This presentation explores optimizing AWS Lambda functions written in Python for speed and cost‑efficiency.

We examine the fundamentals of AWS Lambda and how Python functions operate in a serverless environment. Key factors impacting performance and cost, such as memory allocation and execution time, are discussed.

Techniques for improving speed include leveraging concurrency, optimizing memory settings, and using asynchronous programming patterns.

Cost-efficiency strategies involve selecting appropriate memory configurations, managing resource utilization, and designing efficient code.

The presentation provides practical examples and real-world experiences to demonstrate the benefits of each optimization technique. By the end, attendees will gain a comprehensive understanding of fine-tuning Python AWS Lambda functions to achieve optimal performance while minimizing costs in serverless applications.