Cloud Cost Management
2
mins read
Implement ElastiCache Cost-Cutting Measures
.png)
Amazon ElastiCache pricing is based on multiple factors such as number of nodes, region, instance type, cache engine used (Redis or Memcached), data transfer, and whether data tiering is enabled or not for clusters. With ElastiCache, you pay only for what you use with no minimum fee. ElastiCache supports both on-demand nodes, where you can pay by the hour, and reserved nodes, which offers significant discounts for customers who commit to longer time periods.
Right-sizing ElastiCache instances involves understanding your application's usage patterns and selecting the appropriate instance type accordingly. Monitoring metrics such as CPU utilization, memory usage, and network bandwidth can help understand your resource consumption. Using AWS CloudWatch to track usage patterns of such metrics and identify periods of high or low usage can give an estimate of the instance type and Memory size to be used and ensure your Elastic Cache resources are right-sized and cost is optimized.
Reserved Instances (RIs) offer significant cost savings in exchange for time-bound commitment. Using RIs can result in savings of up to 55% compared to on-demand pricing. By reserving instances for a specific term (1 year or 3 years), you can commit to using ElastiCache and enjoy discounted rates. RIs are ideal for predictable workloads where resource requirements are known in advance. Using AWS Cost Explorer will help in estimating savings by analyzing past usage and finalize cost-effective RI (Reserved Instance) types to be created.
Auto scaling adjusts ElastiCache resources based on demand by automatically adding or removing shards or read replicas in response to changes in application workload, ensuring optimal performance at the lowest possible cost. You can define and apply an auto scaling policy using Amazon CloudWatch metrics and assign target values. By analyzing your workload patterns using metrics such as CPU utilization and memory usage, you can implement effective auto scaling policies and optimize costs.
Data tiering optimizes storage costs by utilizing low-cost solid-state drives (SSDs) in addition to memory. ElastiCache for Redis supports data tiering which automatically moves the lesser accessed items from memory to locally attached SSDs when available memory capacity is fully consumed.
Data tiering in ElastiCache for Redis offers a low-cost way to scale your clusters up to one petabyte total capacity. By storing frequently accessed data in memory and less frequently accessed data on SSDs, you can achieve significant cost savings while maintaining performance. Data tiering is available, starting from Redis version 6.2 on Graviton-based R6gd nodes (Memory + SSD). With nearly five times more total capacity, these nodes can help achieve over 60% savings when running at maximum utilization compared to normal R6g nodes (memory only).
Upgrading to Redis 7 can save money on ElastiCache costs by improving performance, reducing memory usage, and optimizing storage. For example, Redis 7 is up to 72% faster than Redis 6.2 and can handle up to 10 times more concurrent connections. By upgrading to Redis 7 and taking advantage of enhanced I/O multiplexing, you can optimize resource utilization, reduce the overall footprint of your cluster, and potentially save costs. The table below summarizes indicative cost savings with Redis 7. Do note that actual savings will vary based on your workload.
Achieving cost efficiency with AWS ElastiCache requires a comprehensive strategy. By understanding ElastiCache pricing and adopting practices such as rightsizing instances, utilizing reserved instances, implementing autoscaling, and leveraging data tiering, businesses can align resource allocation with actual demand. In addition, upgrading to ElastiCache for Redis 7 enhances performance while potentially reducing costs. These measures can empower organizations to strike a balance between optimal performance and prudent spending, ensuring the effectiveness of their AWS ElastiCache infrastructure.
.png)
.png)
