Enterprise Distributed Application Service (EDAS) integrates with Application Real-Time Monitoring Service (ARMS) so that you can monitor key performance metrics and manage alerts for your applications that are deployed to EDAS.

Application monitoring

EDAS integrates with ARMS so that you can monitor key performance metrics for your applications that are deployed to EDAS. This helps you locate interfaces that have errors and slowly respond and make the called parameters reoccur. Therefore, the efficiency of problem diagnostics in the production environment is significantly improved.

Monitoring granularity Feature description Documentation
Application Overview On the Application Overview page, you can view Kubernetes cluster information, such as the region, namespace, running status, and application diagnosis reports. You can also view key metrics for the health status of the application. The metrics include overall metrics, such as Total Requests and Average Response Time, metrics of Application Support Services and Application Dependent Services, and system information, such as CPU and MEM. View application overview
Prometheus The preset monitoring dashboards that are provided by the Prometheus monitoring feature show the basic information, CPU metrics, memory metrics, and network metrics of pods. In these dashboards, you can view the Prometheus monitoring metrics, and change the properties of dashboard data as needed, such as time intervals and refresh rate. View Prometheus monitoring metrics
Instance Details EDAS provides various application monitoring metrics:
  • The Java Virtual Machine (JVM) monitoring feature is used to monitor important JVM metrics, such as heap memory, non-heap memory, direct buffer, memory-mapped buffer, garbage collection (GC) details, and the number of JVM threads.
  • JVM monitoring can intuitively display multiple memory metrics within a specified period of time. However, although the charts can reflect excessive memory usage, specific information cannot be displayed. Therefore, the charts cannot help you troubleshoot problems. In this case, you can create a memory snapshot and view detailed memory usage by using logs.
  • The host monitoring feature is used to monitor the metrics of the CPUs, memory, disks, load, network traffic, and network packets.
Service Details It is used to monitor the details of interface calls of an application, including SQL analysis, NoSQL analysis, exception analysis, error analysis, upstream and downstream services, and interface snapshots. Service and interface monitoring
Application Diagnosis - Real-time Diagnosis It is suitable for scenarios where you closely monitor application performance and identify the causes of problems in a short period of time. Real-time diagnosis
Application Diagnosis - Exceptions Diagnosis EDAS provides the application exception analysis feature. This feature collects statistics on the number of exceptions, the number of exceptions of each type, and the ports where exceptions occur. Exception analysis
Application Diagnosis - Threads Profiling It provides statistics on the CPU time consumption at the thread level and the number of threads of each type. The method stacks of threads are recorded and aggregated every 5 minutes. This helps you review the code execution process and locate thread issues. Thread profiling
Advanced Monitor ARMS can be accessed within a few clicks. This enables applications that are running in EDAS to be more effectively monitored. Advanced monitoring


You can customize alert rules for specific monitoring objects. If a rule is triggered, the system sends alert messages to the specified contact group by using the notification method that you specify. This way, the contacts can resolve issues at the earliest opportunity.