Redeploying workload based on expanded computing capacity

A data processing system based on a cloud platform comprising:

• at least one processor implementing:
• a distributed task scheduling system;
• a cloud elastic scaling system;
• and
• a task execution system,
• wherein the distributed task scheduling system comprises a task module,
• wherein the cloud elastic scaling system comprises a workload scaling module and a computing node scaling module, and
• wherein the task execution system comprises several computing nodes;
• and
• wherein the task module is used for a target user to submit a task processing request of a scientific computing task, and determine whether the number of obtained task processing requests reaches a preset capacity expansion threshold, and if so, generate a workload capacity expansion request;
• wherein the workload scaling module is used to trigger the computing node scaling module to expand the computing node according to the capacity expansion request;
• and
• wherein the computing node scaling module is used to expand the computing node according to the capacity expansion request;
• redeploy the workload based on the expanded computing nodes after the capacity expansion processing, so as to execute the scientific computing task based on the redeployed workload and
• set the workload as a set of metadata, wherein the metadata includes the image address of a docker container to be run and the computing resource requirements required to run the workload.