Prevent too many tasks from running simultaneously using tags.
Use task tags to limit how many tasks can run at the same time. This is useful when tasks interact with shared resources like databases or external APIs.
from prefect import flow, task@task(tags=["database"])def fetch_data(): # This task will respect the "database" tag's concurrency limit return "data"@flowdef my_workflow(): fetch_data()
As of Prefect 3.4.19, tag-based concurrency limits are backed by global concurrency limits. When you create a tag-based limit, you’ll see a corresponding global concurrency limit with the name tag:{tag_name}.
Tags without concurrency limits allow unlimited concurrent runs. Once you set a limit, only that many tasks with the tag can run simultaneously.
from prefect import flow, task@task(tags=["database"])def query_database(query: str): # Simulate database work return f"Results for {query}"@flowdef data_pipeline(): # These will respect the "database" tag limit query_database("SELECT * FROM users") query_database("SELECT * FROM orders") query_database("SELECT * FROM products")
When a task has multiple tags, it must have available concurrency slots for all tags to run.
from prefect import task@task(tags=["database", "analytics"])def complex_query(): # This task needs available slots in both "database" AND "analytics" limits return "complex results"
# Set a limit of 10 for the "database" tagprefect concurrency-limit create database 10# View all concurrency limitsprefect concurrency-limit ls# View details about a specific tag's limitprefect concurrency-limit inspect database# Delete a concurrency limitprefect concurrency-limit delete database
import asynciofrom prefect import get_clientasync def manage_concurrency_limits(): async with get_client() as client: # Set a concurrency limit of 10 on the "database" tag await client.create_concurrency_limit( tag="database", concurrency_limit=10 ) # Read current limit for a tag limit = await client.read_concurrency_limit_by_tag(tag="database") print(limit) # View all concurrency limits limits = await client.read_concurrency_limits(limit=10, offset=0) print(limits) # Delete a concurrency limit await client.delete_concurrency_limit_by_tag(tag="database")asyncio.run(manage_concurrency_limits())
When a task is delayed due to a concurrency limit, it will wait for a set wait time before retrying. You can set the wait time for when tasks are delayed due to concurrency limits:
prefect config set PREFECT_SERVER_TASKS_TAG_CONCURRENCY_SLOT_WAIT_SECONDS=60
Note: this setting needs to be set on the Prefect server, not the Prefect client.
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