Optimize using Redis Cache

Rubens Max 140 Reputation points
2024-11-20T13:28:24.21+00:00

Im working on a microservices based e commerce platform where Redis Cache is being considered to handle real-time inventory management, user sessions etc The system needs to support high throughput, low latency access to data, and ensure consistency in a highly dynamic environment, especially during peak traffic periods

In a high-traffic, globally distributed application, how should I configure Redis to optimize data access?

Should I use Redis Cluster with automatic sharding, or would Redis Enterprise be more suited to handle the large volume and distribution across regions? How do I choose an effective hashing strategy to minimize cache lookup latency and avoid hotspots in my Redis cluster during rapid inventory updates?

Azure Cache for Redis
Azure Cache for Redis
An Azure service that provides access to a secure, dedicated Redis cache, managed by Microsoft.
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  1. NIKHILA NETHIKUNTA 3,925 Reputation points Microsoft Vendor
    2024-11-20T14:10:57.5566667+00:00

    @Rubens Max
    Thank you for the question and for using Microsoft Q&A platform.

    To optimize data access in a high-traffic, globally distributed application, you can consider using Redis Cluster or Redis Enterprise. Redis Cluster is a good choice if you want to use automatic sharding to distribute data across multiple Redis nodes. Redis Enterprise, on the other hand, is a more advanced solution that provides additional features such as active-active geo-distribution, automatic failover, and more.

    When choosing an effective hashing strategy to minimize cache lookup latency and avoid hotspots in your Redis cluster during rapid inventory updates, you can consider using consistent hashing. Consistent hashing ensures that each key is mapped to a specific Redis node, which helps to minimize the number of cache lookups required to retrieve data. This can help to reduce latency and avoid hotspots in your Redis cluster.

    In addition to consistent hashing, you can also consider using Redis pipelining to reduce the number of round trips required to retrieve data from Redis. Redis pipelining allows you to send multiple commands to Redis in a single request, which can help to reduce latency and improve throughput.

    Finally, you can also consider using Redis Sentinel or Redis Enterprise to provide automatic failover in the event of a node failure. This can help to ensure high availability and prevent data loss in the event of a failure.

    For more information, please refer to the below links:

    https://redis.io/technology/advantages/
    https://redis.io/technology/redis-enterprise-cluster-architecture/

    Hope this helps. Do let us know if you have any further queries.


    If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

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