By using AWS Lambda instead of Amazon EC2 instances for its IPO workload, Financial Engines is realizing an ongoing cost savings. “We project 94 percent savings in hard costs, or about $110,000 annually,” says Yavorskiy. “That’s not including the cost savings in operational maintenance—security patches and library upgrades—which AWS Lambda takes care of automatically.”

Since rolling out AWS Lambda, Financial Engines has experienced near-zero downtime and near-zero performance degradation while serving 200–300 million IPO requests per month at rates of 60,000 per minute during heaviest traffic, which can reach 10 times normal traffic. “AWS has increased our system’s resilience,” says Yavorskiy. “If there are crashes due to bad requests, there is no lasting effect on service stability because new executors are instantiated right away to handle incoming traffic.”

The AWS Lambda function model makes it a natural fit for building microservices. Running the IPO as a microservice on AWS Lambda with its own continuous integration/continuous delivery (CI/CD) pipeline is a major step toward breaking up the company’s monolithic architecture. Financial Engines has 15 additional microservices in production that it expects to build on AWS.

Financial Engines is excited to consider how it might use Lambda and serverless computing to grow its business. “In addition to the one million clients whose accounts we currently manage, we have access to millions of other users who are prospective clients,” says Gibson. “Using AWS Lambda will enable us to scale to serve millions more who need financial help.”