Choosing the Right Tool for Your Observability Needs 🔭
In this article, we will learn more about OpenTelemetry (OTel) and Java Flight (JFR) Recorder for dynamic analysis and compare their similarities and differences to determine which is a better choice for different scenarios.
OpenTelemetry (OTel) VS Java Flight Recorder (JFR)
Terms like observability, profiling, and monitoring have many similarities and differences but also some ambiguities. This overlap in the concepts and applications of these terms will be more problematic when it comes to tools and utilities related to these concepts. In general, all these terms will help us observe and monitor the system’s behavior to learn about system performance, health, and flow. The knowledge gained by this tool will be helpful for optimization, troubleshooting, and system behavior analysis.
Table of Contents
Background
To make a good comparison, we need to introduce OpenTelemetry (OTel) vs. Java Flight Recorder (JFR) briefly to see their common concepts.
In short, OpenTelemetry (OTel) is an Observability framework and toolkit. According to the official websites:
OpenTelemetry (OTel) is an Observability framework and toolkit designed to create and manage telemetry data such as traces, metrics, and logs.
OpenTelemetry is focused on the generation, collection, management, and export of telemetry. A major goal of OpenTelemetry is that you can easily instrument your applications or systems, no matter their language, infrastructure, or runtime environment.
On the other hand, Java Flight Recorder (JFR) is a performance monitoring and profiling tool built into the Java Virtual Machine (JVM). According to the official website:
Java Flight Recorder (JFR) is a tool for collecting diagnostic and profiling data about a running Java application. It is integrated into the Java Virtual Machine (JVM) and causes almost no performance overhead, so it can be used even in heavily loaded production environments.
JFR collects data about the JVM as well as the Java application running on it.
Is this comparison correct?
OpenTelemetry is an open-source observability framework created by merging OpenTracing and OpenCensus. It provides a unified set of APIs, libraries, and agents to collect and export traces, metrics, and logs from distributed applications, offering a comprehensive view of system performance and behavior. Java Flight Recorder, on the other hand, was initially developed by Oracle and is an advanced profiling tool integrated into the Java Virtual Machine (JVM). It was designed to continuously monitor and record detailed information about Java applications with minimal performance overhead.
As is clear, OpenTelemetry and Java Flight Recorder are both tools used for observability, profiling, and monitoring, but they have different scopes, capabilities, and use cases.
It makes sense to compare them in this context to know how to use them in different scenarios.
Core Features and Capabilities: OpenTelemetry (OTel) VS Java Flight Recorder (JFR)
To continue our discussion, we will review their core features.
OpenTelemetry (OTel) Scope and Focus:
- OpenTelemetry is a broader observability framework that provides standardized APIs, libraries, agents, and instrumentation for collecting telemetry data (traces, metrics, and logs) from distributed applications.
- It is not limited to Java and can be used with multiple programming languages and environments.
- OpenTelemetry can be integrated with visualization tools like Grafana, Jaeger, Prometheus, and Zipkin to effectively monitor and analyze your application’s performance and behavior.
Check out a detailed article about OpenTelemetry and its components: Here.
Java Flight Recorder (JFR) Scope and Focus:
- JFR is primarily focused on the detailed monitoring and profiling of Java applications.
- It provides low-overhead, high-resolution telemetry data specifically for JVM-based applications.
- The data collected by JFR can be analyzed using Java Mission Control (JMC), a suite of tools that provides visualizations and analysis capabilities to help interpret the recorded data.
Technical Comparison
Compared to Java Flight Recorder, OpenTelemetry requires more steps and components to collect telemetry data. Since Java Flight Recorder is released as a built-in tool into the Java Virtual Machine (JVM), we only need to start it via command-line options when launching a Java application. On the other hand, In order to use OpenTelemetry to instrument telemetry data in an application, we need to use the OpenTelemetry SDK (or the zero-code approach) in our application and also run an OpenTelemetry Collector server to receive the telemetry data from the application.
Technically, metrics and events recorded by Java Flight Recorder are more detailed than telemetry data collected by OpenTelemetry. For example, JFR can record a wide range of detailed events, including garbage collection activity, thread activity, I/O operations, and more. On the other hand, OpenTelemetry collects a wider range of telemetry data (traces, metrics, and logs), and it is not limited to JVM-based applications.
Use Cases
Based on the scope and focus of each tool, we can see the following use cases for them:
OpenTelemetry Use Cases:
- End-to-end observability in microservices architectures.
- Correlating telemetry data across different services and technology stacks.
- Monitoring and troubleshooting distributed systems.
Java Flight Recorder Use Cases:
- Performance tuning and optimization of JVM applications.
- Detailed troubleshooting and debugging of JVM-related issues.
- Continuous monitoring of Java applications in production.
Advantages and Limitations: OpenTelemetry (OTel) VS Java Flight Recorder (JFR)
We will finish our comparison with a comparison table that shows the advantages and limitations of each in different aspects and scenarios.
How does Digma utilize OpenTelemetry?
Digma is an advanced observability and performance analysis platform designed to integrate seamlessly with OpenTelemetry, ensuring comprehensive data collection across distributed systems. By leveraging OpenTelemetry’s capabilities for distributed tracing, metrics collection, and logging, Digma provides deep insights into application performance and behavior. This integration allows for the aggregation and correlation of telemetry data from various services, creating a unified view of the entire system. Digma’s robust analytical tools enable rapid identification of performance bottlenecks, anomalies, and errors, facilitating quicker diagnosis and resolution of issues. This holistic approach significantly enhances the ability to monitor, troubleshoot, and optimize complex distributed architectures, ensuring high availability and reliability of applications.
Final Thoughts:
In the previous article, I compared the Static Analysis vs. Dynamic Analysis approach for program analysis. In this article, we compared two famous tools for dynamic analysis (OpenTelemetry OTel vs. Java Flight Recorder JFR), And finally, we found out the use cases of each tool in real projects. Knowing this knowledge can help us to choose the proper tools for suitable situations.
Download Digme: Here
