Framework for end-to-end assurance for application workloads

A method comprising:

• receiving, by processing circuitry of a computing system, time series data comprising performance indicators for elements of a plurality of layers of a system having host computing devices that execute workloads for an application, the time series data generated by the elements;
• create, based on mapping, using the time series data, Graphics Processing Units (GPUs) of a compute layer of the plurality of layers to network devices of a network layer of the plurality of layers, a dependency graph comprising nodes and edges, the nodes representing the elements of the plurality of layers, and the edges representing cross-layer relationships between pairs of the elements, each of the elements of each pair being of different layers of the plurality of layers;
• determining, by the processing circuitry and based on the time series data, an anomaly in the performance of a workload of the workloads for the application;
• determining, by the processing circuitry and based on a dependency of the workload on an element of the network layer within the dependency graph, an issue with the element of the network layer as a root cause of the anomaly in the performance of the workload;
• and
• performing, by the processing circuitry, a remedial action for the issue with the element of the network layer as a root cause of the anomaly in the performance of the workload.

Non-transitory, computer-readable media comprising instructions that, when executed, are configured to cause processing circuitry to:

• receive time series data comprising performance indicators for elements of a plurality of layers of a system having host computing devices that execute workloads for an application, the time series data generated by the elements;
• create, based on mapping, using the time series data, Graphics Processing Units (GPUs) of a compute layer of the plurality of layers to network devices of a network layer of the plurality of layers, a dependency graph comprising nodes and edges, the nodes representing the elements of the plurality of layers, and the edges representing cross-layer relationships between pairs of the elements, each of the elements of each pair being of different layers of the plurality of layers;
• determine, based on the time series data, an anomaly in the performance of a workload of the workloads for the application;
• determine, based on a dependency of the workload on an element of the network layer within the dependency graph, an issue with the element of the network layer as a root cause of the anomaly in the performance of the workload;
• and
• perform a remedial action for the issue with the element of the network layer as a root cause of the anomaly in the performance of the workload.