Azure

info

W&B recommends fully managed deployment options such as W&B SaaS Cloud or W&B Dedicated Cloud deployment types. W&B fully managed services are simple and secure to use, with minimum to no configuration required.

If you've determined to self-managed W&B Server, W&B recommends using the W&B Server Azure Terraform Module to deploy the platform on Azure.

The module documentation is extensive and contains all available options that can be used. We will cover some deployment options in this document.

Before you start, we recommend you choose one of the remote backends available for Terraform to store the State File.

The State File is the necessary resource to roll out upgrades or make changes in your deployment without recreating all components.

The Terraform Module will deploy the following mandatory components:

Azure Resource Group
Azure Virtual Network (VPC)
Azure MySQL Fliexible Server
Azure Storage Account & Blob Storage
Azure Kubernetes Service
Azure Application Gateway

Other deployment options can also include the following optional components:

Azure Cache for Redis
Azure Event Grid

Pre-requisite permissions

The simplest way to get the AzureRM provider configured is via Azure CLI but the incase of automation using Azure Service Principal can also be useful. Regardless the authentication method used, the account that will run the Terraform needs to be able to create all components described in the Introduction.

General steps

The steps on this topic are common for any deployment option covered by this documentation.

Prepare the development environment.

Install Terraform
We recommend creating a Git repository with the code that will be used, but you can keep your files locally.

Create the terraform.tfvars file The tvfars file content can be customized according to the installation type, but the minimum recommended will look like the example below.
```
 namespace     = "wandb"
 wandb_license = "xxxxxxxxxxyyyyyyyyyyyzzzzzzz"
 subdomain     = "wandb-aws"
 domain_name   = "wandb.ml"
 location      = "westeurope"
```
The variables defined here need to be decided before the deployment because. The namespace variable will be a string that will prefix all resources created by Terraform.
The combination of subdomain and domain will form the FQDN that W&B will be configured. In the example above, the W&B FQDN will be wandb-aws.wandb.ml and the DNS zone_id where the FQDN record will be created.
Create the file versions.tf This file will contain the Terraform and Terraform provider versions required to deploy W&B in AWS
```
terraform {
  required_version = "~> 1.3"

  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.17"
    }
  }
}
```
Refer to the Terraform Official Documentation to configure the AWS provider.
Optionally, but highly recommended, you can add the remote backend configuration mentioned at the beginning of this documentation.

Create the file variables.tf. For every option configured in the terraform.tfvars Terraform requires a correspondent variable declaration.

 variable "namespace" {
   type        = string
   description = "String used for prefix resources."
 }

 variable "location" {
   type        = string
   description = "Azure Resource Group location"
 }

 variable "domain_name" {
   type        = string
   description = "Domain for accessing the Weights & Biases UI."
 }

 variable "subdomain" {
   type        = string
   default     = null
   description = "Subdomain for accessing the Weights & Biases UI. Default creates record at Route53 Route."
 }

 variable "license" {
   type        = string
   description = "Your wandb/local license"
 }

Deployment - Recommended (~20 mins)

This is the most straightforward deployment option configuration that will create all Mandatory components and install in the Kubernetes Cluster the latest version of W&B.

Create the main.tf In the same directory where you created the files in the General Steps, create a file main.tf with the following content:

provider "azurerm" {
  features {}
}

provider "kubernetes" {
  host                   = module.wandb.cluster_host
  cluster_ca_certificate = base64decode(module.wandb.cluster_ca_certificate)
  client_key             = base64decode(module.wandb.cluster_client_key)
  client_certificate     = base64decode(module.wandb.cluster_client_certificate)
}

provider "helm" {
  kubernetes {
    host                   = module.wandb.cluster_host
    cluster_ca_certificate = base64decode(module.wandb.cluster_ca_certificate)
    client_key             = base64decode(module.wandb.cluster_client_key)
    client_certificate     = base64decode(module.wandb.cluster_client_certificate)
  }
}

# Spin up all required services
module "wandb" {
  source  = "wandb/wandb/azurerm"
  version = "~> 1.2"

  namespace   = var.namespace
  location    = var.location
  license     = var.license
  domain_name = var.domain_name
  subdomain   = var.subdomain

  deletion_protection = false

  tags = {
    "Example" : "PublicDns"
  }
}

output "address" {
  value = module.wandb.address
}

output "url" {
  value = module.wandb.url
}

Deploy to W&B To deploy W&B, execute the following commands:
```
terraform init
terraform apply -var-file=terraform.tfvars
```

Deployment with REDIS Cache

Another deployment option uses Redis to cache the SQL queries and speed up the application response when loading the metrics for the experiments.

You need to add the option create_redis = true to the same main.tf file we worked on in Deployment Recommended to enable the cache.

# Spin up all required services
module "wandb" {
  source  = "wandb/wandb/azurerm"
  version = "~> 1.2"


  namespace   = var.namespace
  location    = var.location
  license     = var.license
  domain_name = var.domain_name
  subdomain   = var.subdomain

  create_redis       = true # Create Redis
  [...]

Deployment with External Queue

Deployment option 3 consists of enabling the external message broker. This is optional because the W&B brings embedded a broker. This option doesn't bring a performance improvement.

The Azure resource that provides the message broker is the Azure Event Grid, and to enable it, you will need to add the option use_internal_queue = false to the same main.tf that we worked on the Deployment Recommended

# Spin up all required services
module "wandb" {
  source  = "wandb/wandb/azurerm"
  version = "~> 1.2"


  namespace   = var.namespace
  location    = var.location
  license     = var.license
  domain_name = var.domain_name
  subdomain   = var.subdomain

  use_internal_queue       = false # Enable Azure Event Grid
  [...]
}

Other deployment options

You can combine all three deployment options adding all configurations to the same file. The Terraform Module provides several options that can be combined along with the standard options and the minimal configuration found in Deployment Recommended

Pre-requisite permissions​

General steps​

Deployment - Recommended (~20 mins)​

Deployment with REDIS Cache​

Deployment with External Queue​

Other deployment options​