Customer-facing and transaction-oriented applications are often built
using Web-based and/or service-oriented architectures, running in open
source environments such as JBoss or on leading commercial application
servers including BEA WebLogic or Oracle Application Server. These
applications experience volatile demand for system and data resources,
with processing requirements that vary significantly throughout the day.
The demand for improved response time creates an insatiable appetite
for more compute power. IT organizations have traditionally answered
this call by adding system resources to support increased transaction
volumes and to meet associated service level requirements. This
approach has had a number of negative effects, such as:
Excess Capacity: Adding servers, storage and bandwidth each time a
new application is installed contributes to an already underutilized
pool of computing resources.
Increased Costs: Building out a siloed, dedicated infrastructure can be expensive to deploy and cumbersome to maintain.
Limited Growth: Resources are dedicated to specific applications,
limiting the ability to take advantage of excess capacity by
horizontally scaling the infrastructure or dynamically allocating
This approach limits the business' ability to respond to market needs
-- especially when it can take weeks or months to rollout hardware and
software in support of new applications. Many organizations recognize
the need for software that can help them utilize existing capacity and
improve the performance and reliability of their J2EE applications.
Extending from Compute-Intensive to Transactional Applications
A recent article in NetworkWorld
acknowledges the evolution of Grid beyond its roots in HPC or "compute-intensive" applications.
"As Grid computing enters more enterprise environments, the buzz over
the technology's potential never ceases. Once Grids are installed,
network executives find them useful for a far wider variety of
applications than just computationally heavy ones. They also work well
for applications that have high transactional volumes or are data
intensive. And after sending those apps to the Grid, it dawns on these
early adopters that what they have is a giant, powerful -- and
comparatively inexpensive -- next-generation generic application
, Sept. 26, 2005)
When applied to applications built in J2SE, J2EE and .NET, Grid
middleware can enable transparent scaling across the computing
The goal is to create an application provisioning and runtime
environment that enables applications to be virtualized from hardware
infrastructure. Instead of applications being configured and
provisioned on specific computers, applications are configured to run
on an application service fabric without identifying the exact set of
computers that they will run on. This creates a highly adaptive
environment for running applications on a shared set of computers or
Grid. In this virtualized environment, automated provisioning decisions
are based on usage policies created for each application. These usage
policies describe the measurable attributes of the application,
including response time or throughput, and rules such as minimum and
maximum resource utilization.
In this scenario, applications in need of more compute-power to
accommodate volatile workloads are provisioned automatically (based on
business policy) at runtime. Traditionally, J2EE applications were
limited to manual provisioning across fixed, siloed clusters. When
distributed over a Grid, it is possible to automatically provision
additional, available system resources to the Grid in order to satisfy
demand. This allows for IT departments to scale with ease, aligning IT
with business goals and dramatically improving service levels.
Benefits of Grid-Enabling Transactional, J2EE Applications
Policy-based Provisioning and Activation: System resources are
allocated at runtime, based on priority, to ensure that service levels
are aligned with business goals. The provisioning and scheduling is
driven by service level policy that can be defined by application or
groups of resources. The result is a more agile and responsive IT
Seamless Virtualization of Java Services: This includes the ability
to virtualize applications built using "plain, old Java objects" and
Enterprise Java Beans. Supporting both programming models provides the
flexibility companies need to seamlessly and transparently run their
applications in an adaptive Grid infrastructure.
Service Level Management: By monitoring and managing key metrics
such as throughput, latency, resource usage and exceptions, the Grid
software can take corrective action by dynamically provisioning
resources to address service levels that may be in breach, assuring
compliance and optimized service level management.
Rapid Application Deployment: The goal is to deploy cross-language,
versioned applications and environment settings, with a facility for
rolling out new applications or components to distributed resources --
while the Grid is still actively running other applications. This
allows for many applications and different versions of the same
application to run in the same distributed environment.
Unlimited Application Scalability: Additional processors can be
simply added to the compute pool, without limit, and made available for
work automatically, on demand. As additional computing power is needed,
the Grid software dynamically provisions resources on the new servers,
enabling applications to be effortlessly and transparently scaled.
Massive Task Throughput Rates: One of the most important
requirements in transaction processing is the ability to handle high
volumes of requests per second. Ideally, hundreds of thousands of tasks
per second are flowing through the adaptive Grid infrastructure.
New technology is available to bring the benefits of Grid computing --
radically improved service levels at significantly lower cost -- to
J2EE applications. When applied in these transactional environments, it
is possible to achieve horizontal scale that optimizes resource
utilization and reduces the need for more hardware. Dynamic service
provisioning allocates resources based on business policy to assure
maximum productivity. Ultimately, this is a logical evolution that can
make the vision of "on-demand computing" an enterprise reality -- by
deploying Grid resources as needed and where needed to meet demand.
About Kelly Vizzini
As chief marketing officer at DataSynapse, Kelly Vizzini works to
leverage the company's existing successes and domain expertise to build
a brand identity that positions DataSynapse as the de facto standard in
the U.S. and European markets for distributed computing solutions.
Prior to her role at DataSynapse, Vizzini held marketing positions at
several software companies including Prescient, Optum, Metasys and
InfoSystems. She holds a bachelor's degree in journalism and
communications from the University of South Carolina.