Robust Multimodal Failure Detection for Microservice Systems

Understand

Proactive failure detection of instances is vitally essential to microservice systems because an instance failure can propagate to the whole system and degrade the system's performance.

• Over the years, many single-modal (i.e., metrics, logs, or traces) data-based nomaly detection methods have been proposed.
• However, they tend to miss a large number of failures and generate numerous false alarms because they ignore the correlation of multimodal data.
• In this work, we propose AnoFusion, an unsupervised failure detection approach, to proactively detect instance failures through multimodal data for microservice systems.