Jolteon: Unleashing the Promise of Serverless for Serverless Workflows

Serverless computing promises automatic resource provisioning to relieve the burden of developers. Yet, developers still have to manually configure resources on current serverless platforms to satisfy application-level requirements. This is because cloud applications are orchestrated as serverless workflows with multiple stages, exhibiting a complex relationship between resource configuration and application requirements.

We propose Jolteon, an orchestrator to unleash the promise of automatic resource provisioning for serverless workflows. At the core of Jolteon is a stochastic performance model that combines the benefits of whitebox modeling to capture the execution characteristics of serverless computing and blackbox modeling to accommodate the inherent performance variability. We formulate a chance constrained optimization problem based on the performance model, and exploit sampling and convexity to find optimal resource configurations that satisfy user-defined cost or latency bounds. We implement a system prototype of Jolteon and evaluate it on AWS Lambda with a variety of serverless workflows. The experimental results show that Jolteon outperforms the state-of-the-art solution, Orion, by up to 2.3× on cost and 2.1× on latency.