MongoDB has introduced Query Shape Insights, a new feature within MongoDB Atlas designed to offer a comprehensive view of query performance across clusters, specifically targeting resource-intensive query shapes. This feature aggregates data on the most demanding query shapes, facilitating root cause analysis, optimizing workflows, and enhancing operational efficiency. Unlike previous tools focusing on individual queries, Query Shape Insights provides a holistic perspective, ranking the top 100 query shapes by execution time and offering detailed metrics such as operation count, documents examined, and bytes read. This allows for a more efficient identification of performance bottlenecks, particularly in microservices environments. With integration into MongoDB’s existing observability suite, users can quickly transition from detection to resolution, supported by features that include interactive analysis tools, flexible filtering options, and programmatic access through MongoDB’s Admin API. Additionally, the feature adapts based on cluster tier, supporting various workload sizes and enabling trend tracking over a seven-day window. Overall, Query Shape Insights represents a significant advancement in performance monitoring, allowing MongoDB Atlas users to manage, investigate, and respond to performance issues more effectively.