US 2024/0256361 A1Published application

Predictive load modeling using a digital twin of a computing infrastructure

AssigneeBank of America Corporation

InventorsGeorge Albero, Maharaj Mukherjee, Jinna Zevulun Kim, Timothy Scott Murphy

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Abstract

A system includes a computing infrastructure, a memory that stores a digital twin of the computing infrastructure, and at least one processor configured to generate simulated containers relating to a job flow, wherein each simulated container simulates a corresponding actual container relating to the job flow that is to run on the computing infrastructure. The digital twin is configured based on configuration parameters to mimic a particular state of the computing infrastructure. A simulation of the job flow is iteratively run on the configured digital twin to determine an allocation of the simulated containers to simulated hardware components that resulted in one or more performance parameters satisfying the respective thresholds.

Claims20

Dependent claims

A system comprising:

a computing infrastructure comprising a plurality of computing nodes;
a memory that stores a digital twin of at least a portion of the computing infrastructure, wherein the digital twin is a software representation of at least the portion of the computing infrastructure;
and
at least one processor communicatively coupled to the computing infrastructure and the memory, wherein the at least one processor is configured to:
generate a plurality of simulated containers relating to a job flow, wherein each simulated container simulates a corresponding actual container relating to the job flow that is to run on the computing infrastructure, and wherein each container is a self-contained virtual environment that comprises software components to process at least a portion of a job relating to the job flow;
receive configuration parameters relating to the digital twin, wherein the configuration parameters, when applied to the digital twin, configure the digital twin to mimic a particular state of the computing infrastructure;
configure the digital twin based on the received configuration parameters;
run a simulation of the job flow on the digital twin that is configured based on the configuration parameters, wherein the simulation comprises deploying using a simulated load balancer of the digital twin, the simulated containers relating to the job flow on a plurality of simulated hardware components in a portion of the digital twin representing a corresponding portion of the computing infrastructure;
record at least one performance parameter as a result of the simulation, wherein the at least one performance parameter is indicative of a performance of a simulated hardware component of the computing infrastructure;
and
if one or more of the performance parameters do not satisfy respective thresholds, run an iteration comprising:
reallocating at least a portion of the simulated containers to a plurality of simulated hardware components of a different portion of the digital twin representing a corresponding different portion of the computing infrastructure;
rerunning the simulation after reallocating at least the portion of the simulated containers;
and
if the one or more performance parameters satisfy the respective thresholds, recording an allocation of the simulated containers that resulted in the one or more performance parameters satisfying the respective thresholds.

12 more elements

A method for allocating computing resources to a job flow, comprising:

generating a plurality of simulated containers relating to the job flow, wherein each simulated container simulates a corresponding actual container relating to the job flow that is to run on a computing infrastructure, and wherein each container is a self-contained virtual environment that comprises software components to process at least a portion of a job relating to the job flow;
receiving configuration parameters relating to a digital twin of at least a portion of the computing infrastructure, wherein:
wherein the digital twin is a software representation of at least the portion of the computing infrastructure;
and
the configuration parameters, when applied to the digital twin, configure the digital twin to mimic a particular state of the computing infrastructure;
configuring the digital twin based on the received configuration parameters;
running a simulation of the job flow on the digital twin that is configured based on the configuration parameters, wherein the simulation comprises deploying using a simulated load balancer of the digital twin, the simulated containers relating to the job flow on a plurality of simulated hardware components in a portion of the digital twin representing a corresponding portion of the computing infrastructure;
recording at least one performance parameter as a result of the simulation, wherein the at least one performance parameter is indicative of a performance of a simulated hardware component of the computing infrastructure;
and
if one or more of the performance parameters do not satisfy respective thresholds, running an iteration comprising:
reallocating at least a portion of the simulated containers to a plurality of simulated hardware components of a different portion of the digital twin representing a corresponding different portion of the computing infrastructure;
rerunning the simulation after reallocating at least the portion of the simulated containers;
and
if the one or more performance parameters satisfy the respective thresholds, recording an allocation of the simulated containers that resulted in the one or more performance parameters satisfying the respective thresholds.

11 more elements

A computer-readable medium storing instructions that when executed by a processor causes the processor to:

generate a plurality of simulated containers relating to the job flow, wherein each simulated container simulates a corresponding actual container relating to the job flow that is to run on a computing infrastructure, and wherein each container is a self-contained virtual environment that comprises software components to process at least a portion of a job relating to the job flow;
receive configuration parameters relating to a digital twin of at least a portion of the computing infrastructure, wherein:
wherein the digital twin is a software representation of at least the portion of the computing infrastructure;
and
the configuration parameters, when applied to the digital twin, configure the digital twin to mimic a particular state of the computing infrastructure;
configure the digital twin based on the received configuration parameters;
run a simulation of the job flow on the digital twin that is configured based on the configuration parameters, wherein the simulation comprises deploying using a simulated load balancer of the digital twin, the simulated containers relating to the job flow on a plurality of simulated hardware components in a portion of the digital twin representing a corresponding portion of the computing infrastructure;
record at least one performance parameter as a result of the simulation, wherein the at least one performance parameter is indicative of a performance of a simulated hardware component of the computing infrastructure;
and
if one or more of the performance parameters do not satisfy respective thresholds, run an iteration comprising:
reallocate at least a portion of the simulated containers to a plurality of simulated hardware components of a different portion of the digital twin representing a corresponding different portion of the computing infrastructure;
rerun the simulation after reallocating at least the portion of the simulated containers;
and
if the one or more performance parameters satisfy the respective thresholds, record an allocation of the simulated containers that resulted in the one or more performance parameters satisfying the respective thresholds.

11 more elements

Dependencies are inferred from the claim text.