A collection of 5 top tips for JBoss performance tuning to ensure optimal application performance and resilience. Learn how to monitor and troubleshoot JBoss systems to eliminate bottlenecks, reduce costs and minimize user issues.

What is JBoss?

JBoss is an open source, standards-compliant, J2EE application server implemented in 100% pure Java. There are many variants of JBoss available today:

  • JBoss EAP is the name for the Java EE application server that Red Hat produces and supports.
  • JBoss AS and WildFly are the community versions of the JBoss application server.

While Apache Tomcat used to be the underlying engine for JBoss EAP and AS, more recently, Undertow is used as the application server engine.

Top tips for JBoss performance tuning

Today’s blog is a quick overview of 5 areas, which are those most likely to be worth your while scrutinizing and optimizing. It should be noted that simply doing performance tuning on JBoss alone is not enough to produce a high-performance application. It is just one of the steps that you need to follow. A more detailed guide on optimizing Java applications within the context of JBoss usage including configuration settings is also available, see: JBoss Performance Tuning & Monitoring | eG Innovations.

I’ll also cover what capabilities the eG Enterprise application performance monitoring and observability solution offers out-of-the-box for JBoss-based applications. Tools such as eG Enterprise are commonly used for JBoss monitoring to automate alerting without the need for scripting or coding and because they cover interdependencies and the whole stack from Java code to server CPU and network.

1. Tune Garbage Collection (GC) for better JBoss performance

  • The performance of Java applications running on JBoss can be impacted by inefficient garbage collection (GC) processes. Garbage collection is a critical process that manages memory in Java applications by reclaiming memory occupied by objects that are no longer in use. However, inefficient GC settings or configurations can lead to increased CPU usage, longer pause times, and degraded overall application performance.
  • Tune garbage collection (GC) settings in JBoss to optimize memory management and improve application performance. Properly configuring and tuning GC parameters such as heap size, garbage collection algorithm, and GC tuning options can help minimize pause times, reduce CPU usage, and optimize memory usage. This can result in improved response times, reduced resource consumption, and enhanced overall application performance.
How can eG Enterprise help?

eG Enterprise provides real-time monitoring and analysis of GC-related metrics, such as GC Pause Times, GC Throughput, Heap Utilization, GC Events, and Memory Usage. It offers JBoss memory analysis capabilities, such as automatic heap dump analysis and GC performance analysis, to identify bottlenecks, inefficiencies, and tuning opportunities in GC processes. This helps in optimizing GC configuration and achieving optimal GC performance. eG Enterprise also offers performance comparison reports for different garbage collection algorithms such as CMS vs G1 vs ZGC.

eG Enterprise enables proactive alerting on GC-related issues in JBoss, such as high GC pause times or heap usage, allowing SREs and IT Operations to quickly identify and resolve problems before they impact application performance. It also provides monitoring capabilities for test and development environments, allowing for thorough testing and fine-tuning of GC configuration before applying changes to production environments.

Learn all about Garbage collection in Java: What is Java Garbage Collection | eG Innovations

2. Optimize resource allocation for JBoss-based applications

  • Inadequate allocation of system resources, such as CPU, memory, disk, and network, in JBoss-based applications can result in performance degradation, slow response times, and potential application failures.
  • Monitor resource utilization: Use eG Enterprise performance monitoring tools to regularly monitor resource utilization, such as CPU usage, memory usage, disk I/O, and network traffic, in the JBoss environment to identify any resource bottlenecks or inadequacies.
  • Optimize resource allocation: Analyze resource utilization patterns and identify any inefficiencies or imbalances in resource allocation. Optimize resource allocation settings, such as CPU affinity, memory allocation, and disk caching, in the JBoss environment to achieve optimal resource utilization and prevent resource-related performance issues.
  • Scale resources dynamically: Implement dynamic resource allocation techniques, such as auto-scaling, in the JBoss environment to dynamically allocate or deallocate resources based on the application’s workload demands, to ensure optimal performance during peak or fluctuating workload periods.
  • Plan for future growth: Anticipate future growth and allocate resources accordingly in the JBoss environment to ensure scalability and performance of the application as the workload increases over time.
How can eG Enterprise help?

