MetricSage
Description
We intend to build a machine-learning model to optimize cost for the Claim Evidence API within VBMS. The input data will be system metrics collected by Dynatrace, such as CPU and memory usage, and the output will be projected usage and optimal sizing of resources based on that usage. VA Project Managers and Benefits Integrated Platform engineers will use this system to determine the resources to provision and the expected cost of those resources. This use case will be used to anticipate future cost in compute based on claim workload.
Detailed example
A dashboard that shows present and anticipated future compute utilization.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
proper forecasting will allows us to right size our compute resources.
Controls / human review
ATO: Not reported; PIA: Not published