Deploy W&B Platform on AWS

Hosting W&B Server on AWS.

W&B recommends fully managed deployment options such as W&B Multi-tenant 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.

W&B recommends using the W&B Server AWS Terraform Module to deploy the platform on AWS.

Before you start, W&B recommends that 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 deploys the following mandatory components:

• Load Balancer
• AWS Identity & Access Management (IAM)
• AWS Key Management System (KMS)
• Amazon Aurora MySQL
• Amazon VPC
• Amazon S3
• Amazon Route53
• Amazon Certificate Manager (ACM)
• Amazon Elastic Load Balancing (ALB)
• Amazon Secrets Manager

Other deployment options can also include the following optional components:

• Elastic Cache for Redis
• SQS

Pre-requisite permissions

The account that runs Terraform needs to be able to create all components described in the Introduction and permission to create IAM Policies and IAM Roles and assign roles to resources.

General steps

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

1. Prepare the development environment.

   • Install Terraform
   • W&B recommend creating a Git repository for version control.

2. 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"
   license                    = "xxxxxxxxxxyyyyyyyyyyyzzzzzzz"
   subdomain                  = "wandb-aws"
   domain_name                = "wandb.ml"
   zone_id                    = "xxxxxxxxxxxxxxxx"
   allowed_inbound_cidr       = ["0.0.0.0/0"]
   allowed_inbound_ipv6_cidr  = ["::/0"]
   eks_cluster_version        = "1.29"
   

   Ensure to define variables in your tvfars file before you deploy because the namespace variable is a string that prefixes 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.

   Both allowed_inbound_cidr and allowed_inbound_ipv6_cidr also require setting. In the module, this is a mandatory input. The proceeding example permits access from any source to the W&B installation.

3. Create the file versions.tf

   This file will contain the Terraform and Terraform provider versions required to deploy W&B in AWS

   provider "aws" {
     region = "eu-central-1"
   
     default_tags {
       tags = {
         GithubRepo = "terraform-aws-wandb"
         GithubOrg  = "wandb"
         Enviroment = "Example"
         Example    = "PublicDnsExternal"
       }
     }
   }
   

   Refer to the Terraform Official Documentation to configure the AWS provider.

   Optionally, but highly recommended, add the remote backend configuration mentioned at the beginning of this documentation.

4. Create the file variables.tf

   For every option configured in the terraform.tfvars Terraform requires a correspondent variable declaration.

   variable "namespace" {
     type        = string
     description = "Name prefix used for resources"
   }
   
   variable "domain_name" {
     type        = string
     description = "Domain name used to access instance."
   }
   
   variable "subdomain" {
     type        = string
     default     = null
     description = "Subdomain for accessing the Weights & Biases UI."
   }
   
   variable "license" {
     type = string
   }
   
   variable "zone_id" {
     type        = string
     description = "Domain for creating the Weights & Biases subdomain on."
   }
   
   variable "allowed_inbound_cidr" {
    description = "CIDRs allowed to access wandb-server."
    nullable    = false
    type        = list(string)
   }
   
   variable "allowed_inbound_ipv6_cidr" {
    description = "CIDRs allowed to access wandb-server."
    nullable    = false
    type        = list(string)
   }
   
   variable "eks_cluster_version" {
    description = "EKS cluster kubernetes version"
    nullable    = false
    type        = string
   }
   

Recommended deployment option

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

1. 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:

   module "wandb_infra" {
     source  = "wandb/wandb/aws"
     version = "~>7.0"
   
     namespace   = var.namespace
     domain_name = var.domain_name
     subdomain   = var.subdomain
     zone_id     = var.zone_id
   
     allowed_inbound_cidr           = var.allowed_inbound_cidr
     allowed_inbound_ipv6_cidr      = var.allowed_inbound_ipv6_cidr
   
     public_access                  = true
     external_dns                   = true
     kubernetes_public_access       = true
     kubernetes_public_access_cidrs = ["0.0.0.0/0"]
     eks_cluster_version            = var.eks_cluster_version
   }
   
    data "aws_eks_cluster" "eks_cluster_id" {
      name = module.wandb_infra.cluster_name
    }
   
    data "aws_eks_cluster_auth" "eks_cluster_auth" {
      name = module.wandb_infra.cluster_name
    }
   
