The Importance of Deep Application Component Monitoring in the Cloud

By Peter and Todd, with guest author, Peco

In a previous blog post, we highlighted some of the key questions that organizations should ask themselves before moving their applications to the cloud, and introduced a performance assessment concept to facilitate smooth migrations.

Peco Karayanev of National Instruments grappled with issues like these while migrating some web-based J2EE applications to the Amazon Elastic Compute Cloud (Amazon EC2). Peco shared the following comments with APMmatters.com:

As Spiderman would put it, “With great power comes great responsibility” … Cloud abstracts some of the infrastructure parts of your system and gives you the ability to scale up resource on demand. This doesn’t mean that your applications will magically work better or understand when they need to scale… For deeper instrumentation we have worked with OPNET to deploy their AppInternals Xpert (former OPNET Panorama) solution in the Amazon EC2 cloud environment. We have already successfully deployed AppInternals Xpert on our own server infrastructure to provide deep instrumentation and analysis of our applications.

While cloud computing can reduce operational overhead related to maintenance of the supporting IT infrastructure, the need to manage and guarantee application performance remains as important as ever—if not more challenging—due to the dynamic and volatile nature of the cloud. Just as in a self-hosted environment, application owners need to monitor performance in the cloud and recover rapidly from any problems that may occur. While some providers offer basic monitoring capabilities that focus on resource utilization and availability, they lack an in-depth understanding of application behavior. For complex applications, it is therefore often difficult to isolate the root causes of degradations to transaction response time and availability.

AppInternals Xpert provides real-time component-level visibility across all servers in the application environment by tracking thousands of system and application metrics from the Java/.NET application server, web server, and database tiers. It uses advanced correlation technology to automatically detect cause-and-effect relationships and to pinpoint root causes of performance problems that would be impractical to find using other approaches. It can be configured during implementation in cloud environments to establish continuity of performance data, even across dynamically instantiated virtual machines, changes to VM hostnames, and IP addresses.