Machine logic for job management based on contextual factors
View Patent ↗Technology for revising a smart contract, including a set of machine logic based rules for job management of jobs to be performed under an SLA (service level agreement). The machine learning algorithm is refined and optimized dynamically based on intermittently received context data (historical, relevant operational data—may be augmented with projections regarding future events and/or operations). Also, the SLA is self-evolving so that its terms also change based an analysis of the context data.
1. A computer-implemented method (CIM) comprising:
receiving a first version of a smart contract designed for use with a first SLA (service level agreement), the first version of the smart contract including a plurality of computing job control rules for performing job management in a computing environment governed by the first SLA;
receiving a plurality of computing jobs;
determining a first workflow for running and prioritizing the plurality of computing jobs;
starting to run the plurality of computing jobs in the computer environment according to the first workflow and the plurality of computing job control rules and governed by the first SLA;
after the plurality of computing jobs has begun to run, collecting context data, with the context data including operational information regarding the running and status of the plurality of computing jobs in the computing environment;
while at least some of the plurality of computing jobs are still running, dynamically determining a second workflow based on the context data;
after the dynamic determination of the second workflow, continuing to run the plurality of computing jobs in the computer environment according to the second workflow of the plurality of computing job control rules and governed by the first SLA;
training a machine learning algorithm using the set of context data as training data; and
applying the machine learning algorithm to the first version of the smart contract, with the application of the machine learning algorithm making at least a first change to the first job control rule and to thereby obtain a second version of the smart contract including a changed version of the first job control rule.
2. The CIM of claim 1 further comprising:
receiving requests for performance of a plurality of requested computing jobs to be performed under second version of smart contract and governed by the first SLA;
determining a contextual situation of the computer system that will be used to perform the plurality of requested computing jobs; and
applying the revised first job control rule of the second version of the smart contract to the contextual situation a prioritized order for performance of the plurality of requested computing jobs.
3. The CIM of claim 1 further comprising: performing the plurality of requested computing jobs in the prioritized order.
4. A computer program product (CPP) comprising: a set of non-transitory storage device(s); and computer code stored collectively in the set of storage device(s), with the computer code including data and instructions to cause a processor(s) set to perform at least the following operations:
receiving a first version of a smart contract designed for use with a first SLA (service level agreement), the first version of the smart contract including a plurality of computing job control rules for performing job management in a computing environment governed by the first SLA;
receiving a plurality of computing jobs;
determining a first workflow for running and prioritizing the plurality of computing jobs; starting to run the plurality of computing jobs in the computer environment according to the first workflow and the plurality of computing job control rules and governed by the first SLA;
after the plurality of computing jobs has begun to run, collecting context data, with the context data including operational information regarding the running and status of the plurality of computing jobs in the computing environment;
while at least some of the plurality of computing jobs are still running, dynamically determining a second workflow based on the context data;
after the dynamic determination of the second workflow, continuing to run the plurality of computing jobs in the computer environment according to the second workflow of the plurality of computing job control rules and governed by the first SLA;
training a machine learning algorithm using the set of context data as training data; and
applying the machine learning algorithm to the first version of the smart contract, with the application of the machine learning algorithm making at least a first change to the first job control rule and to thereby obtain a second version of the smart contract including a changed version of the first job control rule.
5. The CPP of claim 4 further comprising:
receiving requests for performance of a plurality of requested computing jobs to be performed under second version of smart contract and governed by the first SLA;
determining a contextual situation of the computer system that will be used to perform the plurality of requested computing jobs; and
applying the revised first job control rule of the second version of the smart contract to the contextual situation a prioritized order for performance of the plurality of requested computing jobs.
6. The CPP of claim 4 further comprising: performing the plurality of requested computing jobs in the prioritized order.
7. A computer system (CS) comprising:
a processor(s) set;
a set of storage device(s); and
computer code stored collectively in the set of storage device(s), with the computer code including data and instructions to cause the processor(s) set to perform at least the following operations:
receiving a first version of a smart contract designed for use with a first SLA (service level agreement), the first version of the smart contract including a plurality of computing job control rules for performing job management in a computing environment governed by the first SLA;
receiving a plurality of computing jobs;
determining a first workflow for running and prioritizing the plurality of computing jobs;
starting to run the plurality of computing jobs in the computer environment according to the first workflow and the plurality of computing job control rules and governed by the first SLA;
after the plurality of computing jobs has begun to run, collecting context data, with the context data including operational information regarding the running and status of the plurality of computing jobs in the computing environment;
while at least some of the plurality of computing jobs are still running, dynamically determining a second workflow based on the context data;
after the dynamic determination of the second workflow, continuing to run the plurality of computing jobs in the computer environment according to the second workflow of the plurality of computing job control rules and governed by the first SLA;
training a machine learning algorithm using the set of context data as training data; and
applying the machine learning algorithm to the first version of the smart contract, with the application of the machine learning algorithm making at least a first change to the first job control rule and to thereby obtain a second version of the smart contract including a changed version of the first job control rule.
8. The CS of claim 7 further comprising:
receiving requests for performance of a plurality of requested computing jobs to be performed under second version of smart contract and governed by the first SLA;
determining a contextual situation of the computer system that will be used to perform the plurality of requested computing jobs; and
applying the revised first job control rule of the second version of the smart contract to the contextual situation a prioritized order for performance of the plurality of requested computing jobs.
9. The CS of claim 8 further comprising: performing the plurality of requested computing jobs in the prioritized order.