Install the Bacalhau CLI

In this tutorial, you'll learn how to install and run a job with the Bacalhau client using the Bacalhau CLI or Docker.

Step 1 - Install the Bacalhau Client

The Bacalhau client is a command-line interface (CLI) that allows you to submit jobs to the Bacalhau. The client is available for Linux, macOS, and Windows. You can also run the Bacalhau client in a Docker container.

By default, you will submit to the Bacalhau public network, but the same CLI can be configured to submit to a private Bacalhau network. For more information, please read Running Bacalhau on a Private Network.

Step 1.1 - Install the Bacalhau CLI

You can install or update the Bacalhau CLI by running the commands in a terminal. You may need sudo mode or root password to install the local Bacalhau binary to /usr/local/bin:

curl -sL | bash

Step 1.2 - Verify the Installation

To verify installation and check the version of the client and server, use the version command. To run a Bacalhau client command with Docker, prefix it with docker run

bacalhau version

If you're wondering which server is being used, the Bacalhau Project has a demo network that's shared with the community. This network allows you to familiarize with Bacalhau's capabilities and launch jobs from your computer without maintaining a compute cluster on your own.

Step 2 - Submit a Hello World job

To submit a job in Bacalhau, we will use the bacalhau docker run command. The command runs a job using the Docker executor on the node. Let's take a quick look at its syntax:

bacalhau docker run [FLAGS] IMAGE[:TAG] [COMMAND]
bacalhau docker run ubuntu echo Hello World

We will use the command to submit a Hello World job that runs an echo program within an Ubuntu container.

Let's take a look at the results of the command execution in the terminal:

Job successfully submitted. Job ID: f8e7789d-8e76-4e6c-8e71-436e2d76c72e
Checking job status... (Enter Ctrl+C to exit at any time, your job will continue running):

    Communicating with the network  ................  done   0.2s
       Creating job for submission  ................  done   0.7s
                   Job in progress  ................  done   2.1s

To download the results, execute:
    bacalhau get f8e7789d-8e76-4e6c-8e71-436e2d76c72e

To get more details about the run, execute:
    bacalhau describe f8e7789d-8e76-4e6c-8e71-436e2d76c72e

After the above command is run, the job is submitted to the public network, which processes the job and Bacalhau prints out the related job id:

Job successfully submitted. Job ID: 9d20bbad-c3fc-48f8-907b-1da61c927fbd
Checking job status...

The job_id above is shown in its full form. For convenience, you can use the shortened version, in this case: 9d20bbad.

While this command is designed to resemble Docker's run command which you may be familiar with, Bacalhau introduces a whole new set of flags to support its computing model.

Step 3 - Checking the State of your Jobs

After having deployed the job, we now can use the CLI for the interaction with the network. The jobs were sent to the public demo network, where it was processed and we can call the following functions. The job_id will differ for every submission.

Step 3.1 - Job status:

You can check the status of the job using bacalhau list command adding the --id-filter flag and specifying your job id.

bacalhau list --id-filter 9d20bbad

Let's take a look at the results of the command execution in the terminal:

CREATED   ID          JOB                                       STATE      PUBLISHED
15:24:31  0ed7617d    Type:"docker",Params:"map[Entrypoint:<ni  Completed
                       l> EnvironmentVariables:[] Image:ubuntu:
                       latest Parameters:[sh -c uname -a && ech
                       o "Hello from Docker Bacalhau!"] Working

When it says Completed, that means the job is done, and we can get the results.

For a comprehensive list of flags you can pass to the list command check out the related CLI Reference page

Step 3.2 - Job information:

You can find out more information about your job by using bacalhau describe.

bacalhau describe 9d20bbad

Let's take a look at the results of the command execution in the terminal:

    APIVersion: V1beta2
        ClientID: 0ff57b2521334a92e9ddab4b2f8202c887b1eaa35d2aa945ab0e247d3bc0aa88
        CreatedAt: "2023-12-21T15:24:31.750306239Z"
        ID: 0ed7617d-d5ff-40f7-8411-89830b3f3058
        RequesterNodeID: QmbxGSsM6saCTyKkiWSxhJCt6Fgj7M9cns1vzYtfDbB5Ws
        RequesterPublicKey: CAASpgIwggEiMA0GCSqGSIb3DQEBAQUAA4IBDwAwggEKAoIBAQDEHTUAD1JzO0130W9vsaDGhU0PVgpcNjG3fYlE0sJ1BiBWENFuP4jx3Q9alcjNGhdRFdju0Mb/fidTOtJcPhxTdb+H6JxFP6HsADGes9jU4ylBU2SL2vfdb0KXzKdXjNHGGf4BuCGTcH07Oqxp209diK/cT7takL2fLjcgs1tM+6PzlfGzFqCPxvh9Sa0ek34mdmHjcp1XH8yjF1OKOuHvD+pYphqvOBL/2LEN+EBC4fz/QUnhUajCmKYO83MJcNUXSGxb4AN6K3DpVV+cJph7fj9ADdP7i996o2S4Gkz8W4Wpt/jICaPpkUjmyU3Jgcw7MHkZaYEzWxnnO2J936+pAgMBAAE=

This outputs all information about the job, including stdout, stderr, where the job was scheduled, and so on.

Step 3.3 - Job download:

You can download your job results directly by using bacalhau get.

bacalhau get 9d20bbad

This results in

Fetching results of job '0ed7617d'...
Results for job '0ed7617d' have been written to...

In the command below, we created a directory called myfolder and download our job output to be stored in that directory.

Fetching results of job '0ed7617d'...
Results for job '0ed7617d' have been written to...

While executing this command, you may encounter warnings regarding receive and send buffer sizes: failed to sufficiently increase receive buffer size. These warnings can arise due to limitations in the UDP buffer used by Bacalhau to process tasks. Additional information can be found in

After the download has finished you should see the following contents in the results directory.

├── exitCode
├── outputs
├── stderr
└── stdout

Step 4 - Viewing your Job Output

cat job-9d20bbad/stdout

That should print out the string Hello World.

Hello world

With that, you have just successfully run a job on Bacalhau! 🐟

Step 5 - Where to go next?

Here are few resources that provide a deeper dive into running jobs with Bacalhau:

How Bacalhau works, Setting up Bacalhau, Examples & Use Cases


If you have questions or need support or guidance, please reach out to the Bacalhau team via Slack (#general channel).