eG Enterprise can help with:

  • Real-time monitoring of resource utilization metrics, such as CPU usage, memory usage, disk I/O, and network traffic, in the JBoss environment to provide insights into resource utilization patterns and detect resource bottlenecks or inadequacies.
  • Proactive alerts and notifications: eG Enterprise can generate proactive alerts and notifications based on predefined thresholds or anomalies in resource utilization, allowing IT administrators to take proactive measures to allocate sufficient resources and prevent resource-related performance issues in JBoss-based applications.
  • Automated resource allocation: eG Enterprise provides automation capabilities to dynamically allocate or deallocate resources based on workload demands, allowing for optimal resource allocation in JBoss environments.
  • Performance optimization recommendations: eG Enterprise can provide performance optimization recommendations, such as CPU affinity, memory allocation, and disk caching settings, based on resource utilization patterns and best practices, to optimize resource allocation in JBoss environments.
  • Capacity planning: eG Enterprise simplifies capacity planning by sorting hosts (both physical and virtual) based on metrics such as CPU, memory, disk and network. JBoss administrators can categorize hosts, compare relevant metrics, and analyze resource allocation.

    If JBoss deployments are virtualized, you can save money by optimizing host capacity through actions like automatic scaling of VM instances. However, overloaded hosts can lead to poor performance, longer response times, and lost revenue. On the other hand, virtual hosts may underutilize allocated resources while their physical hosts have ample available capacity. eG Enterprise can identify these imbalances and alert you to take corrective measures.

3. Connection pool monitoring for JBoss


Monitoring database connection pool performance and identifying issues such as database connection leaks in JBoss-based applications can be challenging without proper visibility into connection pool metrics and usage. If the connection pool is exhausted or not configured properly, requests to the application may take longer than usual to complete. This can result in slow response times and a poor user experience. And if connections are not released back to the pool properly, they may be held open indefinitely. This can cause the pool to become exhausted, resulting in slow response times, application crashes, or data inconsistencies.


There are many metrics you should proactively monitor for JBoss connections such as ActiveCount, AvailableCount, MaxUsedCount which are available via the native CLI, API and HTTP API.

When using a connection pool, you need to balance the costs of keeping connections open vs. opening/closing new connections. Ideally you will want to size the connection pool such that the number of idle connections is minimized, but also optimize the frequency at which you open/close new connections. You will also need to ensure that the maximum number of connections is appropriate, as this will limit the maximum capacity throughput that a database can achieve.

If monitoring reveals problems with connection pool performance or connection availability, you may need to tune the connection pool. Some advice on how to configure and tune your connection pools is given in JBoss Performance Tuning & Monitoring | eG Innovations.

How can eG Enterprise help?

eG Enterprise for JBoss enables monitoring of connection pool performance metrics out-of-the-box, such as connection pool size, active connections, idle connections, and connection usage statistics. This helps identify potential bottlenecks or performance issues related to connection pooling.

eG Enterprise can also detect and alert on connection leaks, which can occur when connections are not properly closed after usage, leading to resource exhaustion and potential application failures.

