Simple Log Service:Collect monitoring data from JVMs

Background information

If an issue related to Java application performance occurs, you can analyze JVM GC logs to troubleshoot the issue. GC logs provide information about garbage collections, including the cause of GC triggers, GC type, GC , and the number of objects that are collected. You can identify and handle the following common issues by analyzing GC logs:

1. Memory leaks: You can obtain the creation and destruction process of objects and the allocation of objects in the heap memory by analyzing GC logs. If specific objects are not released after you use the objects, memory leaks may occur. You can check whether memory leaks occur, identify the cause of the memory leaks, and fix the issue at the earliest opportunity by analyzing GC logs.

2. High memory usage: GC logs show the memory usage of your application, including the heap memory usage and object distribution. You can optimize memory usage based on the objects that occupy a large volume of memory space by analyzing GC logs.

3. GC performance-related issues: GC logs provide information about garbage collections, including the cause of GC triggers, GC frequency, and GC duration. You can obtain the performance information about garbage collections, such as the GC frequency and GC duration, by analyzing GC logs. If the GC frequency is high or the GC duration is long, the performance of your application may be affected. You can also identify the causes of issues that are related to GC performance and use GC logs to fix the issues.

4. GC policy selection: JVMs provide multiple GC algorithms, such as Mark-Sweep, Copying, Mark-Compact. Analysis of GC logs allows you to evaluate the performance of each GC algorithm and select the appropriate GC policy. This helps improve the stability of your application.

Data flow

The following figure shows the data flow of GC logs.

Procedure

1. Log on to the Simple Log Service console.

2. In the Log Application section, click the Intelligent O&M tab. Then, click Full-stack Observability.

3. On the Simple Log Service Full-stack Observability page, click the instance that you want to manage.

4. In the left-side navigation pane, click Full-stack Monitoring.

   The first time you use Full-stack Monitoring in the instance, click Enable.

5. In the left-side navigation pane, click Data Import. On the Data Import Configurations page, find GC Log Analysis in the JVM Monitoring section.

   The first time you create a Logtail configuration for host monitoring data, turn on the switch to go to the configuration page. If you created a Logtail configuration, click the icon to go to the configuration page.

6. Create and select a machine group.

   • If a machine group is available, click Use Existing Machine Groups.

   • If no machine groups are available, perform the following steps to create a machine group. In this example, an Elastic Compute Service (ECS) instance is used.

     1. On the ECS Instances tab, select Manually Select Instances. Then, select the ECS instance that you want to use and click Create.

        For more information, see Install Logtail on ECS instances.

        Important

        If your server is an ECS instance that belongs to another Alibaba Cloud account, a server that is provided by a third-party cloud service provider, or a server that is deployed in a self-managed data center, you must install Linux Logtail V0.16.40 or later on the server. For more information, see Install Logtail on a Linux server. After you install Logtail, you must configure a user identifier for the server. For more information, see Configure a user identifier.

     2. After Logtail is installed, click Complete Installation.

     3. In the Create Machine Group step, configure the Name parameter and click Next.

        Simple Log Service allows you to create IP address-based machine groups and custom identifier-based machine groups. For more information, see Create an IP address-based machine group and Create a custom identifier-based machine group.

7. In the Specify Data Source step, configure the parameters and click Complete.

   The following table describes the parameters. Retain the default settings for the other parameters.

   Parameter	Description	Example
   Config Name	The name of the Logtail configuration.	host-szytbsxv
   Log Path	The path of GC log files.	/app/sls-mall/*.gc*
   Docker File	If the Java process runs in a Docker container or a Kubernetes cluster, you must select Docker File.	Yes
   Deployed in K8s	If the Java process is deployed in a Kubernetes cluster, select Deployed in K8s.	Yes
   Mode	The log file collection mode. Select Simple Mode.	Simple Mode
   Topic Generation Mode	If you deploy multiple Java processes in the same host or container, you can use topics to identify the GC logs of each Java process. We recommend that you select File Path RegEx to generate topics. If you select this method, you must add the %p parameter to the name of the JVM GC file to record Java process IDs. Example: -Xloggc:gc-%p.log. After you configure the setting, the system adds the pid suffix to each GC file name. Example:gc-pid1.log.0.current.	File Path RegEx
   Custom Regular Expression	The regular expression that is used to generate topics. For more information, see Log topics. By default, Full-stack Observability performs association analysis based on the pid field. We recommend that you set the named capturing group in the regular expression to (?P<pid>).	/sls-mall/gc-pid(?P<pid>\d*).log.*

   After you configure the settings, Simple Log Service automatically creates assets such as Metricstores. For more information, see Assets.