README.md

RL Loop Deployment

This guide provides step-by-step instructions to deploy the RL Loop in Azure.

Prerequisites

Before you begin, ensure you have the following:

• An active Azure subscription (or create one)
• Azure CLI installed
• Bicep CLI installed (can be installed via Azure CLI)
• Docker rl_loop is in the process of releasing to open-source along with an official Docker repository. In the interim, you will need to load an image into your own repository.
  • Install the Docker Engine
  • Create a container registry (eg. Docker Hub or an Azure Container Registry)

Setup

1. Login to Azure:

   az login

2. Install Bicep CLI (if not already installed - Bicep CLI Install Documentation)

   az bicep install

3. Clone the repository:

   git clone https://github.com/VowpalWabbit/rl_loop_deployment.git
   cd rl_loop_deployment/deploy

4. Load the rl_loop image (located here) to a container registry

   Load rl_loop_image.tar to a container registry such as Docker Hub or an Azure Container Registry. The procedure for both is similar.

   Docker Hub

   docker load -i rl_loop_image.tar
   docker tag personalizerstandaloneintegrationtest.azurecr.io/personalizerstandalone:<version-tag> <myname-or-organization>/rl_loop:latest
   docker login
   docker push <myname-or-organization>/rl_loop:latest

   Azure Container Registry

   docker load -i rl_loop_image.tar
   docker tag personalizerstandaloneintegrationtest.azurecr.io/personalizerstandalone:<version-tag> <my-acr>.azurecr.io/rl_loop:latest
   az login
   az acr login --name <my-acr>
   az acr show --name <my-acr> --query loginServer --output table
   docker push <my-acr>.azurecr.io/rl_loop:latest

Deployment Steps

1. Create a Resource Group:

   Create a resource group if needed (exmaple below).

   az group create --name myResourceGroup --location eastus

2. Image Repository Access

   Depending on the image source, there are three options for authenticating with the image repository:

   Credentials via Managed Identity

   Using managed identity by setting the registry object in the container's configuration as follows (see sample.bicepparam):

   // set the mainConfig.registry object in the bicepparam file
   registry: {
       host: 'acrhost.io', // e.g., docker.io, myacr.azurecr.io, etc.
       credentials: {
           type: 'managedIdentity',
           username: 'identity',
           password: null
       }
   }
   

   Credentials via a Key Vault (how to create a Key Vault?)

   Use a Key Vault by setting the registry object for the container's configuration as follows (see sample.biceparam):

   
   // get the secrets from the key vault in the bicepparam file
   param kvImageRegistryUsername = getSecret('mysubscriptionid', 'myresourcegroup', 'keyvaultname', 'imageRegistryUsername')
   param kvImageRegistryPassword = getSecret('mysubscriptionid', 'myresourcegroup', 'keyvaultname', 'imageRegistryPassword')
   
   ...
   
   // set the mainConfig.registry object in the bicepparam file
   registry: {
       host: 'acrhost.io', // e.g., docker.io, myacr.azurecr.io, etc.
       credentials: {
           type: 'keyVault'
       }
   }
   

   Credentials via Username/Password

   Using explicity username and password by setting the registry object in the container's configuration as follows (see sample.biceparam):

   Note: this method is not recommended

   // set the mainConfig.registry object in the bicepparam file
   registry: {
       host: 'acrhost.io', // e.g., docker.io, myacr.azurecr.io, etc.
       credentials: {
           type: 'usernamePassword',
           username: 'myusername',
           password: 'mypassword'
       }
   }
   

3. Deploy the RL Loop using Bicep:

   See the deployment readme for more information on how to customize your deployment.

   az deployment group create --resource-group myResourceGroup --name sample_loop  --rollback-on-error --parameters sample.bicepparam

4. Verify Deployment:

   Check the Azure portal to ensure all resources are deployed correctly.

Post-Deployment

1. Access the Application:

   Navigate to the deployed container application in the resource group. The container for the sample deployment is called sample_loopcg.

2. Monitor and Manage:

   Use Azure Portal to monitor the performance and manage the resources.

3. Use rl_sim to simulate training:

Running rl_sim against your loop

The details building rl_sim are located in project reinforcement_learning.

1. Build reinforcement_learning

2. Setup your rl_sim settings

   ./generate-rl-sim-config.ps1 -appId sample_loop -resourceGroupName myResourceGroup -configFilename rl-sim-config.json

3. Run rl_sim After building reinforcement_learning execute the r_rim_cpp simulator. This file is located in the following path.

   reinforcement_learning/build/binaries/Debug
   or
   reinforcement_learning/build/binaries/Release
   

   rl_sim_cpp.out.exe -j ./rl-sim-config.json

Cleanup

To clean up resources resulting from the provided Bicep scripts, use the az command to remove all resources with the specified deployment tag as follows.

Note: The deployment tag is specified during deployment as an optional parameter (see sample.bicepparam).

az resource list --resource-group rg_test_rl_loop --query "[?tags.deploymentGroupName=='sample_loop'].id" -o tsv | % { az resource delete --ids $_ }

Troubleshooting

• Common Issues:

  • Ensure all prerequisites are met.
  • Verify Azure CLI and Bicep CLI are up to date.
  • Check for any error messages in the deployment output.

• Useful Commands:

  • To view deployment logs:

    az deployment group show --resource-group myResourceGroup --name sample_loop

Additional Resources

• Azure CLI Documentation
• Bicep Documentation