    provider "kubernetes" {
      host                   = data.aws_eks_cluster.eks_cluster_id.endpoint
      cluster_ca_certificate = base64decode(data.aws_eks_cluster.eks_cluster_id.certificate_authority.0.data)
      token                  = data.aws_eks_cluster_auth.eks_cluster_auth.token
    }
   
   
    provider "helm" {
      kubernetes {
        host                   = data.aws_eks_cluster.eks_cluster_id.endpoint
        cluster_ca_certificate = base64decode(data.aws_eks_cluster.eks_cluster_id.certificate_authority.0.data)
        token                  = data.aws_eks_cluster_auth.eks_cluster_auth.token
      }
    }
   
    output "url" {
      value = module.wandb_infra.url
    }
   
    output "bucket" {
      value = module.wandb_infra.bucket_name
    }
   

2. Deploy W&B

   To deploy W&B, execute the following commands:

   terraform init
   terraform apply -var-file=terraform.tfvars
   

Enable REDIS

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_elasticache_subnet = true to the same main.tf file described in the Recommended deployment section to enable the cache.

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "~>7.0"

  namespace   = var.namespace
  domain_name = var.domain_name
  subdomain   = var.subdomain
  zone_id     = var.zone_id
	**create_elasticache_subnet = true**
}
[...]

Enable message broker (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 AWS resource that provides the message broker is the SQS, and to enable it, you will need to add the option use_internal_queue = false to the same main.tf described in the Recommended deployment section.

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "~>7.0"

  namespace   = var.namespace
  domain_name = var.domain_name
  subdomain   = var.subdomain
  zone_id     = var.zone_id
  **use_internal_queue = false**

[...]
}

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

Manual configuration

To use an Amazon S3 bucket as a file storage backend for W&B, you will need to:

• Create an Amazon S3 Bucket and Bucket Notifications
• Create SQS Queue
• Grant Permissions to Node Running W&B

you’ll need to create a bucket, along with an SQS queue configured to receive object creation notifications from that bucket. Your instance will need permissions to read from this queue.

Create an S3 Bucket and Bucket Notifications

Follow the procedure bellow to create an Amazon S3 bucket and enable bucket notifications.

1. Navigate to Amazon S3 in the AWS Console.
2. Select Create bucket.
3. Within the Advanced settings, select Add notification within the Events section.
4. Configure all object creation events to be sent to the SQS Queue you configured earlier.

Enable CORS access. Your CORS configuration should look like the following:

<?xml version="1.0" encoding="UTF-8"?>
<CORSConfiguration xmlns="http://s3.amazonaws.com/doc/2006-03-01/">
<CORSRule>
    <AllowedOrigin>http://YOUR-W&B-SERVER-IP</AllowedOrigin>
    <AllowedMethod>GET</AllowedMethod>
    <AllowedMethod>PUT</AllowedMethod>
    <AllowedHeader>*</AllowedHeader>
</CORSRule>
</CORSConfiguration>

Create an SQS Queue

Follow the procedure below to create an SQS Queue:

1. Navigate to Amazon SQS in the AWS Console.
2. Select Create queue.
3. From the Details section, select a Standard queue type.
4. Within the Access policy section, add permission to the following principals:

• SendMessage
• ReceiveMessage
• ChangeMessageVisibility
• DeleteMessage
• GetQueueUrl

Optionally add an advanced access policy in the Access Policy section. For example, the policy for accessing Amazon SQS with a statement is as follows:

{
    "Version" : "2012-10-17",
    "Statement" : [
      {
        "Effect" : "Allow",
        "Principal" : "*",
        "Action" : ["sqs:SendMessage"],
        "Resource" : "<sqs-queue-arn>",
        "Condition" : {
          "ArnEquals" : { "aws:SourceArn" : "<s3-bucket-arn>" }
        }
      }
    ]
}

Grant permissions to node that runs W&B

The node where W&B server is running must be configured to permit access to Amazon S3 and Amazon SQS. Depending on the type of server deployment you have opted for, you may need to add the following policy statements to your node role:

{
   "Statement":[
      {
         "Sid":"",
         "Effect":"Allow",
         "Action":"s3:*",
         "Resource":"arn:aws:s3:::<WANDB_BUCKET>"
      },
      {
         "Sid":"",
         "Effect":"Allow",
         "Action":[
            "sqs:*"
         ],
         "Resource":"arn:aws:sqs:<REGION>:<ACCOUNT>:<WANDB_QUEUE>"
      }
   ]
}

Configure W&B server

Finally, configure your W&B Server.

