and orchestration: multiple functions work together to complete a task.
• Data processing pipelines: stream or batch events driving transformations.

Choosing patterns

• Start small and stateless: easy to test and replace.
• Use queues for async work and backpressure.
• Orchestrate when steps depend on each other; consider durable functions or step functions.
• Monitor costs with alerts and budgets; set hard limits for runaway usage.

When to avoid serverless

• Long-running tasks or memory-hungry processes.
• Very strict latency requirements.
• Complex, monolithic legacy code that is hard to refactor.

Conclusion Serverless helps teams move fast, but success comes from good patterns, disciplined design, and clear a cost model.

Key Takeaways

• Be mindful of cold starts, costs, and vendor differences.
• Use patterns that fit event-driven workloads.
• Plan for observability and orchestration as you scale.