AWS Compute Optimizer now supports Aurora I/O-Optimized Recommendations

Starting today, AWS Compute Optimizer delivers new recommendations for your Amazon Aurora DB clusters. Compute Optimizer analyzes the cost of your clusters and identifies opportunities to leverage Aurora I/O-Optimized cluster storage configuration to save cost and improve price predictability for your most I/O-intensive workloads.

Amazon Aurora is a relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. With Aurora, you can choose between two storage configurations: Aurora Standard or Aurora I/O-Optimized. Aurora Standard is a cost-effective option for applications with low to moderate I/O operations. You pay for I/O operations in addition to the instance and storage usage of your DB clusters. With Aurora I/O-Optimized, you pay hourly for your database instances and storage usage, instead of paying per I/O operation. This option can help you save cost for I/O-intensive applications and make it easy to predict your database spend up front.

Introducing Aurora I/O-Optimized recommendations in AWS Compute Optimizer

With these new recommendations in AWS Compute Optimizer, you can quickly identify opportunities to optimize your database cluster storage configurations. Compute Optimizer automatically analyzes the instance, storage, and I/O costs for each of your Aurora Standard clusters. It then compares these costs to the potential cost of using Aurora I/O-Optimized. When Compute Optimizer identifies a cost-saving opportunity, it highlights the cluster as “Not Optimized” with a “DB cluster storage savings available” finding reason. Additionally, Compute Optimizer provides an estimated savings amount and a breakdown of the instance, storage, and I/O costs differences between the two options to help inform your decision.

The default analysis period is over the last 14 days, but you can extend this to the last 32 days for free or up to the last 93 days for a fee by enabling Enhanced Infrastructure Metrics.

Figure 1. Illustrative example of Aurora I/O-Optimized recommendations in AWS Compute Optimizer

Compute Optimizer also helps you understand the estimated cost of switching to Aurora I/O-Optimized, even when your current storage configuration is considered optimized from a cost perspective. Switching to Aurora I/O-Optimized can provide a more predictable monthly cost because you only pay for your provisioned instances and storage usage and don’t have to worry about variable I/O charges. This can result in more predictable cost that helps you simplify planning processes. To help you understand the variability of your I/O usage, Compute Optimizer shows you your Amazon CloudWatch utilization metrics over the lookback period. When you have Enhanced Infrastructure metrics enabled, Compute Optimizer also estimates the monthly I/O variability over the last 93 days.

Figure 2. Illustrative example of an Aurora I/O-Optimized recommendation that helps you understand the cost variability

When you’re ready to switch from Aurora Standard to Aurora I/O-Optimized, you can do so with a single click in the AWS Management Console or with a command through the AWS Command Line Interface. You can switch existing database clusters to I/O-Optimized once every 30 days and switch back to Standard at any time. There is no downtime when you switch to I/O-Optimized storage options for clusters with DB instances that don’t have NVME-based storage.

Your existing Aurora Reserved Instances (RIs) are fully compatible with Aurora I/O-Optimized. Aurora automatically accounts for the price difference between Standard and I/O-Optimized configurations. Note that Aurora DB instances are charged a higher rate with Aurora I/O-Optimized than Aurora Standard, so they consume 30% more normalized units per hour. You can purchase additional RIs to extend your RI discount coverage and realize even more savings.

Getting started in AWS Compute Optimizer

If you have already opted into Compute Optimizer, Aurora I/O-Optimized recommendations are automatically enabled. In the Compute Optimizer console, choose “Aurora and RDS recommendations” from the navigation pane. Then click on the “Storage” tab to see a list of all the recommendations for your Aurora DB clusters storage. For more details, see our user guide “Accessing RDS DB instance recommendations and details”.

New customers who have not opted in Compute Optimizer can enable the service with a few clicks in the Compute Optimizer Console or through the Compute Optimizer API. Once activated, Compute Optimizer needs at least 14 days of cost and usage data before it delivers storage recommendations for an Aurora DB clusters. For more details, see user guide “Getting started with AWS Compute Optimizer”.

All your Amazon Aurora rightsizing recommendations in one place

AWS Cost Optimization Hub is a single dashboard that allows you to easily identify, filter, and consolidate over 15 types of AWS cost optimization recommendations across your AWS accounts and AWS Regions within your organization, so that you can get the most out of your AWS spend. If you have Cost Optimization Hub enabled, you will automatically see these new recommendations for Amazon Aurora DB clusters aggregated across your organization. These Aurora I/O-Optimized recommendations are presented as a new resource type: Aurora DB clusters storage.

Figure 3. Illustrative example of Aurora recommendations in Cost Optimization Hub

In Cost Optimization Hub, you will also find recommendations to identify idle Aurora DB instances. You can consider deleting these instances or converting them to Aurora Serverless v2 with auto-pause to save cost on unused resources. You’ll also find opportunities to migrate to Graviton and purchase Reserved Instances for Amazon Aurora to further help you optimize your fleet.

Conclusions

With these new recommendations in Compute Optimizer, you can quickly identify opportunities to utilize Aurora I/O-Optimized for your Aurora DB cluster storage, so you can save costs and improve price-predictability. In Cost Optimization Hub, you get a clear understanding of the potential savings for your Aurora workloads and can evaluate and prioritize them among all of your other savings opportunities across your organization.