1. Navigate to the W&B settings page at http(s)://YOUR-W&B-SERVER-HOST/system-admin.
2. Enable the **Use an external file storage backend option
3. Provide information about your Amazon S3 bucket, region, and Amazon SQS queue in the following format:

• File Storage Bucket: s3://<bucket-name>
• File Storage Region (AWS only): <region>
• Notification Subscription: sqs://<queue-name>

4. Select Update settings to apply the new settings.

Upgrade your W&B version

Follow the steps outlined here to update W&B:

1. Add wandb_version to your configuration in your wandb_app module. Provide the version of W&B you want to upgrade to. For example, the following line specifies W&B version 0.48.1:

module "wandb_app" {
    source  = "wandb/wandb/kubernetes"
    version = "~>1.0"

    license       = var.license
    wandb_version = "0.48.1"

Alternatively, you can add the wandb_version to the terraform.tfvars and create a variable with the same name and instead of using the literal value, use the var.wandb_version

2. After you update your configuration, complete the steps described in the Recommended deployment section.

Migrate to operator-based AWS Terraform modules

This section details the steps required to upgrade from pre-operator to post-operator environments using the terraform-aws-wandb module.

The transition to a Kubernetes operator pattern is necessary for the W&B architecture. See the architecture shift explanation for a detailed explanation.

Before and after architecture

Previously, the W&B architecture used:

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "1.16.10"
  ...
}

to control the infrastructure:

and this module to deploy the W&B Server:

module "wandb_app" {
  source  = "wandb/wandb/kubernetes"
  version = "1.12.0"
}

Post-transition, the architecture uses:

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "4.7.2"
  ...
}

to manage both the installation of infrastructure and the W&B Server to the Kubernetes cluster, thus eliminating the need for the module "wandb_app" in post-operator.tf.

This architectural shift enables additional features (like OpenTelemetry, Prometheus, HPAs, Kafka, and image updates) without requiring manual Terraform operations by SRE/Infrastructure teams.

To commence with a base installation of the W&B Pre-Operator, ensure that post-operator.tf has a .disabled file extension and pre-operator.tf is active (that does not have a .disabled extension). Those files can be found here.

Prerequisites

Before initiating the migration process, ensure the following prerequisites are met:

• Egress: The deployment can’t be airgapped. It needs access to deploy.wandb.ai to get the latest spec for the Release Channel.
• AWS Credentials: Proper AWS credentials configured to interact with your AWS resources.
• Terraform Installed: The latest version of Terraform should be installed on your system.
• Route53 Hosted Zone: An existing Route53 hosted zone corresponding to the domain under which the application will be served.
• Pre-Operator Terraform Files: Ensure pre-operator.tf and associated variable files like pre-operator.tfvars are correctly set up.

Pre-Operator set up

Execute the following Terraform commands to initialize and apply the configuration for the Pre-Operator setup:

terraform init -upgrade
terraform apply -var-file=./pre-operator.tfvars

pre-operator.tf should look something like this:

namespace     = "operator-upgrade"
domain_name   = "sandbox-aws.wandb.ml"
zone_id       = "Z032246913CW32RVRY0WU"
subdomain     = "operator-upgrade"
wandb_license = "ey..."
wandb_version = "0.51.2"

The pre-operator.tf configuration calls two modules:

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "1.16.10"
  ...
}

This module spins up the infrastructure.

module "wandb_app" {
  source  = "wandb/wandb/kubernetes"
  version = "1.12.0"
}

This module deploys the application.

Post-Operator Setup

Make sure that pre-operator.tf has a .disabled extension, and post-operator.tf is active.

The post-operator.tfvars includes additional variables:

...
# wandb_version = "0.51.2" is now managed via the Release Channel or set in the User Spec.

