Figure 2 shows the various phases involved in the optimization: Profiling, Learning, Optimizing, and Capacity reduction. Granulate starts the optimization process with a quick ROI analysis using an open-source profiling tool, gProfiler, which enables users to get a clear estimate of expected performance gains.

After the gProfiler assessment phase, Security Agent (sAgent) must be installed on the platform. Then sAgent will initiate the Learning phase. In that phase, sAgent continuously learns the data patterns and data flows to identify resources that are contended for, bottlenecks, and prioritization opportunities.

After a few days of learning, the agent is ready to be activated. The workload will show immediate performance improvements upon sAgent activation signified by capacity reduction and cost savings. The test results reported here are based on applications running in an on-premises environment.

Figure 2.   Granulate optimization phases