Developers take advantage of the JVM argument -XX:+UseGCLogFileRotation to rotate GC log files.
Example:
Try to Avoid -XX:+UseGCLogFileRotation
Best Practices for Efficient Log Management and Monitoring
When managing cloud-native applications, it's essential to have end-to-end visibility into what's happening at any given time. This is especially true because of the distributed and dynamic nature of cloud-native apps, which are often deployed using ephemeral technologies like containers and serverless functions.
With so much flux and complexity across a cloud-native system, it's important to have robust monitoring and logging in place to control and manage the inevitable chaos. This post discusses what we consider to be some of the best practices and standards to follow when logging and monitoring cloud-native applications.
Spring Sweets: Group Loggers With Logical Name [Snippet]
Spring Boot 2.1 introduced log groups. A log group is a logical name for one or more loggers. We can define log groups in our application configuration. Then, we can set the log level for a group, so all loggers in the group will get the same log level. This can be very useful to change a log level for multiple loggers that belong together with one setting. Spring Boot already provides two log groups by default: web and sql. In the following list, we see which loggers are part of the default log groups:
- web:
org.springframework.core.codec,org.springframework.http,org.springframework.web,org.springframework.boot.actuate.endpoint.web,org.springframework.boot.web.servlet.ServletContextInitializerBeans - sql:
org.springframework.jdbc.core,org.hibernate.SQL
To define our own log group, we must add in our application configuration the key logging.group. followed by our log group name. Next, we assign all loggers that we want to be part of the group. Once we have defined our group, we can set the log level using the group name prefixed with the configuration key logging.level..
The Challenge of Log Management in Modern IT Environments
Gaining visibility into modern IT environments is a challenge that an increasing number of organizations are finding difficult to overcome.
Yes — the advent of cloud computing and virtually “unlimited” storage has made it much easier to solve some of the traditional challenges involved in gaining visibility. However, architecture has evolved into microservices, containers, and scheduling infrastructure. Software stacks and the hardware supporting them are becoming more complex, creating additional and different challenges. These changes have directly impacted the complexity of logging and it takes a very specific set of tools and strategies to be able to solve this visibility challenge.