MuleSoft has become a preferred choice for integrating systems and automating business processes due to its lightweight and user-friendly nature, avoiding the complexities often associated with other integration technologies. However, managing the observability of MuleSoft components, especially in distributed environments, can be challenging when relying on varied and bespoke monitoring tools. This article introduces the use of Elastic Stack, particularly Elastic APM, to enhance the monitoring of MuleSoft environments. By integrating the Elastic APM Java Agent with Mule runtime, users can collect runtime transaction performance and metric data, providing a comprehensive view of Mule and non-Mule deployments on a single dashboard. The post details how to set up the Elastic Stack for MuleSoft, including instrumenting Mule projects with Maven and configuring them for both local and CloudHub deployments. The use of Elastic’s machine learning capabilities and advanced visualizations in Kibana further enhances the monitoring experience, offering insights into performance metrics and system health.