In the world of software development, visibility into your application’s performance is paramount. Enter Automon – a powerful Java library that aids developers in monitoring and tracing their code with ease. In this blog, we’ll explore what Automon is, its key features, and how you can get started with it. Let’s dive in!

What is Automon?

Automon is a Java library that integrates seamlessly with AspectJ to facilitate the monitoring and tracing of your Java applications without invasive code changes. Version 1.0 focused on monitoring, while version 2.0 introduced tracing capabilities. Think of it as using a telescope to study the stars—instead of modifying the stars themselves, you’re just getting a clearer view of what they do.

Why Automon?

• Non-invasive monitoring and tracing: No need to alter your existing codebase.
• Flexibility: Integrates with existing monitoring tools.
• Comprehensive coverage: Audit your code, the Java Development Kit (JDK), and third-party libraries.
• Performance insights: Spot bottlenecks and optimize application performance.
• Exception tracking: Log and analyze exceptions effectively for reliability.

Key Features

• Performance Monitoring: Track execution times and identify areas that slow down your application.
• Tracing: Capture method calls, parameters, returns, and exceptions in detail.
• Exception Tracking: Understand errors and improve your application’s reliability.
• Flexibility: Compatible with tools like Micrometer, JAMon, Yammer Metrics, StatsD, and more.
• Spring Integration: Integrate Automon smoothly into your Spring applications.
• Dynamic Enable/Disable: Toggle monitoring via Java Management Extensions (JMX).

Dependencies of Automon

To use Automon effectively, familiarize yourself with its dependencies:

• AspectJ: The foundation for AOP in Java, allowing for contextual monitoring.
• SLF4J: A logging facade enabling flexible logging implementations.
• Monitoring Tools: Automon works with various monitoring tools to gather metrics and insights.

Tutorials

• Automon Tutorial: Learn how to effectively use Automon.
• Automon Aspects and Class Diagrams: Understand the structure of Automon.
• AspectJ Tutorial: Introduction to AspectJ and its implementation in Java applications.
• SLF4J and Log4j2 Tutorial: A guide to using SLF4J with Log4j2.

How Does Automon Work?

Automon employs AspectJ weaving to insert monitoring and tracing code within your application at specific points. This can occur during runtime (Load Time Weaving) or build time (Build Time Weaving). Picture this as if Automon were a skilled plumber—finding the right spots in your plumbing system to install monitoring gauges without disrupting the flow of water.

Examples of What Automon Can Do

• Monitoring: Track method invocation times and exception frequencies effortlessly. The data can be stored in your preferred monitoring tool.
• Tracing: It collects rich detail about method executions, such as entry and exit logs along with context. An example is shown below:

01:00:00.000 - BEFORE method execution
01:00:00.001 - AFTER method execution, executionTime=1ms

Automon Source Code

You can access the source code for Automon here. This includes the code for building the Automon jar file and examples of how to use it.

Glossary

• AOP: A programming paradigm for modularizing cross-cutting concerns.
• Aspect: A module that encapsulates a cross-cutting concern.
• Join Point: A point in your application’s execution where you can apply aspects.
• Weaving: The process of integrating aspects into the code.

Troubleshooting

If you encounter any issues while using Automon, consider these troubleshooting steps:

• Ensure that all dependencies are correctly defined in your project configuration.
• Verify configurations and pointcuts specified in AspectJ to ensure they align with the code being traced.
• Consult the tutorials for step-by-step guidance on setup.
• If you’re experiencing issues with specific monitoring tools, check for compatibility or documentation that outlines additional setup instructions.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Happy tracing and monitoring with Automon!