In 2006, Christus Health reached a painful peak in its server-processing capacity within our eight data centers and their associated space, electrical power consumption, and cooling capability. Within these data centers, nearly 500 IT associates were managing more than 600 host-based applications, 15,000 desktop devices, and 2,000 servers (70% of which were in the primary data center in San Antonio, Texas) for 30,000 users. We also had a rapidly growing server and application base and rising implementation costs.

Christus Health is a Catholic, faith-based, not-for-profit health system comprised of 380 services and facilities, including more than 50 hospitals and long-term care facilities, 175 clinics and outpatient centers, and dozens of other health ministries and ventures. Christus services can be found in 60 cities in Arkansas, Georgia, Louisiana, Missouri, Texas, and Utah, and in Chihuahua, Chiapas, Coahuila, Nuevo León, and Tamaulipas, Mexico.

As a result of the IT capacity crunch, it was getting difficult to deploy new applications and upgrade hardware without impacting business. Also, as more of our clinical care depends on our IT systems, service outages would affect more than just the business of health care operations--they would affect clinical care itself.

One of the key challenges hospitals face is the need to provide high-quality, efficient patient care while keeping hospitals and the rest of the health care system operating smoothly. Consider, for example, the variety of information that affects a patient's record: In addition to critical care information, there are financial records, demographic records, insurance claims, and inventory accountability. Behind all of these touch points are innumerable workflows and processes.

At Christus, we decided to conduct an assessment of the potential for server virtualization. By virtualizing a large deployment on a few highly scalable, highly reliable, enterprise-class servers, an organization can substantially reduce costs related to hardware and application purchases, services, and maintenance.

That assessment included an ROI analysis in our Microsoft operating system environment, where the majority of our applications reside and our processing takes place. The assessment revealed some interesting facts about our data center usage:

• 92% of the systems in the San Antonio data center were using 10% or less of their processing power;
• 97% of the systems in that data center were using 20% or less of their processing power;

• 29% of available memory was being used in the data center;
• 22% of available drive space was being used.

The results told us that we had a big IT environment with lots of systems, many of which we weren't using efficiently.

So virtualization appeared to make a lot of sense for Christus. To start the process, we selected the virtualization software: VMware ESX Server. Because of the number and diversity of applications we support, we selected an enterprise-class vendor for the hardware: Hewlett-Packard's ProLiant BL20P and BL25P blade servers. We then assessed what our optimum processing ratio would be. After studying seven to eight different models and configurations--from four-way processors with 4 GB of memory to eight-way processors with 128 GB of memory--we ended with a dual-core processor configuration with 10 to 12 GB of RAM, depending on the application. We estimated a minimum consolidation rate of eight processors to one blade to allow for spikes in processing and memory usage.

In addition, we added an HP EVA 8000 midtier storage system with 10 TB of initial storage to accommodate the pooling of resources and the virtual environment. Mission-critical services are run on an EMC Symmetric frame.

After about 16 weeks, we had established three distinct VMware farms that supported many of our important functions, including our Meditech Health Information System application servers, support servers, core infrastructure servers, and servers for enterprise applications such as the Ansos nursing scheduling system, printing, and directory services. We chose not to migrate several applications that were deemed weak candidates for virtualization such as servers regulated by Food and Drug Administration requirements, applications with unique hardware requirements such as the Kronos TeleTime system, and systems that maintain high CPU or memory utilization and enterprise databases.

ADDED BENEFIT
On one hand, virtualization has been a way to make better use of our processors and improve system availability. It's also been a way to reduce the co-location space we've had to rent while we're building a new data center. We found it would cost approximately $3 million to upgrade our hospital facilities to get the power we needed in the San Antonio data center, and since we were physically limited to obtaining only another 2,000 square feet from the San Antonio site, we decided to build a new data center, which we hope to open by the end of this year or in early 2009.

Over the last year and a half, Christus Health has used virtualization to reduce 824 servers to 83 blade servers with only one application problem. We also decreased the San Antonio data center's electrical/cooling load by 202 kilowatts, even after we had redeployed some of the savings. For every kilowatt that we save in electricity directly related to server consolidation, we save another 80% related to cooling. We translated that to $125,000 per year savings in electrical costs (San Antonio rates). What we aren't spending on co-location space averages $200,000 in cost avoidance.

Christus has spent about $975,000 to put all the technology in place, including blade servers and virtualization software. We redeployed $1.5 million worth of hardware harvested from the consolidation. With our total cost avoidance near $3 million, our net cost avoidance is $1.8 million.

Our total cost avoidance encompassed three years worth of electrical source costs, depreciation avoidance of a data center build cost, and server reallocation and reserve capacity. The difference between the total cost avoidance and the hardware, software, and implementation costs equals $1.8 million (rounded off). In other words, we would have spent $1.8 million more than we did to provide the same level of processing and IT capabilities.