Elastic Jobs makes it easy to reliably execute operations across a large number of databases on a schedule or on-demand.
Jobs can be composed of one or more T-SQL scripts which run in parallel across many databases. The databases that are targeted by a job can be in one or more SQL servers, SQL elastic pools, or across multiple subscriptions. The list of databases in a server or pool can be determined at job run time, with the flexibility to include or exclude specific individual databases. A job’s maximum degree of parallelism across these targets can be configured if they are in a shared resource container such as a SQL elastic pool, ensuring that the resource container is not overburdened.
Elastic Jobs also reduces costs by using minimal compute resources while waiting for long-running jobs to complete. The outcome of a job’s steps on each target database are recorded in fine detail, and script output can be captured to a specified table.
This comprehensive range of features, focus on scale, and convenience make Elastic Jobs an ideal management tool for applications of any scale.