# Required Operator Variables for Upgrade:
size                 = "small"
enable_dummy_dns     = true
enable_operator_alb  = true
custom_domain_filter = "sandbox-aws.wandb.ml"

Run the following commands to initialize and apply the Post-Operator configuration:

terraform init -upgrade
terraform apply -var-file=./post-operator.tfvars

The plan and apply steps will update the following resources:

actions:
  create:
    - aws_efs_backup_policy.storage_class
    - aws_efs_file_system.storage_class
    - aws_efs_mount_target.storage_class["0"]
    - aws_efs_mount_target.storage_class["1"]
    - aws_eks_addon.efs
    - aws_iam_openid_connect_provider.eks
    - aws_iam_policy.secrets_manager
    - aws_iam_role_policy_attachment.ebs_csi
    - aws_iam_role_policy_attachment.eks_efs
    - aws_iam_role_policy_attachment.node_secrets_manager
    - aws_security_group.storage_class_nfs
    - aws_security_group_rule.nfs_ingress
    - random_pet.efs
    - aws_s3_bucket_acl.file_storage
    - aws_s3_bucket_cors_configuration.file_storage
    - aws_s3_bucket_ownership_controls.file_storage
    - aws_s3_bucket_server_side_encryption_configuration.file_storage
    - helm_release.operator
    - helm_release.wandb
    - aws_cloudwatch_log_group.this[0]
    - aws_iam_policy.default
    - aws_iam_role.default
    - aws_iam_role_policy_attachment.default
    - helm_release.external_dns
    - aws_default_network_acl.this[0]
    - aws_default_route_table.default[0]
    - aws_iam_policy.default
    - aws_iam_role.default
    - aws_iam_role_policy_attachment.default
    - helm_release.aws_load_balancer_controller

  update_in_place:
    - aws_iam_policy.node_IMDSv2
    - aws_iam_policy.node_cloudwatch
    - aws_iam_policy.node_kms
    - aws_iam_policy.node_s3
    - aws_iam_policy.node_sqs
    - aws_eks_cluster.this[0]
    - aws_elasticache_replication_group.default
    - aws_rds_cluster.this[0]
    - aws_rds_cluster_instance.this["1"]
    - aws_default_security_group.this[0]
    - aws_subnet.private[0]
    - aws_subnet.private[1]
    - aws_subnet.public[0]
    - aws_subnet.public[1]
    - aws_launch_template.workers["primary"]

  destroy:
    - kubernetes_config_map.config_map
    - kubernetes_deployment.wandb
    - kubernetes_priority_class.priority
    - kubernetes_secret.secret
    - kubernetes_service.prometheus
    - kubernetes_service.service
    - random_id.snapshot_identifier[0]

  replace:
    - aws_autoscaling_attachment.autoscaling_attachment["primary"]
    - aws_route53_record.alb
    - aws_eks_node_group.workers["primary"]

You should see something like this:

Note that in post-operator.tf, there is a single:

module "wandb_infra" {
  source  = "wandb/wandb/aws"
  version = "4.7.2"
  ...
}

Changes in the post-operator configuration:

1. Update Required Providers: Change required_providers.aws.version from 3.6 to 4.0 for provider compatibility.
2. DNS and Load Balancer Configuration: Integrate enable_dummy_dns and enable_operator_alb to manage DNS records and AWS Load Balancer setup through an Ingress.
3. License and Size Configuration: Transfer the license and size parameters directly to the wandb_infra module to match new operational requirements.
4. Custom Domain Handling: If necessary, use custom_domain_filter to troubleshoot DNS issues by checking the External DNS pod logs within the kube-system namespace.
5. Helm Provider Configuration: Enable and configure the Helm provider to manage Kubernetes resources effectively:

provider "helm" {
  kubernetes {
    host                   = data.aws_eks_cluster.app_cluster.endpoint
    cluster_ca_certificate = base64decode(data.aws_eks_cluster.app_cluster.certificate_authority[0].data)
    token                  = data.aws_eks_cluster_auth.app_cluster.token
    exec {
      api_version = "client.authentication.k8s.io/v1beta1"
      args        = ["eks", "get-token", "--cluster-name", data.aws_eks_cluster.app_cluster.name]
      command     = "aws"
    }
  }
}

This comprehensive setup ensures a smooth transition from the Pre-Operator to the Post-Operator configuration, leveraging new efficiencies and capabilities enabled by the operator model.