A note on software tools and techniques for monitoring and prediction of cloud services

The Special Issue of presents research papers on developing software tools and techniques for monitoring and prediction of cloud services. Ryckbosch and Diwan propose a Temporal Pattern Analyzer system in their paper 'Analyzing Performance Traces Using Temporal Formulas' that uses formulas in linear-temporal logic extended with variables to analyze traces to investigate long-tail performance problems at Google and reduce the manual labor involved in analyzing traces. Cao and co-researchers also use execution trace information and propose a novel method for 'CPU load prediction for cloud environment based on a dynamic ensemble model' to obtain better performances. 'A Novel Monitoring Mechanism by Event Trigger for Hadoop System Performance Analysis' by Chang and co-researchers focuses on adapting to failed application service in a distributed environment by introducing fault avoidance service. Gülcü proposes an approach to prevent the occurrence of errors that result from the unavailability of prtner services in the first place.