How to Overcome Performance Issues in Java with JProfiler

A few weeks back, Oracle rolled out its latest iteration of the Java programming language - Java 24. The programming language, which not only refuses to die quietly but is still strongly serving as the backbone of enterprise computing, will soon be offering enhanced development features, security, stability, and more. However, the Java Virtual Machine (JVM) humming quietly beneath millions of applications still hasn’t been able to address some performance issues. Despite the promises of faster startup times and smarter compilers, real-world Java applications still suffer from memory leaks, thread contention, and inexplicable CPU spikes.

JProfiler, a popular tool for deep JVM analysis, can help against such performance issues with its high-level features. In this blog, we will discuss these features in detail and see how the Java profiler can help further strengthen Java-based enterprise innovations.

Understanding the Nature of JVM

At its core, the Java Virtual Machine (JVM) abstracts away hardware-level execution to offer portability, security, and automatic memory management. It is an essential part of Java’s elegance thanks to its ability to obscure low-level execution details from developers. However, being a behind-the-scenes player, especially with its Just-In-Time (JIT) compiler, JVM leaves the developers blind to the inner workings that shape its runtime behavior. Here’s how this opacity leads to some persistent JVM issues:

• Memory Leaks:  Java developers often assume garbage collection is a silver bullet for memory optimization. However, logical memory leaks, where objects remain referenced and thus never collected, are still a prevalent issue. Complex object graphs, static references, or improperly managed caches can quietly balloon heap usage, leading to crashes with no clear culprit.
• Thread Contention and Deadlocks: Java’s multithreading model is powerful, but prone to misuse. Thread contentions and deadlocks are common when multiple threads compete for shared resources. They force high-concurrency applications or thread pools to freeze entire systems.
• CPU Bottlenecks: A method or class consuming disproportionate CPU time may not always be obvious. This is especially the case when JIT optimization obscures stack traces or when tight loops, polling, or background tasks spiral out of control. Without fine-grained profiling, pinpointing the origin of CPU spikes is like finding a black cat in a dark room.
• Hidden Cost of Abstractions: Frameworks like Spring Boot, Hibernate, and JPA abstract away a lot of logic, but these abstractions introduce layers of indirection. A single database call might trigger hundreds of method invocations across the call stack, making latency and resource consumption harder to trace.
• Remote and Containerized Complexity: In modern architectures, the JVM often runs inside Docker containers, on Kubernetes clusters, or across multiple microservices. This compounds the difficulty of profiling because performance issues may arise not from your code, but from how it interacts with the orchestrator, network, or external services.

JProfiler and Deep JVM Analysis

Expanding memory or tweaking GC settings cannot efficiently solve these issues for the JVM and the enterprise software it helps develop. Dealing with this requires an observability-first mindset towards the JVM. The Java ecosystem is mature, vast, and incredibly powerful—but it’s also deceptively abstract. Therefore, there’s a need to engage with tools that no longer treat the JVM as a black box. These tools will help analyze the code behavior within the JVM and point out issues like classloader leaks, resource starvation, GC pauses and more. Here’s how JProfile can help achieve this:

• Heap Walker and Snapshot Analysis: The Heap Walker feature helps JProfiler identify memory consumption by tracing reference chains, isolating unreachable yet retained objects, and revealing thread-local or classloader leaks. With support for HPROF, PHD, and JFR snapshots, it can offer deep memory analysis in real time. This helps with eliminating memory leaks at the root.

• Live Thread Profiling: JProfiler can also help visualize thread states, locks, and wait times to point out where contention is occurring. Local and remote request tracking helps to connect the dots across virtual threads and gRPC boundaries to illustrate the full execution path.

• Call Tree Analysis: When CPU usage surges, JProfiler drills into JIT-compiled call paths, GC events, and method-level hotspots. This helps identify the thread that spiked, the method it ran, and the time it took. With call tree, hotspot view, and live CPU metrics, JProfiles helps pinpoint the cause of CPU spikes within seconds.

• High-Level Technology Probes: JProfiler offers first-class support for technologies like Spring, JPA, JDBC, Kafka, and MongoDB. These probes add high-level semantic context to low-level method traces. This helps with understanding the relevant query, transaction, and even the REST endpoint for technology probes.
• Zero-Config Remote Profiling: Profiling inside containers is typically a nightmare of permissions and configurations. JProfiler cuts through that noise with built-in Docker and Kubernetes support. By just selecting the container in the UI, the users can get the relevant insights without dealing with any external agents or custom JVM flags.

Conclusion

Java, with JVM at its heart, is among the most influential and definitive innovations of our times. As the digital landscape constantly evolves, Java stands strong and reliable for large enterprises and their complex business use cases. However, certain natural behaviors of the JVM often lead to frustrating performance issues for Java developers. JProfiler offers the right features to deal with these issues and maintain the rightful elegance of the programming language. A slight tweak in our attitude towards Java can help us retain its robust and secure nature in enterprise digitalization.