background-job

Scalable background jobs use paging strategies like SimplePaged and BatchScrolling patterns to process large datasets efficiently. This Skill automates job orchestration with explicit paging, handling recurring tasks, data synchronization, and maintenance jobs while managing page sizing and multi-tenant contexts to avoid memory overload.

Multi-tenant aware background jobs isolate processing per tenant using repository queries and executor classes. This approach ensures each tenant's data syncs independently on a schedule, preventing cross-tenant data leakage and allowing independent job execution patterns for each tenant.

Batch data processing with paging uses scrolling and batch-scrolling patterns to iterate through large datasets in manageable chunks. The Skill provides job type decision trees and page sizing logic, letting you choose between simple pagination or continuous scrolling based on your data volume and performance needs.

Yes. This Skill handles both scheduled recurring jobs (cron-based) and one-time batch processing through the same job orchestration framework. The flexible design supports data synchronization, maintenance tasks, and recurring reports with consistent paging and multi-tenant handling across both patterns.

Background job design includes built-in scheduling and monitoring patterns that track job execution, handle failures, and manage retry logic. These patterns integrate with your job executor classes, providing visibility into batch processing progress and multi-tenant job status across recurring tasks.