I see that the author took a 'heuristical' approach for retrying tasks (having a predetermined amount of time a task is expected to take, and consider it failed if it wasn't updated in time) and uses SQS. If the solution is homemade anyway, I can only recommend leveraging your database's transactionality for this, which is a common pattern I have often seen recommend and also successfully used myself:
- At processing start, update the schedule entry to 'executing', then open a new transansaction and lock it, while skipping already locked tasks (`SELECT FOR UPDATE ... SKIP LOCKED`).
- At the end of processing, set it to 'COMPLETED' and commit. This also releases the lock.
This has the following nice characteristics:
- You can have parallel processors polling tasks directly from the database without another queueing mechanism like SQS, and have no risk of them picking the same task.
- If you find an unlocked task in 'executing', you know the processor died for sure. No heuristic needed
- At processing start, update the schedule entry to 'executing', then open a new transansaction and lock it, while skipping already locked tasks (`SELECT FOR UPDATE ... SKIP LOCKED`).
- At the end of processing, set it to 'COMPLETED' and commit. This also releases the lock.
This has the following nice characteristics:
- You can have parallel processors polling tasks directly from the database without another queueing mechanism like SQS, and have no risk of them picking the same task.
- If you find an unlocked task in 'executing', you know the processor died for sure. No heuristic needed