Application Real-Time Monitoring Service:Use the code diagnostics feature to diagnose slow traces

Enable the code diagnostics feature

1. Log on to the ARMS console. In the left-side navigation pane, choose Application Monitoring > Application List.

2. On the Application List page, select a region in the top navigation bar and click the name of the application that you want to manage.

   Note

   If the icon is displayed in the Language column, the application is connected to Application Monitoring. If a hyphen (-) is displayed, the application is connected to Managed Service for OpenTelemetry.

3. In the left-side navigation pane, click Application Settings. On the page that appears, click the Custom Configuration tab.

4. In the Continuous profiling section, turn on Main switch and Code hotspot, and then configure the IP address of an application instance or the CIDR blocks of multiple instances.

   Important

   In an ARMS agent V4.2.x or later, this feature is enabled by default. In an ARMS agent of an earlier version, this feature displays enabled in the console for applications that are not configured with it, but will take effect only after you click Save.

5. In the lower part of the tab, click Save.

   The modification takes effect without the need to restart the application.

View hotspot code data on the Interface Invocation page

Example: Parse and traverse JSON data and call downstream HTTP interfaces.

public class HotSpotAction extends AbsAction {

  private RestTemplate restTemplate = new RestTemplate();
  
  // The request method.
  @Override
  public void runBusiness() {
    readFile();
    invokeAPI();
  }

  // Execute an HTTP call.
  private void invokeAPI() {
    String url = "https://httpbin.org/get";
    String response = restTemplate.getForObject(url, String.class);
  }

   // Read and parse the file data.
  private double readFile() {
    InputStreamReader reader = new InputStreamReader(
        ClassLoader.getSystemResourceAsStream("data/xxx.json"));
    LinkedList<Movie> movieList = GSON.fromJson(reader, new TypeToken<LinkedList<Movie>>() {
    }.getType());
    double totalCount = 0;
    for (int i = 0; i < movieList.size(); i++) {
      totalCount += movieList.get(i).rating();
    }
    return totalCount;
  }
}

1. Log on to the ARMS console. In the left-side navigation pane, choose Application Monitoring > Application List.

2. On the Application List page, select a region in the top navigation bar and click the name of the application that you want to manage.

   Note

   If the icon is displayed in the Language column, the application is connected to Application Monitoring. If a hyphen (-) is displayed, the application is connected to Managed Service for OpenTelemetry.

3. In the left-side navigation pane, click Interface Invocation. On the page that appears, select an interface and click the Interface Snapshot tab.

4. On the Interface Snapshot tab, click a trace ID.

5. Click the Magnifier icon in the Details column and then click the Code Hotspot tab.

   

   The left side of the figure shows the time consumed for all methods involved, and the right side shows the flame graph of all method stack information of each method.

   • The Self column displays the time or resources that each method consumes within the stack, excluding the time or resources that their child methods consume. The data can be used to identify methods that spend excessive time or resources for their own.

   • The Total column displays the time or resources consumed for each method itself, including the time or resources consumed for all of its child methods. The data can be used to identify methods that contribute the most time or resources.

   When you analyze code logic, you can locate the time-consuming methods by focusing on the Self column or the wide flame at the bottom of the right-side flame graph. Generally, wide flame indicates a system performance bottleneck. The java.lang.Thread.sleep() method in the preceding figure consumes much time because of system performance bottlenecks.

   Based on the preceding figure, perform the following analysis.

   1. Arrange the values in the Self column in ascending order. Find and click the method java.util.LinkedList.node(int) with the largest value. The relevant methods are shown in the flame graph.

      

   2. You can find that the java.util.LinkedList.node(int) method has the widest box at the stack top of the flame graph.

   3. Because the java.util.LinkedList.node(int) method is a library function of Java Development Kit (JDK), you need to search up further, and you can find the java.util.LinkedList.get(int) method and its parent method com.alibaba.cloud.pressure.memory.HotSpotAction.readFile(). As the first service method defined by the application, the com.alibaba.cloud.pressure.memory.HotSpotAction.readFile() method consumes 3.75 seconds, accounting for 69.88% of the stack. Therefore, a conclusion can be drawn that the com.alibaba.cloud.pressure.memory.HotSpotAction.readFile() method consumes a large amount of resources in the specified time period. You can use the method to analyze the logic of relevant methods and check whether they can be optimized.