What's the design pattern you recommend Temporal users use to implement multiple consumers?
Usecase: Handle a large, spiky backlog by dynamically sharding the consumer input, starting and putting multiple consumers to work until the backlog is within nominal specs.
Eg: Shipping orders during a sales event. Each S&H order takes the same response time but multiple S&H orders can be parallelized and there are a few hundred thousand orders pending. Of course, S&H order can fail, in which case they are restored to the pending state after a timeout or loss of a lock
ah for this one you dont need multiple “consumers”, you need multiple workers, in our model. they’re kinda the same thing when u get down to it but this is the paradigm shift.
every temporal workflow goes into an assigned task queue, and Temporal handles distributing/load balancing to multiple workers polling that queue. you can have 10000 orders coming in simultaneously to 1 task queue being processed by 5 workers for example and Temporal would register heavy load but would still process through all that work in due time. the beauty is that when you write workflows you dont have to worry about acquiring locks or whatever, just write as though you had one durable long running process per order. its very freeing.
this is not to say it does everything, ie Temporal is not a replacement for a true pubsub model. we just described N workers processing 1 type of workflow initiated 10,000 times, but its not designed for 1 event type initiated 10,000 times that are reacted to by N types of processes that are supposed to be completely decoupled.
What's the design pattern you recommend Temporal users use to implement multiple consumers?
Usecase: Handle a large, spiky backlog by dynamically sharding the consumer input, starting and putting multiple consumers to work until the backlog is within nominal specs.
Eg: Shipping orders during a sales event. Each S&H order takes the same response time but multiple S&H orders can be parallelized and there are a few hundred thousand orders pending. Of course, S&H order can fail, in which case they are restored to the pending state after a timeout or loss of a lock