Queues & Parallelism

Queues allow you to run functions with managed concurrency. They are useful for controlling the number of functions run in parallel, or the rate at which functions are started.

To create a queue, specify its name:

from dbos import Queue

queue = Queue("example_queue")

You can then enqueue any DBOS workflow, step, or transaction. Enqueuing a function submits it for execution and returns a handle to it. Queued tasks are started in first-in, first-out (FIFO) order.

queue = Queue("example_queue")

@DBOS.step()
def process_task(task):
  ...

task = ...
handle = queue.enqueue(process_task, task)

Queue Example

Here's an example of a workflow using a queue to process tasks concurrently:

from dbos import DBOS, Queue

queue = Queue("example_queue")

@DBOS.step()
def process_task(task):
  ...

@DBOS.workflow()
def process_tasks(tasks):
  task_handles = []
  # Enqueue each task so all tasks are processed concurrently.
  for task in tasks:
    handle = queue.enqueue(process_task, task)
    task_handles.append(handle)
  # Wait for each task to complete and retrieve its result.
  # Return the results of all tasks.
  return [handle.get_result() for handle in task_handles]

Reliability Guarantees

Because queues use DBOS workflows, they provide the following reliability guarantees for enqueued functions. These guarantees assume that the application and database may crash and go offline at any point in time, but are always restarted and return online.

1. Enqueued functions always run to completion. If a DBOS process crashes and is restarted at any point after a function is enqueued, it resumes the enqueued function from the last completed step.
2. Enqueued steps (or steps called from enqueued workflows) are tried at least once but are never re-executed after they complete. If a failure occurs inside a step, the step may be retried, but once a step has completed, it will never be re-executed.
3. Enqueued transactions (or transactions called from enqueued workflows) commit exactly once.

Managing Concurrency

You can specify the concurrency of a queue, the maximum number of functions from this queue that may run concurrently, at two scopes: global and per process. Global concurrency limits are applied across all DBOS processes using this queue. Per process concurrency limits are applied to each DBOS process using this queue. If no limit is provided, any number of functions may run concurrently. For example, this queue has a maximum global concurrency of 10 and a per process maximum concurrency of 5, so at most 10 functions submitted to it may run at once, up to 5 per process:

from dbos import Queue

queue = Queue("example_queue", concurrency=10, worker_concurrency=5)

You may want to specify a maximum concurrency if functions in your queue submit work to an external process with limited resources. The concurrency limit guarantees that even if many functions are submitted at once, they won't overwhelm the process.

Rate Limiting

You can set rate limits for a queue, limiting the number of functions that it can start in a given period. Rate limits are global across all DBOS processes using this queue. For example, this queue has a limit of 50 with a period of 30 seconds, so it may not start more than 50 functions in 30 seconds:

queue = Queue("example_queue", limiter={"limit": 50, "period": 30})

Rate limits are especially useful when working with a rate-limited API, such as many LLM APIs.

In-Order Processing

You can use a queue with concurrency=1 to guarantee sequential, in-order processing of events. Only a single event will be processed at a time. For example, this app processes events sequentially in the order of their arrival:

from fastapi import FastAPI
from dbos import DBOS, Queue

app = FastAPI()
DBOS(fastapi=app)

queue = Queue("in_order_queue", concurrency=1)

@DBOS.step()
def process_event(event: str):
   ...

@app.post("/events/{event}")
def event_endpoint(event: str):
   queue.enqueue(process_event, event)

Queue Management

Because DBOS manages queues in Postgres, you can view and manage queued functions from the command line. These commands are also available for applications deployed to DBOS Cloud using the cloud CLI.

Listing Queued Functions

You can list all currently enqueued functions with:

dbos workflow list

By default, this lists all currently enqueued functions, including queued functions that are currently executing, but not completed functions You can parameterize this command for advanced search, see full documentation here.

Removing Queued Functions

You can remove a function from a queue with:

dbos workflow cancel <workflow-id>

This removes the function from its queue and transitions it to a CANCELLED state, so it will not run unless manually resumed.

Resuming Workflows

You can start execution of an enqueued function with:

dbos workflow resume <workflow-id>

This starts execution immediately, bypassing the queue and transitioning the function to a PENDING state. It also removes the function from its queue.