# Local Agent

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The local agent starts flow runs as processes local to the same machine it is running on. It's useful for running lightweight workflows on standalone machines, testing flows locally, or quickly getting acclimated with the Prefect API. While the local agent is fully capable of executing flows in conjunction with the Prefect API, we generally recommend using one of the other agents to help with modularity and scale.

# Requirements

The local agent has no outside dependencies and only requires that Prefect is installed.

If you want to use a Prefect backend for orchestrating and managing flows, you can use Prefect Cloud or the open-source Prefect Server.

To learn more about Prefect Cloud, which is the recommended orchestration backend, see the Orchestration layer set up documentation.

To learn more about Prefect Server, see the Server Overview documentation and the instructions for Deploying to a single node.


If running the local agent inside a Docker container, we recommend you also use an init process like tini. Running without an init process may result in lingering zombie processes accumulating in your container. If you're using the official Prefect docker images then this is already handled for you.

# Flow Configuration

The Local Agent will deploy flows using either a UniversalRun (the default) or LocalRun run_config. Using a LocalRun object lets you customize the deployment environment for a flow (exposing env, working_dir, etc...):

from prefect.run_configs import LocalRun

# Configure extra environment variables for this flow,
# and set a custom working directory
flow.run_config = LocalRun(
    env={"SOME_VAR": "VALUE"},

See the LocalRun documentation for more information.

# Agent Configuration

The local agent can be started from the Prefect CLI as

$ prefect agent local start

API Keys Cloud

When using Prefect Cloud, this will require a service account API key, see here for more information.

Below we cover a few common configuration options, see the CLI docs for a full list of options.

# Labels

Like all agents, the local agent can optionally be configured with labels. These are used to filter which flow runs an agent can deploy.

$ prefect agent local start -l label1 -l label2

By default, the local agent will include a label for its hostname. This is useful for flows using Local Storage, which also adds this label by default. To disable this default label, use the --no-hostname-label flag:

$ prefect agent local start --no-hostname-label

# Streaming Flow Run Logs

The local agent includes an option to stream logs from its running flows to the console, rather than relying on Prefect Cloud/Server to access these logs. This can be useful for debugging flow runs locally. To enable, use the --show-flow-logs flag:

$ prefect agent local start --show-flow-logs

# Using with Supervisor

Supervisor is a tool for managing long running processes on a UNIX-like operating system. This can be useful for deployments where you want to ensure you have a Prefect Local Agent always running in the background.

The Prefect CLI provides a command for generating an example supervisord.conf file for managing a local agent.

$ prefect agent local install

This outputs example contents of a supervisord.conf. The install command accepts many of the same arguments as prefect agent local start, allowing for easy configuration. See the CLI docs for information on all available options. Likewise, see the Supervisor docs for more information on installing and using supervisor.

# Multiple local agents with the same label

We recommend assigning a unique label to each agent, particularly when running multiple local agents. While Prefect Cloud has a mechanism to ensure that each flow run gets executed only once, race conditions may occur if you have multiple agents with the same label. The example below shows that instead of starting all agents with label "prod", we can add a number to make it unique.

$ prefect agent local start --no-hostname-label --label prod1
$ prefect agent local start --no-hostname-label --label prod2

Currently, Prefect has no notion of a task queue that would allow load-balancing flow runs across multiple agents based on available resources on each agent. If you need such functionality, you would need to assign unique labels to your agents, and then assign corresponding labels to your flows to spread the load across multiple agents. For instance:

Flow 1:

from prefect.run_configs import UniversalRun
with Flow(name="example1", run_config=UniversalRun(labels=["prod1"])) as flow:

Flow 2:

from prefect.run_configs import UniversalRun
with Flow(name="example2", run_config=UniversalRun(labels=["prod2"])) as flow:

To help with scale, we recommend using one of the other agents, such as: