Test and validate improvements

Perform small tests with minimized investment to reduce the risk of a large-scale effort.

Implement a representative copy of your workload in your testing environment to limit the cost and risk to perform testing and validation. Perform a predefined set of test transactions, measure the provisioned resources, and determine the resources used per unit of work to establish a testing baseline.

Implement your target improvement in the testing environment and repeat the test using the same methodology under the same conditions. Then measure the provisioned resources and resources used per unit of work with your improvement in place.

Calculate the percentage change from your baseline of the resources provisioned per unit of work, and determine the expected quantitative reduction in resources provisioned in your production environment. Compare these values against the anticipated values. Determine if the result is an acceptable level of improvement. Evaluate if any trade-offs in additional resources consumed make the net benefit from the improvement unacceptable.

Determine if the improvement is a success and if resources should be invested in implementing the change in production. If the change is evaluated as unsuccessful at this time, redirect your resources to test and validate your next target and continue your improvement cycle.

% Reduction in provisioned resources per unit of work	Quantitative reduction in provisioned resources	Action
Met expectations	Met expectations	Proceed with improvement
Did not meet expectations	Met expectations	Proceed with improvement
Met expectations	Did not meet expectations	Pursue alternative improvement
Did not meet expectations	Did not meet expectations	Pursue alternative improvement

Applying this step to the Example scenario, you perform tests to validate success.

After you perform the tests on the improved compression algorithm, the percentage reduction in resources provisioned per unit of work (the storage required for both the original image and the modified image) met expectations with an average 30% reduction in provisioned storage and negligible increased compute load.

You determine that the additional compute resources required to apply the improved compression algorithm to existing files in production is insignificant compared to the reduction in storage achieved. You confirmed success with the quantitative reduction in resources required (TBs of storage), and the improvement is approved for production deployment.