FaaSter Troubleshooting -- Evaluating Distributed Tracing Approaches for Serverless Applications
This addresses the difficulty of fault identification in serverless applications for developers, but it is incremental as it builds on existing tracing methods.
The paper tackled the problem of troubleshooting serverless applications by investigating distributed tracing approaches, resulting in a model for fault observability and insights into trade-offs like execution latency and resource utilization.
Serverless applications can be particularly difficult to troubleshoot, as these applications are often composed of various managed and partly managed services. Faults are often unpredictable and can occur at multiple points, even in simple compositions. Each additional function or service in a serverless composition introduces a new possible fault source and a new layer to obfuscate faults. Currently, serverless platforms offer only limited support for identifying runtime faults. Developers looking to observe their serverless compositions often have to rely on scattered logs and ambiguous error messages to pinpoint root causes. In this paper, we investigate the use of distributed tracing for improving the observability of faults in serverless applications. To this end, we first introduce a model for characterizing fault observability, then provide a prototypical tracing implementation - specifically, a developer-driven and a platform-supported tracing approach. We compare both approaches with our model, measure associated trade-offs (execution latency, resource utilization), and contribute new insights for troubleshooting serverless compositions.