Five Best Practices for Delivering Great Customer Experience with Java APM Solutions

Java Application Monitoring Best Practices

Java is one of the most popular programming languages in the world with thousands of business applications (banking, insurance, healthcare, retail, government, etc.) built on its robust computing platform, and millions of end-users accessing them. Ensuring superior user experience and peak application performance are mission-critical, especially as organizations are undergoing digital transformation of their businesses and focusing on growing profits through application-driven customer engagement and sales models. Addressing this need is one of the fastest growing markets in IT today: application performance monitoring (Java APM). In this blog, we will discuss 5 Java application monitoring best practices.

APM solutions are focused on understanding the customer experience and behavior as they interact with digital applications, gaining code-level insight into the application code for identifying performance issues, and deriving contextual visibility of how the underpinning infrastructure affects application performance, and, in turn, the business service.

Many different parts of the Java application stack can each impact application performance:  the JVM, Java container (Tomcat, JBoss, WebLogic, WebSphere, Glassfish, etc.), the application code executed by the container, the backend database, and the underlying server (physical/virtual/cloud), storage and network tiers. In this article, we will take a look at five best practices for setting up APM for Java applications to understand performance impact and improve end-user experience.

Best Practice #1: Measure the Digital Experience of the End User

User experience monitoring is the approach where measurements are taken of how a website or web application responds as real end-users access it. There are two methods for monitoring user experience:

Real user experience monitoring (RUM) provides real-time insights of web page availability, load time, errors, etc., helping application owners track how customer from different geographies are affected. RUM’s diagnostic capabilities help engage the correct set of stakeholders for further analysis and troubleshooting.

  • Frontend: Is the frontend JavaScript code to blame?
  • Network: TCP or DNS issues?
  • Backend: Is the server slow?
  • Content Download: Is a huge content payload size the cause of slowness?

eG Innovations Real User Monitoring - Java application monitoring best practices #1

Synthetic monitoring is the process of simulating pre-defined user transactions and synthetically testing them from different locations to proactively identify user experience abnormalities. This method does not track real user experience, but allows application teams to test synthetic scenarios and capture issues before application rollouts and at times when users are not actively accessing the service.

Best Practice #2: Deep-dive into Middleware Performance with Transaction Tracing

Assuming that RUM has identified the problem in the server-side backend, application teams then need to gain clear visibility into how a user transaction is affected and which tier in the application middleware is the cause (web server, application server, database, external calls, etc.)

Business transaction monitoring is the process of tracing business transactions across all the tiers in the Java runtime environment, and isolating the problematic tier that is causing application slowdown. Using this approach, administrators can gain code-level insight into the error-prone application code, isolate slow database queries, and pinpoint slow remote procedure calls.

Java APM business transaction monitoring - Java application monitoring best practices #2

However, transaction tracing is not sufficient by itself. You also need deeper insight into the infrastructure that underpins the application.

Best Practice #3: Inspect Java Application Components

Administrators and developers need deeper levels of Java performance insight in order to troubleshoot issues originating from the JVM, the Java container, or the server hosting them.

Critical Java infrastructure performance components that need to be monitored for problem diagnosis:
JVM Java web container Server
  • Datasource / connection pool
  • Web connectors
  • Sub-systems, such as EJB and messaging
  • Application Processes
  • TCP
  • Network
  • Operating System

Use a Java APM tool that can automatically correlate performance issues across these critical Java components and pinpoint the root cause for faster troubleshooting and problem resolution.

Best Practice #4: Utilize Converged Application and Infrastructure Visibility

Applications do not operate in silos. There are various infrastructure components such as network, server, database, storage, virtualization, cloud and containers that work together to deliver the application service. Monitoring Java business transactions will only go as far as identifying code-level issues. When there is a storage bottleneck in a SAN array that is impacting all databases and, in turn, all application queries hitting the database, transaction monitoring cannot pinpoint the problem.

A true Java APM solution must understand application dependencies across the supporting infrastructure tiers, and automatically correlate performance insights to identify if a problem in the IT infrastructure is affecting application performance. The application infrastructure must be monitored as a service with converged application-centric infrastructure visibility, rather than only in silos.

eG Enterprise Infrastructure Topology - Java application monitoring best practices #4

Best Practice #5: Leverage IT Analytics for Actionable Insights

Historical performance metrics and resource utilization data can provide a wealth of meaningful information for capacity planning, infrastructure optimization and application performance fine-tuning. Look for an APM tool that offers a wide range of pre-built and customizable reports to help analyze usage trends, forecast capacity needs, and study workload variations for load balancing. Using artificial intelligence and built-in machine learning capabilities, an APM tool can automatically baseline the infrastructure and identify performance deviations.

Key APM analytic capabilities that should be in consideration:

  • Auto-baselining
  • Automatic correlation
  • Predictive analysis
  • Capacity planning
  • Historical reporting
  • Bottleneck detection
  • Optimization recommendations

Benefits of Using Java Application Monitoring Best Practices

Developing and implementing a Java APM strategy with these five Java application monitoring best practices in place will help ensure success in the following ways:

  • Service owners ensure great user experience for customers, high application uptime and performance
  • Administrators detect problems proactively before users notice
  • Developers speed up code-level diagnosis
  • IT architects plan and invest wisely for growth

For a deeper dive into Java application monitoring best practices, watch the on-demand webinar: Why is My Java Application Slow? 5 Java Monitoring Best Practices to Deliver a Great User Experience »

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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.