Amazon OpenSearch Service adds new insights for improved cluster stability

Amazon OpenSearch Service has enhanced Cluster Insights with two new insights — Cluster Overload and Suboptimal Sharding Strategy. Suboptimal Sharding Strategy provides instant visibility into shard imbalances that cause uneven workload distribution, while Cluster Overload surfaces elevated cluster resource utilization that can lead to request throttling or rejections. Both insights come with details of affected resources along with actionable mitigation recommendations. Previously, identifying resource constraints and shard imbalances required manually correlating multiple metrics and logs, making it difficult to detect issues early. With these new insights, you can proactively monitor cluster health and take timely action. Suboptimal Sharding Strategy detects shard imbalances caused by indices with too few shards relative to the number of data nodes, or by shards carrying disproportionately large amounts of data compared to others. It identifies the root cause of uneven workload distribution and provides recommendations to help you achieve optimal shard distribution for improved query performance and resource utilization. Similarly, Cluster Overload helps you identify elevated resource utilization, including CPU, memory, disk I/O, disk throughput, and disk utilization that can potentially lead to request throttling or rejections. It also provides scale-up recommendations so you can take timely action to protect your critical workloads. These new insights are available at no additional cost for OpenSearch version 2.17 or later in all Regions where the OpenSearch UI is available. See the complete list of supported Regions here . To learn more, visit the Cluster Insights documentation or view the complete catalog of available insights .