Predictive analytics for Smarttarget: Proactive performance anomaly detection techniques for cloud-based Web services

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The private sector partner for this research project is Ottawa based Predikat Inc. The company provides a suiteof application performance management (APM) tools called Smarttarget for their customers. Predikat'scustomers typically host Web services on cloud platforms such as Amazon EC2 and Microsoft Azure. Webservice performance is an important consideration for these customers. In particular, customers would like toensure fast response times for their Web services to support good Quality of Experience (QoE) to end users ofthese services. Unfortunately, several factors make it challenging to achieve good performance. In particular,the workload experienced by a Predikat Web service can often fluctuate significantly. Furthermore, cloudplatforms are known to introduce performance degradations since in such platforms multiple applications cancompete for shared cloud resources. Consequently, a Predikat customer requires APM tools that canautomatically and proactively predict the impending onset of performance problems. Such a capability wouldallow the customer to quickly put in place strategies to mitigate the problem thereby ensuring that end userQoE is not compromised. The purpose of this Engage collaboration is to identify the challenges in buildingsuch tools and to investigate effective solutions for these challenges.