A Controller for Anomaly Detection, Analysis and Management for Self-Adaptive for Container Clusters
El Ioini N
MetadataShow full item record
SubjectCloud computing; Container Technology; Distributed Cluster; Markov Model; Anomaly detection; Anomaly Analysis; Workload; Performance
Service computing in the cloud allows applications to be deployed remotely. These are managed by third-party service providers that make virtualised resources available for these services. Self-adaptive features for load-balancing and auto-scaling are available here, but generally there is no direct access to the infrastructure or platform-level execution environment.Some quality parameters of a provided service can be directly observed while others remain hidden from the service consumer.Our solution is an autonomous self-adaptive controller for anomaly remediation in this semi-hidden setting. The objective of the controller is to, firstly, determine possible root causes of consumer-observed anomalies and, secondly, take appropriate action. This needs to happen in an underlying provider-controlled infrastructure. We use Hidden Markov Models to map observed performance anomalies into hidden resources, and to identify the root causes of the observed anomalies. We apply the model to a clustered computing resource environment that is based on three layers of aggregated resources. We discuss use cases to illustrate the utility of the proposed solution.
Showing items related by title, author, creator and subject.
Samir A; El Ioini N; Fronza I; Barzegar HR; Le VT; Pahl C (2019)Virtualised environments such as cloud and edge computing architectures allow software to be deployed and managed through third-party provided services. Here virtualised resources available can be adjusted, even dynamically ...
Pahl C; Lee B (IEEE, 2015)Cloud technology is moving towards more distribution across multi-clouds and the inclusion of various devices, as evident through IoT and network integration in the context of edge cloud and fog computing. Generally, ...
Pahl C; Helmer S; Miori L; Sanin J; Lee B (IEEE, 2016)Cloud technology is moving towards multi-cloud environments with the inclusion of various devices. Cloud and IoT integration resulting in so-called edge cloud and fog computing has started. This requires the combination ...