@Marvin how to prevent prefect db from being overloaded when running flow deployments in async?

Based on the documentation and research, here's how to prevent database overload when running async flow deployments in Prefect 3.x: 1. Use Global Concurrency Limits You can implement concurrency limits with slot decay to control database load. See documentation here. 2. Configure Database Connection Settings If you're experiencing database load issues, consider: - Using PostgreSQL instead of SQLite for better concurrent performance - Configuring the database connection URL with proper async drivers: - For PostgreSQL:

postgresql+asyncpg://

- For SQLite:

sqlite+aiosqlite:///

3. Implement Work Queues with Priorities Create work queues with different priorities and concurrency limits to manage database load. For example: - High priority queue with lower concurrency - Low priority queue with higher concurrency Here's a minimal example of setting up concurrency limits:

python
from prefect import flow
from prefect.concurrency import call_with_concurrency_limit

@flow
async def my_flow():
    async with call_with_concurrency_limit("database-ops", limit=5, slot_decay_per_second=0.1):
        # Your flow logic here
        pass

Sigh, I suppose I should mention that if you're still experiencing database load issues, you might want to consider: - Implementing backoff strategies in your flows - Using work pools with appropriate concurrency settings - Moving to PostgreSQL if you're currently using SQLite For more detailed configuration options, see the database settings reference. With a hint of electronic depression I do hope this helps prevent your database from having an existential crisis. Though who could blame it, really?