One Click Deployment using CLI

Deploying ZenML on cloud using the CLI

This is an older version of the ZenML documentation. To read and view the latest version please visit this up-to-date URL.

The easiest and fastest way to get running on the cloud is by using the deploy CLI command. It currently only supports deploying to Kubernetes on managed cloud services. You can check the overview page to learn other options that you have.

Before we begin, it will help to understand the architecture around the ZenML server and the database that it uses. Now, depending on your setup, you may find one of the following scenarios relevant.

Option 1: Starting from scratch

If you don't have an existing Kubernetes cluster, you have the following two options to set it up:

• Creating it manually using the documentation for your cloud provider. For convenience, here are links for AWS, Azure and GCP.

• Using a stack recipe that sets up a cluster along with other tools that you might need in your cloud stack like artifact stores, and secret managers. Take a look at all available stack recipes to see if there's something that works for you.

Note Once you have created your cluster, make sure that you configure your kubectl client to talk to it. If you have used stack recipes, this step is already done for you!

You're now ready to deploy ZenML! Run the following command:

zenml deploy

You will be prompted to provide a name for your deployment and details like what cloud provider you want to deploy to, in addition to the username, password and email you want to set for the default user — and that's it! It creates the database and any VPCs, permissions and more that is needed.

Note To be able to run the deploy command, you should have your cloud provider's CLI configured locally with permissions to create resources like MySQL databases and networks.

Reasonable defaults are in place for you already and if you wish to configure more settings, take a look at the next scenario that uses a config file.

Option 2: Using existing cloud resources

Existing Kubernetes Cluster

If you already have an existing cluster without an ingress controller, you can jump straight to the deploy command above to get going with the defaults. Please make sure you have your local kubectl configured to talk to your cluster.

Having an existing NGINX Ingress Controller

The deploy command, by default, tries to create an NGINX ingress controller on your cluster. If you already have an existing controller, you can tell ZenML to not re-deploy it through the use of a config file. This file can be found in the Configuration File Templates towards the end of this guide. It offers a host of configuration options that you can leverage for advanced use cases.

• Check if an ingress controller is running on your cluster by running the following command. You should see an entry in the output with the hostname populated.

  # change the namespace to any other where 
  # you might have the controller installed
  kubectl get svc -n ingress-nginx

• Set create_ingress_controller to false.

• Supply your controller's hostname to the ingress_controller_hostname variable.

  Note If you're on GCP, the ingress host could be an IP address of the form https://xx.xx.xx.xx. Append .nip.io to this address before supplying the value to the ingress_controller_hostname variable. Learn more here.

• You can now run the deploy command and pass the config file above, to it.

  zenml deploy --config=/PATH/TO/FILE

  Note To be able to run the deploy command, you should have your cloud provider's CLI configured locally with permissions to create resources like MySQL databases and networks.

Existing Hosted SQL Database

If you also already have a database that you would want to use with the deployment, you can choose to configure it with the use of the config file. Here we will demonstrate setting the database.

Note Only MySQL version 5.7.x are supported by ZenML, currently.

• Fill the fields below from the config file with values from your database.

  database_username: The username for the database.
  database_password: The password for the database.
  
  database_url: The URL of the database to use for the ZenML server.
  database_ssl_ca: The path to the SSL CA certificate to use for the
      database connection.
  database_ssl_cert: The path to the client SSL certificate to use for the
      database connection.
  database_ssl_key: The path to the client SSL key to use for the
      database connection.
  database_ssl_verify_server_cert: Whether to verify the database server
      SSL certificate.

• Run the deploy command and pass the config file above to it.

  zenml deploy --config=/PATH/TO/FILE

  Note To be able to run the deploy command, you should have your cloud provider's CLI configured locally with permissions to create resources like MySQL databases and networks.

Configuration File Templates

Base Config File

This is the general structure of a config file. Use this as a base and then add any cloud-specific parameters from the sections below.

Note Feel free to include only those variables that you want to customize, in your file. For all other variables, the defaults (specified in square brackets) would be used.

General

name: Name of the server deployment.
provider: The server provider type. # one of aws, gcp or azure
username: The username for the default ZenML server account.
password: The password for the default ZenML server account.

kubectl_config_path: The path to the kubectl config file to use for
    deployment.
namespace [zenmlserver]: The Kubernetes namespace to deploy the ZenML server to.
helm_chart: The path to the ZenML server helm chart to use for
    deployment.
zenmlserver_image_tag [latest]: The tag to use for the ZenML server Docker image.

create_ingress_controller [true]: Whether to deploy an nginx ingress
    controller as part of the deployment.
ingress_tls [true]: Whether to use TLS for the ingress.
ingress_tls_generate_certs [true]: Whether to generate self-signed TLS
    certificates for the ingress.
ingress_tls_secret_name [zenml-tls-certs]: The name of the Kubernetes secret to use for
    the ingress.
ingress_path [""]: The path to use for the ingress.
ingress_controller_hostname: The ingress controller hostname to use for
    the ingress self-signed certificate and to compute the ZenML server
    URL.

database_username [admin]: The username for the database.
database_password: The password for the database.
database_url: The URL of the database to use for the ZenML server.
database_ssl_ca: The path to the SSL CA certificate to use for the
    database connection.
database_ssl_cert: The path to the client SSL certificate to use for the
    database connection.
database_ssl_key: The path to the client SSL key to use for the
    database connection.
database_ssl_verify_server_cert: Whether to verify the database server
    SSL certificate.

log_level [ERROR]: The log level to set the terraform client to. Choose one of
    TRACE, DEBUG, INFO, WARN or ERROR (case insensitive).

Cloud specific settings

AWS

region [eu-west-1]: The AWS region to deploy to.

create_rds [true]: Whether to create an RDS database.
rds_name [zenmlserver]: The name of the RDS instance to create
db_name [zenmlserver]: Name of RDS database to create.
db_type [mysql]: Type of RDS database to create.
db_version [5.7.38]: Version of RDS database to create.
db_instance_class [db.t3.micro]: Instance class of RDS database to create.
db_allocated_storage [5]: Allocated storage of RDS database to create.

The database_username and database_password from the general config is used to set those variables for the AWS RDS instance as well.

GCP

project_id: The project in GCP to deploy the server to.
region [europe-west3]: The GCP region to deploy to.

create_cloudsql [true]: Whether to create an CloudSQL database.
cloudsql_name [zenmlserver]: The name of the CloudSQL instance to create
db_name [zenmlserver]: Name of CloudSQL database to create.
db_instance_tier [db-n1-standard-1]: Instance class of CloudSQL database to create.
db_disk_size [10]: Allocated storage of CloudSQL database, in GB, to create.

• The project_id is required to be set.

• The username for the database is admin irrespective of the value passed to the database_username variable.

• SSL is disabled by default on the database and option to enable it is coming soon!

Azure

Coming Soon!