In large distributed application-based systems, an ensemble of co-existing micro-services perform individual functions and communicate with other micro-services. As these interactions and individual behaviors can be complex, it may be necessary to monitor micro-services for any abnormalities. Manual monitoring of all such micro-services, or establishing individual rule-based alerts for micro-services can be time-consuming. In addition to maintaining functionality of micro-services, it is important to prevent micro-services from becoming a performance bottleneck for other micro-services. In such situations, an alert may not suffice. For example, if a micro-service serves as a data store for all other services, a bottleneck at that micro-service may affect an entire system. By performing a predictive analysis of the health of micro-services, large distributed application-based systems can incorporate either preventive or reactive healing, thereby becoming auto-corrective in nature.

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This work is licensed under a Creative Commons Attribution 4.0 License.