The Java Virtual Machine (JVM) is an important part of the Java programming language, allowing applications to run on any device with the JVM, regardless of the hardware and operating system. It interprets Java bytecode and manages memory, garbage collection, and performance optimization to ensure smooth execution and scalability. Effective JVM monitoring is critical for performance and stability. This is where OpenTelemetry comes into play.

In the fast-paced world of software development, efficiency is everything. Developers are constantly under pressure to keep up with rapid technological changes, unclear requirements, and tight deadlines. With the demand for skilled developers rapidly increasing and projected to grow by 22% by 2029 in the US alone , finding ways to enhance productivity and streamline workflows can provide a much-needed relief, making the difference between delivering a project on time or spending long nights debugging.

As Elastic continues its commitment to OpenTelemetry (OTel), we are excited to announce the Elastic distribution of the OTel Java Agent. In this blog post, we will explore the rationale behind our unique distribution, detailing the powerful additional features it brings to the table. We will provide an overview of how these enhancements can be utilized with our distribution, the standard OTel SDK, or the vanilla OTel Java agent.

Java has long been a foundational pillar in application development, its versatility and robustness serving as key drivers behind its widespread adoption. Since its inception, Java has evolved to meet the ever-changing demands of scalable deployments, offering a reliable platform for creating everything from web applications to complex, server-side systems.

Log4j is a logging framework for Java, facilitating the systematic recording of runtime information in software applications. Developed by the Apache Software Foundation, Log4j has become a standard tool in Java development since its inception in 1996. Its primary purpose is to generate log messages that provide insights into the application's execution, aiding developers in debugging, monitoring, and analysing software behaviour.

SRE and IT Operations play a critical role in ensuring reliable, high-performance applications. Yet, SREs (Site Reliability Engineers) often face ‘thrown-over-the-wall’ code deployments to operate without having insights into the code-level features. In my previous article (“Is your Java Observability tool Lambda Expressions aware?”), I delved into one such code-level feature: Java lambda expressions which replace anonymous inner classes.

In Java applications, concurrency issues can be difficult to reproduce and debug. Because work is scheduled nondeterministically across threads, the conditions that have led to an error in one execution of the program may not trigger the same issue the next time around. Exceptions that are silently handled—also known as swallowed exceptions—can also be challenging to debug because they typically do not leave any trace in the logs.

Most SREs and IT Ops manage Java applications without source code access or communication with AppDev teams. When applications have performance issues those SREs or IT Ops teams deploying and maintaining the infrastructure often have to prove that it is the application at fault and supply information to the app supplier which provides evidence of the issue.