![]() About three times the amount of ad hoc storage was required on a frequent basis, to onboard large tables to the cluster, and it became difficult to add these tables with only 8 DC2 nodes. Inability to add more storage without resizing the cluster – Because each dc2.8xlarge node had a fixed storage unit capacity, the only way to add additional storage was by resizing the cluster.A healthy Amazon Redshift cluster must not have more than 80% of storage utilization, but this threshold had been crossed. This caused high disk usage per node whenever disk-intensive queries were run (and these queries were already optimized). High disk usage and high storage utilization – The storage utilization of the Amazon Redshift cluster crossed 90% because each dc2.8xlarge node had less SSD space (2.56 TB).In addition to the pain of purchasing extra compute, the team faced some challenges: This led to an increase in the operating costs for supporting mission-critical applications. As a result, more compute was purchased whenever additional storage was required. The previous generation of Amazon Redshift instances didn’t allow you to scale compute and storage resources separately because compute and storage were tightly coupled in a node. ![]() However, Customer Service has been using dense-compute nodes over dense-storage nodes to support real-time analytical dashboards that require high-speed retrievals using NVMe-based SSDs offered exclusively by the dense-compute nodes. In fact, Customer Service’s storage capacity needs have grown faster than computing power needs. General challengesĪs the Amazon Customer Service data warehouse continues to grow in volume, additional storage is required to store the new information. The new nodes enabled the team to plan and scale storage resources flexibly without having to purchase additional compute, and they can continuously innovate with the highest standards for their customers. Upgrading to 3 RA3 nodes allowed the team to not only save up to 55% on Amazon Redshift operating costs per year, but also improve the load times of most dashboards up to 47% and the data retrieval performance of most queries up to 25%. The team operated 8 DC2 nodes, but they required 6 nodes of computing power and 10–12 nodes of storage unit capacity. The RA project was a major strategic move for the Amazon Customer Service Technology team. Moving to the most advanced Amazon Redshift architecture enabled the team to reduce its infrastructure costs, improve the performance of queries, optimize its compute and storage capacity planning processes, and accelerate the performance of analytical dashboards for making business-critical decisions. In 2021, the Amazon Customer Service Technology team upgraded its dense-compute nodes (dc2.8xlarge) to the Amazon Redshift RA3 instance family (ra3.16xlarge). Amazon Customer Service solves exciting and challenging customer care problems for, the world’s largest online retailer.
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