Five best practices for migrating workloads to AWS Lambda

Since its introduction in 2015, AWS Lambda has become a popular choice for deploying serverless functions due to its automatic scaling and pay-per-use pricing, eliminating the need for server management. However, migrating applications to Lambda requires careful consideration, as it is best suited for event-driven, stateless workloads with execution times under 15 minutes. For longer-running processes or stateful applications, services like Amazon ECS or Fargate may be more appropriate. The guide offers strategies for assessing workload suitability, handling technical migration details, and optimizing Lambda's capabilities, such as cold start performance and cost efficiency. It emphasizes the importance of right-sizing memory allocations, considering ARM-based processors for better price-performance, and avoiding common pitfalls like creating "distributed monoliths" without clear service boundaries. Tools like vFunction can aid in architectural modernization, helping teams to identify service boundaries and optimize applications for serverless environments. Overall, the decision to use Lambda should be based on an evaluation of workload characteristics and the specific strengths and limitations of serverless computing.