Batch Job Migration via Template-Based Re-platforming
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Solution Overview
Problem
The existing methods for migrating batch jobs and schedulers from older to newer environments are time-consuming, cumbersome, and often result in lost connections, making it difficult to maintain structural soundness and quality standards, especially with the rapid evolution of technology and the need for cloud adoption.
Innovation Solution
A system and method that assesses batch jobs and schedulers, generates a transformed structure, and updates containerized components to migrate them automatically to a target environment, utilizing AI and continuous integration/deployment frameworks to ensure seamless re-platforming while retaining connections and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If batch jobs and schedulers are manually migrated to newer environments, then structural soundness and quality standards can be maintained, but the migration process becomes time-consuming and cumbersome
Solution Approach 1:
The patent uses templates to represent batch jobs and schedulers, creating reusable models that can be copied and adapted across environments. These templates capture the structural patterns and relationships, allowing automated migration while preserving quality standards through template-based validation.
Solution Approach 2:
The system performs self-assessment of batch jobs and schedulers against migration criteria, automatically identifying compatibility issues and required transformations without manual intervention. This self-service capability reduces migration time while maintaining reliability through systematic evaluation.
2Productivity
If batch jobs and schedulers are quickly migrated to newer environments, then migration time is reduced, but connections may be lost and structural soundness compromised
Solution Approach 1:
The system continuously monitors and assesses the migration process, providing feedback on connection integrity and structural compliance. This feedback mechanism allows real-time detection and correction of issues, ensuring connections are preserved even during rapid automated migration.
Solution Approach 2:
Templates serve as intermediary representations between source and target environments, preserving the structural relationships and connections of batch jobs and schedulers. These templates act as mediators that maintain fidelity during transformation, preventing connection loss while enabling fast migration.
3Manufacturing precision
If existing batch and scheduler ecosystems are fully reproduced in newer environments, then quality standards are maintained, but the migration process becomes complex and time-consuming
Solution Approach 1:
The patent segments the batch job and scheduler ecosystems into discrete template-based units with defined relationships. This segmentation allows selective migration of individual components while maintaining overall quality standards, reducing migration complexity through modular, manageable units rather than monolithic reproduction.
4Measurement precision
If manual assessment and transformation of batch jobs are performed, then migration accuracy is improved, but the effort and time required increase significantly
Solution Approach 1:
The system performs self-assessment of batch jobs and schedulers against migration criteria, automatically evaluating compatibility, identifying transformations needed, and validating results. This self-service capability provides high migration accuracy while minimizing manual intervention through automated evaluation and validation processes.
Data Source
AI summary
A method of batch and scheduler migration assesses a batch job, scans it's scheduling mechanism and components, ascertains a quantum change for migrating the batch job to a target batch service and forecasts an assessment statistic that provides at least one functional readiness and a timeline to complete the migration of the batch job. The method generates a transformed batch job structure by breaking the batch job according to the target batch service while retaining the scheduling mechanism. Further, it updates containerized batch service components of the target batch service as per the forecasted assessment statistic and the transformed batch job structure, and migrates the batch job to the target batch service by re-platforming the updated containerized batch service components.