Question 1

How to scale Ratus for high availability with MongoDB?

Accepted Answer

Deploy multiple Ratus instances behind a load balancer with health checks, all connected to the same MongoDB replica set. This ensures failover and load distribution, as detailed in the replication section.

Question 2

Ratus vs Celery: which is better for Python background jobs?

Accepted Answer

Ratus excels in polyglot environments with its REST API, while Celery is Python-specific with richer integrations. Choose Ratus if you need language flexibility or are migrating from Celery to a REST-based system.

Question 3

How to handle task retries and failures in Ratus?

Accepted Answer

Implement idempotent task logic and use the commit API to mark completion. If a task times out or fails, it automatically reverts to pending state for retry, ensuring at-least-once execution.

Question 4

Can Ratus use Redis as a storage backend?

Accepted Answer

Redis support is listed in the roadmap but not yet implemented. Currently, only MemDB and MongoDB are available, so you'd need to wait or contribute to add Redis.

Question 5

What are the performance implications of MemDB list operations?

Accepted Answer

List operations in MemDB are relatively expensive as they scan the entire database or index, which could impact scenarios with frequent large queries, though the README notes these are uncommon.

Question 6

How to schedule tasks at specific future times in Ratus?

Accepted Answer

Set the 'scheduled' field when creating a task via the REST API. Ratus uses a unified model that combines priority and time-based scheduling, executing tasks only after their scheduled time.

Question 7

Is Ratus suitable as primary task storage?

Accepted Answer

No, the README explicitly recommends against it. Instead, store full task records in a separate database and use minimal descriptors in Ratus payloads to avoid data loss risks.

Ratus

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