Running on the devbox

The Flyte devbox is a lightweight local cluster that runs on your machine with Docker. It gives you a full Flyte environment — including the UI, scheduler, and object store — so you can test remote execution without deploying to a real cluster.

What you’ll need

Python 3.10+ in a virtual environment
Docker installed and running

Install the SDK

If you haven’t already, install the flyte package:

pip install flyte

Start the devbox

Launch the local cluster:

flyte start devbox

Devbox start

This pulls the necessary containers and starts a local Flyte instance. Once ready, the Flyte UI is available at http://localhost:30080.

The first start may take a few minutes while Docker images are downloaded.

Configure

Create a config file that points to the devbox:

        
    
flyte create config \
    --endpoint localhost:30080 \
    --project flytesnacks \
    --domain development \
    --builder local \
    --insecure

This creates .flyte/config.yaml configured to talk to your local devbox cluster.

Run a workflow on the devbox

Using the same hello.py from the Quickstart:

hello.py
                
                    
                
            
                
            
# hello.py

import flyte

# The `hello_env` TaskEnvironment is assigned to the variable `env`.
# It is then used in the `@env.task` decorator to define tasks.
# The environment groups configuration for all tasks defined within it.
env = flyte.TaskEnvironment(name="hello_env")

# We use the `@env.task` decorator to define a task called `fn`.
@env.task
def fn(x: int) -> int: # Type annotations are required
    slope, intercept = 2, 5
    return slope * x + intercept

# We also use the `@env.task` decorator to define another task called `main`.
# This is the is the entrypoint task of the workflow.
# It calls the `fn` task defined above multiple times using `flyte.map`.
@env.task
def main(x_list: list[int] = list(range(10))) -> float:
    y_list = list(flyte.map(fn, x_list)) # flyte.map is like Python map, but runs in parallel.
    y_mean = sum(y_list) / len(y_list)
    return y_mean

Run it on the devbox:

flyte run hello.py main

Without the --local flag, the workflow runs on the devbox cluster rather than in your local Python process. Tasks execute inside containers, just like they would on a remote cluster.

View results in the UI

Open http://localhost:30080 to see your workflow execution in the Flyte UI. You can inspect task inputs, outputs, logs, and execution timelines.

Devbox UI

Stop the devbox

When you’re done, shut down the cluster:

flyte stop devbox

Inline configuration

Skip the config file entirely by passing parameters directly.

Programmatic

CLI

Use flyte.init:

        
    
flyte.init(
    endpoint="localhost:30080",
    project="flytesnacks",
    domain="development",
    insecure=True,
)

Some parameters go after flyte, others after the subcommand:

        
    
flyte \
    --endpoint localhost:30080 \
    --insecure \
    --builder local \
    run \
    --domain development \
    --project flytesnacks \
    hello.py \
    main

See the CLI reference for details.

Delete the devbox

flyte delete devbox  # add the --volume flag to delete the Docker volume

Next steps

When you’re ready to run on a remote Flyte cluster, see Running on a remote cluster to configure the CLI and SDK.