SYSTEM AND METHODS FOR COMPLEX IT PROCESS ANNOTATION, TRACING, ANALYSIS, AND SIMULATION
A system and method for complex IT process annotation and tracing, analysis, and simulation, comprising at least a generative simulation platform, optimization engine, and metric engine, which is able to simulate a variety of simulations and develop adaptive models for simulation, and can be used more specifically for IT infrastructure simulation to identify vulnerable systems and vertices in an IT infrastructure, perform load-testing and quality control tests, and determine the overall health to known attacks and interruptions as a system or network topography change and update.
1 . A system for complex IT process annotation and tracing, analysis, and simulation, comprising:
a generative simulation platform comprising at least a first plurality of programming instructions stored in a memory of, and operating on at least one processor of, a computing device, wherein the first plurality of programming instructions, when operating on the at least one processor, cause the computing device to:
receive some combination of object, environment, or simulation data from a resource over a network;
parse received data using pattern recognition;
parametrize parsed data into objects for model building; and
alter parameters or objects to simulate random or unknown events occurring;
a directed computational graph comprising at least a second plurality of programming instructions stored in a memory of, and operating on at least one processor of, a computing device, wherein the second plurality of programming instructions, when operating on the at least one processor, cause the computing device to:
retrieve the first and second datasets from the time series data retrieval and storage server; and
comparatively analyze the first dataset against second dataset to determine an optimal model to use for predictive simulation; and
a multidimensional time series datastore comprising at least a third plurality of programming instructions stored in a memory of, and operating on at least one processor of, a computing device, wherein the third plurality of programming instructions, when operating on the at least one processor, cause the computing device to:
create a first dataset by retrieving from memory previously gathered and analyzed data based at least in part on a plurality of perils; and
create a second dataset by retrieving from memory synthetically generated data based at least on the plurality of perils; and
a metric engine operating on a computing device comprising at least a fourth plurality of programming instructions stored in a memory of, and operating on at least one processor of, a computing device, wherein the fourth plurality of programming instructions, when operating on the at least one processor, cause the computing device to:
determine and calculate a resilience metric for an IT infrastructure;
determine and calculate a blast radius metric for an IT infrastructure;
simulate attacks and interruptions on an IT infrastructure;
normalize calculated metrics;
prioritize metric scores for IT infrastructure health and safety;
develop and calculate graphs for domain controllers in an IT infrastructure; and
traverse network paths for additional infrastructure criticality simulations.
2 . The system of claim 1 , whereby a metric engine is hosted on a separate network-enabled computer from an IT infrastructure that it is used to analyze.
3 . The system of claim 1 , wherein a metric engine is hosted on a computer on the same network as the IT infrastructure it is used to analyze.
4 . A method for complex IT process annotation and tracing, analysis, and simulation, comprising the steps of:
receiving some combination of object, environment, or simulation data from a resource over a network, using a generative simulation platform;
parsing received data using pattern recognition, using a generative simulation platform;
parametrizing parsed data into objects for model building, using a generative simulation platform;
altering parameters or objects to simulate random or unknown events occurring, using a generative simulation platform;
retrieving the first and second datasets from the time series data retrieval and storage server, using a directed computational graph;
comparatively analyzing the first dataset against second dataset to determine an optimal model to use for predictive simulation, using a directed computational graph;
creating a first dataset by retrieving from memory previously gathered and analyzed data based at least in part on a plurality of perils, using a multidimensional time series datastore; and
creating a second dataset by retrieving from memory synthetically generated data based at least on the plurality of perils, using a multidimensional time series datastore;
determining and calculate a resilience metric for an IT infrastructure, using a metric engine;
determining and calculate a blast radius metric for an IT infrastructure, using a metric engine;
simulating attacks and interruptions on an IT infrastructure, using a metric engine;
normalizing calculated metrics, using a metric engine;
prioritizing metric scores for IT infrastructure health and safety, using a metric engine;
developing and calculate graphs for domain controllers in an IT infrastructure, using a metric engine; and
traversing network paths for additional infrastructure criticality simulations, using a metric engine.
5 . The method of claim 4 , whereby a metric engine is hosted on a separate network-enabled computer from an IT infrastructure that it is used to analyze.
6 . The method of claim 4 , wherein a metric engine is hosted on a computer on the same network as the IT infrastructure it is used to analyze.