Question: How can I scale down an Azure Redis instance?


Scaling down an Azure Redis Cache involves reducing the size of the cache. This is a bit tricky because Azure Redis Cache does not support direct scaling down.

If you need to scale down your Azure Redis Cache, it should be done indirectly by creating a new smaller instance and migrating the data from the current larger instance to the new one. Here are the steps:

  1. Create a new Azure Redis Cache instance that is smaller than your current instance.

    You can use the Azure portal, Azure CLI, or Azure Powershell to do this. Here's an example of how to do this using Azure CLI. Replace <your-resource-group>, <your-cache-name>, and <your-location> with your actual values:

    az redis create --name <your-cache-name> --resource-group <your-resource-group> --location <your-location> --sku Basic --vm-size C0
  2. Export the data from your current (larger) Azure Redis Cache instance.

    Redis provides a bgsave command to create a snapshot of your database. However, since you cannot directly access the file system of Azure Redis Cache service, you might have to use RDB tools to parse Redis dump.rdb files.

  3. Import the data into your new (smaller) Azure Redis Cache instance.

    After exporting data from the old instance, you can import it to the new one using different methods such as using SYNC command or various data migration tools.

  4. Update your application's configuration to point to the new smaller Azure Redis Cache instance.

  5. Test your application to make sure it works correctly with the new smaller Azure Redis Cache instance.

  6. Once everything is working correctly, delete the old larger Azure Redis Cache instance to stop incurring charges for it.

Remember, there's some risk involved with this process as it involves data migration. Always ensure you have a backup of your data before starting the operation, and thoroughly test your application afterwards to prevent any loss of functionality or data.

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Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.