Performance and Cost

This chapter covers how serverless performance and economics actually behave after the demo phase. The platform can remove server management, but it does not remove latency, concurrency limits, downstream bottlenecks, or expensive architectural choices. Those still show up in production as cold-start spikes, throttling, queue lag, and monthly bills that surprise teams who assumed usage-based pricing would stay naturally efficient.

Read the lessons in order. They move from startup latency and cold starts into scaling controls, then into cost-model reasoning, and finally into optimization strategies that improve both speed and spend. The common theme is that serverless cost and performance are design outcomes, not automatic platform gifts.

In this section

• Cold Starts and Startup Optimization
  Explain cold starts, warm execution reuse, package size effects, dependency loading, and runtime choices. This section should connect architecture decisions to real latency.
• Throughput, Concurrency, and Scaling Controls
  Describe concurrency limits, throttling, scaling bursts, reserved capacity patterns, and how function and event characteristics affect throughput.
• Cost Modeling and Cost Surprises
  Explain billing dimensions such as invocations, duration, memory size, data transfer, requests, storage, and workflow steps. Show how serverless can become unexpectedly expensive when patterns are poorly chosen.
• Optimization Strategies That Actually Work
  Describe right-sizing, batching, reducing redundant invocations, gateway caching, asynchronous decoupling, and minimizing unnecessary service chatter.