Troubleshooting Serverless functions: a combined monitoring and debugging approach

Abstract

Today, Serverless computing gathers pace and attention in the cloud computing area. The abstraction of operational tasks combined with the auto-scaling property are convincing reasons to adapt this new cloud paradigm. Building applications in a Serverless style via cloud functions is challenging due to the fine-grained architecture and the tighter coupling to back end services. Increased complexity, loss of control over software layers and the large number of participating functions and back end services complicate the task of finding the cause of a faulty execution. A tedious but widespread strategy is the manual analysis of log data. In this paper, we present a semi-automated troubleshooting process to improve fault detection and resolution for Serverless functions. Log data is the vehicle to enable a posteriori analysis. The process steps of our concept enhance the log quality, detect failed executions automatically, and generate test skeletons based on the information provided in the log data. Ultimately, this leads to an increased test coverage, a better regression testing and more robust functions. Developers can trigger this process asynchronously and work with their accustomed tools. We also present a prototype SeMoDe to validate our approach for Serverless functions implemented in Java and deployed to AWS Lambda.