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Deploy lakeFS on GCP

⏰ Expected deployment time: 25 min

Create a Database

lakeFS requires a PostgreSQL database to synchronize actions on your repositories. We will show you how to create a database on Google Cloud SQL, but you can use any PostgreSQL database as long as it’s accessible by your lakeFS installation.

If you already have a database, take note of the connection string and skip to the next step

  1. Follow the official Google documentation on how to create a PostgreSQL instance. Make sure you’re using PostgreSQL version >= 11.
  2. On the Users tab in the console, create a user. The lakeFS installation will use it to connect to your database.
  3. Choose the method by which lakeFS will connect to your database. Google recommends using the SQL Auth Proxy.

Run the lakeFS Server

  1. Save the following configuration file as config.yaml:

      type: "postgres"
        connection_string: "[DATABASE_CONNECTION_STRING]"
        # replace this with a randomly-generated string:
        secret_key: "[ENCRYPTION_SECRET_KEY]"
      type: gs
       # Uncomment the following lines to give lakeFS access to your buckets using a service account:
       # gs:
       #   credentials_json: [YOUR SERVICE ACCOUNT JSON STRING]
  2. Download the binary to the GCE instance.
  3. Run the lakefs binary on the GCE machine:
    lakefs --config config.yaml run

    Note: it is preferable to run the binary as a service using systemd or your operating system’s facilities.

To support container-based environments like Google Cloud Run, lakeFS can be configured using environment variables. Here is a docker run command to demonstrate starting lakeFS using Docker:

docker run \
  --name lakefs \
  -p 8000:8000 \
  -e LAKEFS_DATABASE_TYPE="postgres" \
  treeverse/lakefs:latest run

See the reference for a complete list of environment variables.

You can install lakeFS on Kubernetes using a Helm chart.

To install lakeFS with Helm:

  1. Copy the Helm values file relevant for Google Storage:

        # replace DATABASE_CONNECTION_STRING with the connection string of the database you created in a previous step.
        # e.g.: postgres://postgres:myPassword@localhost/postgres:5432
        databaseConnectionString: [DATABASE_CONNECTION_STRING]
        # replace this with a randomly-generated string
        authEncryptSecretKey: [ENCRYPTION_SECRET_KEY]
    lakefsConfig: |
          type: gs
          # Uncomment the following lines to give lakeFS access to your buckets using a service account:
          # gs:
          #   credentials_json: [YOUR SERVICE ACCOUNT JSON STRING]
  2. Fill in the missing values and save the file as conf-values.yaml. For more configuration options, see our Helm chart README.

    The lakefsConfig parameter is the lakeFS configuration documented here but without sensitive information. Sensitive information like databaseConnectionString is given through separate parameters, and the chart will inject it into Kubernetes secrets.

  3. In the directory where you created conf-values.yaml, run the following commands:

    # Add the lakeFS repository
    helm repo add lakefs
    # Deploy lakeFS
    helm install my-lakefs lakefs/lakefs -f conf-values.yaml

    my-lakefs is the Helm Release name.

Load balancing

To configure a load balancer to direct requests to the lakeFS servers you can use the LoadBalancer Service type or a Kubernetes Ingress. By default, lakeFS operates on port 8000 and exposes a /_health endpoint that you can use for health checks.

💡 The NGINX Ingress Controller by default limits the client body size to 1 MiB. Some clients use bigger chunks to upload objects - for example, multipart upload to lakeFS using the S3-compatible Gateway or a simple PUT request using the OpenAPI Server. Checkout Nginx documentation for increasing the limit, or an example of Nginx configuration with MinIO.

Create the admin user

When you first open the lakeFS UI, you will be asked to create an initial admin user.

  1. open http://<lakefs-host>/ in your browser. If you haven’t set up a load balancer, this will likely be http://<instance ip address>:8000/
  2. On first use, you’ll be redirected to the setup page:

    Create user

  3. Follow the steps to create an initial administrator user. Save the credentials you’ve received somewhere safe, you won’t be able to see them again!

    Setup Done

  4. Follow the link and go to the login screen. Use the credentials from the previous step to log in.

Create your first repository

  1. Use the credentials from the previous step to log in
  2. Click Create Repository and choose Blank Repository.

    Create Repo

  3. Under Storage Namespace, enter a path to your desired location on the object store. This is where data written to this repository will be stored.
  4. Click Create Repository
  5. You should now have a configured repository, ready to use!

    Repo Created

Congratulations! Your environment is now ready 🤩