Critical Java business applications have been deployed for some time. However, enterprise IT support staff members still face difficulties in ensuring application health and performance.
The scale and complexity of deployments have grown, and customer-facing apps are experiencing more traffic than ever before. For example, for the first time last year, the banking industry reported that online banking transactions exceeded traditional in-branch transactions.
This growth in usage was accompanied by technology trends such as Service Oriented Architectures (SOA) and cloud-based models for storage, infrastructure, and application hosting – making applications more dynamic and agile than ever before.
Monitoring tools have become very good at collecting performance metrics for these new architectures. These tools have become so good at generating performance data that, according to Gartner, IT staff have to try to analyze 300% more metrics than just four years ago. There can be hundreds, or even thousands of metrics for just one application running on a single server. And enterprise scale applications can consist of hundreds or thousands of servers. It's not surprising then that many of today’s application performance management (APM) tools have failed to evolve their analytics enough to help users address this “Big Data” problem in APM.
What is required is a solution that will help users model and understand the volume, velocity, variety, and complexity of the new dynamic application ecosystem and, as much as possible, automate the process of digesting and understanding all this performance data.
To learn more, check out this new white paper (registration required). It looks at two developments that will help IT and application support staffs better understand and manage the performance of distributed Java applications.
Specifically, you will learn the following:
- How application performance monitoring has changed, and how a new APM paradigm is best suited to help support staff understand the performance of distributed Java applications.
- How analytics technologies have evolved to automate performance management and analysis of applications and their supporting infrastructures.
Graham Gillen is the Product Marketing Director for Netuitive. He currently leads Netuitive’s initiatives to market solutions in the areas of applications performance management and private cloud management. Before joining Netuitive in 2008, Graham worked at VeriSign and webMethods (now Software AG). Graham’s educational background includes executive training in Marketing at the University of Virginia Darden School of Business, a Master of Science degree from Georgia Tech and a Bachelor of Science degree in Engineering from the University of Virginia.