⭐ IRS Order API for Scalable Job and Batch Delegation

[mkanal]

As system architect,
I want to design the IRS Order API to support scalable job and batch processing by delegating tasks to multiple IRS instances, either through a master instance or a set of equal peer workers,
so that to improve performance and efficiency.

To handle an increasing volume of job and batch requests, the IRS Order API will be designed to enable horizontal scaling of the IRS. The API should support distributing jobs and batches to multiple IRS instances dynamically, either through a master instance that controls job delegation or through a cluster of equal peer worker instances that coordinate job processing among themselves.

Hints / Details

Decision:
The IRS Order API will be redesigned to support one of the following modes of job and batch delegation:

• Master Instance Mode: A single master IRS instance will manage job delegation and distribute tasks to multiple worker irs instances.
• Peer-to-Peer Worker Mode: Multiple IRS instances will act as equal peers, coordinating among themselves to process jobs and batches without a central master instance.

Acceptance Criteria

Concept and ADR created covering following criteria

• The IRS Order API must support job and batch delegation to multiple IRS instances.
• Concept evaluates multiple approaches : a master instance model and a peer-to-peer worker model or alternatives
• The solution should ensure that jobs are evenly distributed across available IRS instances to optimize resource utilization.
• The system should be resilient to failures, with automatic recovery and rebalancing of jobs if an IRS instance becomes unavailable.
• The API should provide monitoring and logging capabilities to track job statuses, delegation, and instance performance.
• The API should support secure communication between IRS instances, ensuring data integrity and confidentiality.

Out of Scope

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