Case Study: Financial Engines achieves 90% cost reduction and scalable, resilient service with Amazon Web Services (AWS) Lambda

Financial Engines Cuts Costs 90% Using AWS Lambda and Serverless Computing

Financial Engines, a provider of portfolio optimization and retirement-planning services, faced growing infrastructure strain as its integer programming optimizer (IPO) consumed over 30% of CPU capacity. The monolithic codebase and frequent traffic spikes during marketing campaigns made capacity planning, resilience, and operational overhead major challenges.

The company migrated the IPO engine to AWS Lambda, replacing roughly 50 servers with four Lambda endpoints and running the IPO as a stateless microservice (Java + third‑party native libraries) monitored via CloudWatch and Splunk. The move delivered ~94% hard‑cost savings (about $110,000 annually), near‑zero downtime while handling 200–300 million IPO requests per month (peaks up to ~60,000/min or ~1,000 req/sec), reduced maintenance burden, and increased resilience and scalability—enabling rapid growth and additional microservices on serverless infrastructure.

Financial Engines

Paul Gibson

Principal System Architect