Using Google Memorystore for Redis with DataRobot¶

Introduction¶

DataRobot supports the integration of external caching solutions, including Google Memorystore for Redis, to optimize performance and enhance data retrieval. This documentation provides step-by-step instructions on configuring DataRobot to utilize Google Memorystore for Redis as a caching layer.

Steps to Configure Google Memorystore for Redis with DataRobot¶

1. Create a Google Memorystore for Redis Instance¶

• Log in to the Google Cloud Console.
• Navigate to the Memorystore section.
• Click "Create instance" and select "Memorystore for Redis."
• Choose an appropriate Capacity based on our requirements.
• Set the Engine Version to 7.0
• on Set up connection Choose the network where to place your Redis instance
• Follow the on-screen instructions to configure your Memorystore for Redis instance, specifying details such as instance ID, region, and other settings.

2. Disable In-Transit Encryption¶

• Scroll down to the "Security" section.
• Uncheck the option for "In-transit encryption" to disable encryption for data in transit.

  Note: "In-transit encryption" required a dedicated CA that is not fully supported

3. Obtain Memorystore for Redis Connection Details¶

• Once the Memorystore for Redis instance is created, note down the Instance connection string. You'll need this for configuring DataRobot.

4. Configure DataRobot to Use Google Memorystore for Redis¶

When Redis is configured to utilize an external service, additional YAML override values must be provided..

global:
  redis:
    internal: false
    hostname: "YOUR_GCP_REDIS_DNS"
    port: "YOUR_GCP_REDIS_PORT"
    sentinel:
      enabled: false
    auth:
      password: YOUR_GCP_REDIS_PASSWORD

core:
  config_env_vars:
    REDISPROXY_PORT: YOUR_GCP_REDIS_PORT

buzok-onprem:
  buzok-worker:
    services:
      redis:
        tls: false
        cluster: false
        useSentinel: false
        host: YOUR_GCP_REDIS_DNS
        port: YOUR_GCP_REDIS_PORT # GCP Redis default port is 6378

Google Cloud Memorystore snapshots¶

Google Cloud Memorystore for Redis offers backup and restore capabilities to protect your cache data. You can configure automatic backups and perform manual backups to ensure data durability and recovery options in case of failures. Refer to the Google Cloud documentation for more information on backup options and best practices.

Conclusion¶

By following these steps, you can seamlessly integrate Google Memorystore for Redis with DataRobot, providing an efficient caching layer to enhance performance. This setup improves data retrieval and overall system responsiveness. If issues arise, refer to DataRobot documentation and Google Memorystore for Redis documentation for troubleshooting guidance.

Note: Always ensure that you follow best practices for security and compliance when configuring external caching solutions with DataRobot.