Azure Redis Cache is a powerful, highly available, and scalable solution for caching data in your applications. When it comes to scaling there are mainly two strategies that you can use: vertical scaling (scaling up or down) and horizontal scaling (sharding).
1. Vertical Scaling
This involves changing the tier or pricing model of your Azure Redis Cache instance. In terms of vertical scaling, you can scale up (increase capacity) or scale down (decrease capacity). This type of scaling is suitable when your workload increases or decreases significantly.
In the above PowerShell example, we're logging into Azure and then scaling up the Redis Cache named 'myCache' within the resource group 'myResourceGroup' to a premium P2 size.
2. Horizontal Scaling
Horizontal scaling, also known as sharding, involves adding more cache instances to manage increased load. Azure Redis Cache supports partitioning your data across multiple cache units with a feature called Redis Cluster. Each shard in the cluster holds a subset of your cached data.
To enable clustering, pass the
--cluster-enabled flag when creating or updating your cache:
Remember: Sharding with Redis Cluster involves splitting your data among multiple shards, which can complicate application logic. It might not be the right choice for every situation but can be very effective if properly implemented.
Please check the official Azure Documentation regularly as Azure updates features frequently.