4. Optimize JBoss clustering with caching to improve Java performance

  • The performance of critical Java functions in JBoss could be adversely impacted by the high load on the database. This could result in slow response times and degraded overall application performance.
  • Implement application and web caching as part of JBoss Clustering to reduce the load on critical Java methods and functions. By caching frequently accessed data in memory, JBoss Clustering reduces the need to repeatedly fetch data from the database, resulting in faster response times and improved overall application performance.
  • However, be sure to tune the cache. Performance issues such as cache misses, high turnaround, and memory exhaustion can impact your application negatively.
How can eG Enterprise help?

eG Enterprise can help with:

  • Real-time monitoring of caching-related metrics, such as:
    • Cache Hits: The number of times data was successfully retrieved from the cache without needing to fetch from the underlying data source.
    • Cache Misses: The number of times data was requested from the cache but was not found, resulting in a fetch from the underlying data source.
    • Cache Evictions: The number of times data was removed from the cache to free up space for new data.
    • Cache Put Operations: The number of times data was added or updated in the cache.
    • Cache Hit Ratio: The ratio of cache hits to the total number of cache accesses (hits + misses), expressed as a percentage. A higher hit ratio indicates a more effective cache.
    • Average Time for Cache Access: The average time taken for a cache access operation, including both cache hits and misses. This metric can provide insights into the efficiency of cache retrieval operations.
    • Cache Size: The current size of the cache, indicating the amount of data stored in the cache at any given time.
  • Alerting and troubleshooting: eG Enterprise provides alerting capabilities to detect any abnormalities or issues with the JBoss caching mechanism and ensure timely troubleshooting and resolution of cache-related performance issues. Learn about eG Innovations’ AIOps automated alerting and anomaly detection capabilities, see: Proactive IT Alerts & Alert Monitoring | eG Innovations.

5. Optimize database access when implementing JBoss-based applications

  • Inefficient database access patterns and queries in JBoss-based applications can result in unnecessary database roundtrips, increased database overhead, and degraded performance.
  • Review and Optimize Database Access: Analyze the application’s database access patterns and queries to identify any inefficient or redundant queries that result in unnecessary database roundtrips. Optimize database access patterns and queries to minimize database overhead and improve overall application performance.

How can eG Enterprise help?
  • Monitor database performance: eG Enterprise monitors database performance metrics, such as query execution times, database CPU utilization, database I/O, and database connection pooling, to identify any potential performance bottlenecks related to database access.
  • Alerts and notifications: eG Enterprise can trigger alerts and notifications based on predefined thresholds for database performance metrics, allowing proactive identification and resolution of database-related performance issues before they impact application performance.
  • Visualize database performance: eG Enterprise provides graphical dashboards and reports that visualize database performance metrics, making it easy to identify inefficient database access patterns, redundant queries, and other areas that need optimization.
  • End-to-end monitoring: eG Enterprise provides end-to-end monitoring of the entire JBoss application stack, including the underlying infrastructure, application servers, web servers, and databases, allowing comprehensive performance analysis and optimization of database access within the larger application context.
  • Database-specific monitoring: eG Enterprise supports monitoring of various databases, including Oracle, Microsoft SQL Server, MySQL, PostgreSQL, IBM DB2, and others, providing database-specific insights and recommendations for optimizing database access in JBoss applications.
  • Real-time and historical monitoring: eG Enterprise provides real-time and historical monitoring capabilities, allowing analysis of both current and historical database performance trends, patterns, and anomalies, and enabling proactive identification and resolution of database-related performance issues.

Other best practices for improving JBoss application performance include:

  • Optimize Logging: Avoid excessive logging, configure logging levels appropriately, and log only what is necessary for troubleshooting and monitoring.
  • Enable Compression: Enable compression for web content to reduce the amount of data transmitted over the network and improve response times.
  • Apply Security Best Practices: Follow best practices for securing the JBoss environment, such as keeping it up to date with security patches, implementing proper access controls, and securing communication channels.
  • Implement Load Balancing: Use load balancing techniques, such as JBoss clustering or a dedicated load balancer, to distribute application workload across multiple servers for improved performance and scalability.

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About the author

Arun is Head of Products, Container & Cloud Performance Monitoring at eG Innovations. Over a 20+ year career, Arun has worked in roles including development, architecture and ops across multiple verticals such as banking, e-commerce and telco. An early adopter of APM products since the mid 2000s, his focus has predominantly been on performance tuning and monitoring of large-scale distributed applications.