Systems engineering

Representative Work

Optimizing Future State using Modeling + Simulation

A US government agency wanted to modernize its large portfolio of infrastructure services, including compute, storage, and networking services. To determine the proper mix of infrastructure capacity and their placement (various data centers, edge locations, facilities) throughout the world, a detailed model was developed.

Axiologic Solutions’ systems engineers used various MBSE tools to create the resource allocation model. The developed model included:

  • the profile of the various facilities to house equipment that considered floor space, power availability, racks, desks, connectivity, etc.
  • the profile of the users that considered headcount, location, applications used, networks used, etc.
  • the profile of the systems and applications that considered resources consumed, relationships, usage patterns, etc.
  • the profile of the networks that considered topology, bandwidth, latency, usages, etc.
  • the profile of the data that considered volume, growth, usages, security, etc.
  • the profile of workflows and business processes that considered volume, frequency, triggering events, etc.
  • the SLAs and expectations for performance, availability, reliability, and scalability.

Various historical statistics were captured to seed the model. Future demand levels for different resources were derived. All data was processed using modern data engineering techniques. The model was then used in various simulations (including Monte Carlo) to optimize various objective functions such as cost, security, availability, and extendibility.

Using the model’s results of the optimized future state (including cost, power, cooling, performance, etc.), a transition plan from the current state, including acquisition, was developed.

With the model in place, the customer was able to effectively plan this migration, reducing waste and eliminating risk.