It is such a better model for the majority of queues. All you're doing is storing a message, hitting an HTTP endpoint and deleting the message on success. This makes it so much easier to scale, reason, and test task execution.
Update: since multiple people seem confused. I'm talking about the implementation of a job queue system, not suggesting that they use the GCP tasks product. That said, I would have just used GCP tasks too (assuming the usecase dictated it, fantastic and rock solid product.)
The trouble with hitting an HTTP API to queue a task is: what if it fails, or what if you're not sure about whether it failed? You can continue to retry in-band (although there's a definite latency disadvantage to doing so), but say you eventually give up, you can't be sure that no jobs were queued which you didn't get a proper ack for. In practice, this leads to a lot of uncertainty around the edges, and operators having to reconcile things manually.
There's definite scaling benefits to throwing tasks into Google's limitless compute power, but there's a lot of cases where a smaller, more correct queue is plenty of power, especially where Postgres is already the database of choice.
This is covered in the GCP Tasks documentation.
> There's definite scaling benefits to throwing tasks into Google's limitless compute power, but there's a lot of cases where a smaller, more correct queue is plenty of power, especially where Postgres is already the database of choice.
My post was talking about what I would implement if I was doing my own queue, as the authors were. Not about using GCP Tasks.
No, we don't operate like that. Call me out when I'm wrong technically, but don't tell me that because someone is some sort of celebrity that I should cut them some slack.
Everything he pointed out is literally covered in the GCP Tasks documentation.