Heap Walker scripting for snapshot analysis

Previously, JProfiler's heap walker only offered advanced filtering and grouping features in live sessions. With JProfiler 15, the heap walker introduces full support for filtering and grouping in snapshots. A new API lets you write scripts to filter objects or define custom grouping logic based on dumped object data.

This screencast demonstrates the new functionality with a small Hibernate-based demo that creates different types of query cache entries. Hibernate’s second-level cache can quickly fill up with unexpected entries, and identifying what’s taking up space is key to resolving memory issues. JProfiler now makes it possible to answer such questions with snapshots.

The screencast shows how you can:

• Group cache keys by query structure to compare memory impact
• Use object set filter scripts to isolate problematic cache entries
• Use merged dominating references to understand why objects are retained

Capturing and comparing MBean states with JProfiler

MBeans expose a wide range of runtime metrics and management operations that are essential for understanding the internal state of Java applications. Traditionally, JProfiler has supported live inspection of MBeans during a profiling session.

With the new MBean snapshot feature in JProfiler 15, it is now possible to capture the complete MBean state, compare snapshots, and analyze metrics offline, even after the application has shut down.

This screencast demonstrates the new functionality with a small Hazelcast application that performs random map operations and registers a custom MBean for triggering cleanup operations.

Along the way, you will see how to:

• Capture and compare MBean snapshots manually
• Trigger MBean snapshots programmatically with method triggers
• Restrict the snapshot scope to specific MBeans

Advanced SSH remote profiling with JProfiler

Remote profiling can be challenging when SSH access involves custom setups, proxies, or cloud authentication plugins. JProfiler 15 introduces advanced SSH connection features that remove these obstacles, enabling profiling in complex environments without manual setup.

This screen cast shows how to profile remote JVMs even in situations where the built-in SSH client is insufficient, using AWS Session Manager as an example.

Along the way, you will see how to:

• Use OpenSSH mode for remote profiling
• Connect with ProxyCommand and the AWS CLI
• Handle SSH port forwarding restrictions with netcat mode

Profiling Java applications in VS Code with JProfiler

JProfiler now integrates directly into VS Code, bringing the powerful profiling tool into your everyday development workflow.

In this screencast, we profile the Spring Pet Clinic demo and walk through the features of the JProfiler extension for VS Code, including:

• Toggling profiling mode
• Automatic setup of profiled packages
• Source code navigation from profiling views
• Attach mode for unsupported launch methods (like Maven)
• Built-in Gradle integration

If you're using a launch method in VS Code that isn't currently supported, let us know — we’re always looking to expand support.

Advanced Kafka probe configuration in JProfiler

In our first Kafka screencast, we looked at how JProfiler correlates message flow and CPU usage through producers, consumers, and topic-level call trees.

In this follow-up, we go deeper, showing how to configure custom naming for Kafka messages based on their content.

This enables you to:

• split call trees by semantic message types
• track specific event types in probe views
• add value-level details to single event descriptions
• visualize outliers in event duration histograms

We also trigger a Kafka message spike via an API call and analyze its impact, all without changing the application code.

Profiling Kafka #1 – Message Flow & Hot Spots

Kafka-based applications are notoriously hard to profile. Message flow happens in background threads, stack traces don’t reveal the full picture, and it’s hard to know which topic contributes to which hot spot.

JProfiler’s Kafka probes give you deep insight—producers, consumers, and message-level details are all captured and correlated with performance data.

This screencast walks through profiling a Spring Kafka application, showing how:

• consumer call trees are split by topic
• producers link directly into probe views
• you can correlate CPU hot spots with Kafka topics
• Kafka events are filterable, inspectable, and aggregatable

Garbage collector analysis in JProfiler

This screencast shows how to use the garbage collector probe in JProfiler. Having access to detailed information about the overall activity of the GC, as well as the single garbage collections, is crucial for tuning the garbage collector and achieving an optimal performance for your application.

Recording JFR snapshots with JProfiler

Recording JFR snapshots with JProfiler

This screencast shows JProfiler's versatile functionality as a JFR recording controller. As an example, a JFR recording on a Kubernetes cluster is recorded and the resulting snapshot is shown in JProfiler. In this context, you can see the wizard for configuring JFR recording settings. In addition, JFR recordings of terminated JVMs and the handling of externally started JFR recordings are demonstrated.

Enhanced JFR snapshot analysis with JProfiler

JProfiler has excellent support for viewing JFR snapshots. This screencast focuses on the event browser, which is specific to JFR snapshots, and also gives an overview of the other view sections that offer some of the same views as regular profiling sessions.

Working with probe events in JProfiler

Probe events are of great help in debugging specific performance problems. To find events of interest, JProfiler gives you a lot of tools to narrow down the set of displayed events.

This screencast shows the HTTP server and HTTP client probes, the JDBC and JPA/Hibernate probes as well as the socket probe when profiling a real-world application. The various ways of filtering probe events as well as duration and throughput histograms are explained.

The profiled application is the CommaFeed RSS reader.