Detecting and mitigating cross-layer impact of change events on a cloud computing system

A method, comprising:

• receiving a plurality of change event identifiers associated with a plurality of change events detected across multiple hierarchical layers of a hierarchical structure of a distributed computing system;
• maintaining a record of failure events across the multiple hierarchical layers of the distributed computing system indicating counts of detected failure events;
• identifying a failure anomaly within the plurality of change events based on a count of detected failure events within the record of failure events exceeding a threshold count of failure events of an associated failure type;
• determining whether the distributed computing system has a built-in remedy for addressing the failure anomaly;
• and
• at least one of:
• responsive to determining that the distributed computing system has a built-in remedy for addressing the failure anomaly, causing the built-in remedy to be executed without generating a recommendation including a recommended action to perform on one or more computing nodes of the distributed computing system;
• or
• responsive to determining that the distributed computing system does not have a built-in remedy for addressing the failure anomaly:
• selectively analyzing a subset of change event identifiers from the plurality of change event identifiers associated with the failure anomaly to determine a correlation between at least one change event and the failure anomaly, the subset of change event identifiers being associated with change events detected across at least two of the multiple hierarchical layers of the hierarchical structure of the distributed computing system;
• and
• generating a recommendation including a recommended action to perform on one or more nodes of the distributed computing system associated with the at least one change event based on the determined correlation between the at least one change event and the failure anomaly.

A system, comprising:

• at least one processor;
• memory in electronic communication with the at least one processor;
• and
• instructions stored in the memory, the instructions being executable by the at least one processor to:
• receive a plurality of change event identifiers associated with a plurality of change events detected across multiple hierarchical layers of a hierarchical structure of a cloud computing system;
• maintain a record of failure events across the multiple hierarchical layers of the cloud computing system indicating counts of detected failure events;
• identify a failure anomaly within the plurality of change events based on a count of detected failure events within the record of failure events exceeding a threshold count of failure events of an associated failure type;
• determine whether the cloud computing system has a built-in remedy for addressing the failure anomaly;
• and
• at least one of:
• responsive to determining that the cloud computing system has a built-in remedy for addressing the failure anomaly, causing the built-in remedy to be executed without generating a recommendation including a recommended action to perform on one or more computing nodes of the cloud computing system;
• or
• responsive to determining that the cloud computing system does not have a built-in remedy for addressing the failure anomaly
• selectively analyze a subset of change event identifiers from the plurality of change event identifiers associated with the failure anomaly to determine a correlation between at least one change event and the failure anomaly, the subset of change event identifiers being associated with change events detected across at least two of the multiple hierarchical layers of the hierarchical structure of the cloud computing system;
• and
• generate a recommendation including a recommended action to perform on one or more nodes of the cloud computing system associated with the at least one change event based on the determined correlation between the at least one change event and the failure anomaly and generate a recommendation based on the determined correlation between the at least one change event and the failure anomaly.