For a cloud service provider, the goal is to proactively identify signals that can help reduce outages and/or reduce the mean-time-to-detect and mean-time-to-resolve. After an incident is reported, the Site Reliability Engineers diagnose the fault ...

Auto-tuning attracts increasing attention in industry practice to optimize the performance of a system with many configurable parameters. It is particularly useful for cloud applications and services since they have complex system hierarchies and ...

Microservice architecture design highly relies on expert experience and may often result in improper service decomposition. Moreover, a microservice architecture is likely to degrade with the continuous evolution of services. Architecture measurement ...

Cloud computing systems have become increasingly popular in recent years. A typical cloud system utilizes millions of computing nodes as the basic infrastructure. Node failure has been identified as one of the most prevalent causes of cloud system ...

Modern DevOps organizations require a high degree of automation to achieve software stability at frequent changes. Further, there is a need for flexible, timely reconfiguration of the infrastructure, e.g., to use pay-per-use infrastructure efficiently ...

Due to the large amount and high complexity of trace data, microservice trace analysis tasks such as anomaly detection, fault diagnosis, and tail-based sampling widely adopt machine learning technology. These trace analysis approaches usually use a ...

Fault localization is challenging in an online service system due to its monitoring data's large volume and variety and complex dependencies across/within its components (e.g., services or databases). Furthermore, engineers require fault localization ...