GenServer Bottleneck Analysis

This document analyzes the use of GenServer.call within the application. The extensive use of synchronous calls is a significant architectural concern that can lead to performance bottlenecks, reduced concurrency, and cascading failures under load.

1. Audit Findings

A search for GenServer.call has revealed an extremely high number of instances across the codebase, particularly within the lib/mabeam and lib/foundation directories. This pattern is especially prevalent in modules that act as central registries, managers, or services.

Key Hotspots:

• lib/mabeam/economics.ex: Contains a very large number of calls, suggesting that complex economic calculations may be happening synchronously.
• lib/mabeam/coordination.ex: Manages complex coordination protocols using synchronous calls, which can block critical application logic.
• lib/mabeam/process_registry.ex & lib/mabeam/agent_registry.ex: These registries are central points of failure and can easily become bottlenecks if all interactions are synchronous.
• lib/foundation/services/*.ex: Many services expose their entire API via GenServer.call, limiting their ability to handle concurrent requests.

2. Analysis and Recommendations

The architectural pattern of using a single GenServer to manage a complex domain and exposing its entire API via synchronous calls is an anti-pattern in high-concurrency systems. It serializes all operations through a single process, effectively creating a global lock on that part of the system.

Recommendations:

1. Favor Asynchronous Operations (cast): For any operation that does not require an immediate response, GenServer.cast should be used instead of call. This is a fundamental shift from a synchronous to an asynchronous mindset.

2. Separate Read and Write APIs: For GenServers that manage state, consider separating the read and write APIs. Write operations can be handled by the GenServer, while read operations can be directed to an ETS table or a separate, replicated read-only process. This is a form of the CQRS (Command Query Responsibility Segregation) pattern.

3. Delegate Work to Tasks: For long-running or computationally intensive operations, the GenServer should not perform the work itself. It should delegate the work to a Task (supervised, of course) and immediately return, freeing it up to handle other requests. The result of the task can be sent back to the caller asynchronously.

4. Introduce More Granular Processes: Instead of a single, monolithic GenServer for a whole subsystem, consider breaking it down into smaller, more focused processes. For example, instead of one economics server, there could be a GenServer per auction or per market.

Next Steps:

• Identify Top Offenders: Prioritize the GenServers with the highest number of calls and the most complex handle_call implementations for refactoring.
• Refactor to Asynchronous APIs: Begin refactoring the identified GenServers to favor asynchronous operations. This will likely require changes to the client code as well.
• Update Developer Guidelines: The project’s developer guidelines should be updated to strongly discourage the overuse of GenServer.call and provide clear patterns for asynchronous communication.