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System z Is at the Center of IBM’s Smarter Computing Initiative

In 2007, IBM announced project Big Green, designed to address the ever-increasing number of servers deployed in IBM’s internal data centers that support core business operations. This project included consolidating the workloads of about 3,900 distributed servers to about 30 System z* servers. The objectives were substantial financial savings and a large reduction in energy consumption and floor-space requirements.

IBM has developed a better understanding and knowledge of IT transformations, which has led to new tools, methodologies and practices that IBM can bring to its clients.

Five years later, this project has evolved into a full-scale IT transformation, positioning IBM’s internal data centers on the path to smarter computing. As this transformative process progresses, System z technology plays a key role in the new infrastructure. Smarter computing helps organizations address today’s IT challenges—an explosion of data, inflexible IT silos, and sprawling server and storage footprints—while overcoming constraints, such as flat budgets, to transform IT economics. This approach creates an infrastructure that exhibits three fundamental characteristics:

• It’s tuned to the task, optimizing performance and economics by matching workloads to the best platform to meet specific workload requirements.
• It’s designed for data, delivering insights in seconds through systems built to process a variety of data at scale.
• It’s managed with cloud technologies, improving service quality, speed of delivery and efficiency.

IBM is utilizing these principles to deliver significant financial savings for businesses while establishing an environment for value creation.

Tuned to the Task

The decision to undertake a full IT transformation has dramatically changed the focus of the initial project. The scope has been extended to all 15,000 servers within the IBM internal account, giving the company the opportunity to assess what action should be taken with every workload. It also enables a location view of the infrastructure to systematically assess every server in any data center and decide where the workload should be located. This allows entire data centers to be decommissioned, which can provide a new level of savings.

Creating an optimized infra­structure requires each workload be deployed on the most appropriate platform, its characteristics assessed and then aligned with platform attributes. The assessment extends beyond the technical requirements of the workload to include the cost of deployment and its strategic priority to the business and the service level required. The workloads assessed so far have been deployed across various System z, Power* and System x* platforms, with about half being deployed on System z and 40 percent on Power Systems*.

While significant benefits can be realized by migrating workloads to their best-fit platforms, those migrations also include associated costs. As part of this expanded project, IBM developed a better understanding of when to migrate and created tools and methodologies to reduce migration costs.

Of the roughly 10,000 servers assessed through 2011, 6,500 migrations have occurred. Between 2008 and 2011, new practices have changed the average System z hardware migration from 200 days and $43,000 per server to 90 days and $12,000 per server.

At the end of 2011, IBM was roughly two-thirds through the transformation, which has an expected 2014 completion date. The project has delivered significant results:

• Savings to date of about $100 million
• Reduced energy consumption by more than 30,000 megawatt hours per year, roughly equivalent to the total annual power requirements of a town of 3,000
• 74,000 square feet of floor space freed up, including the closing of several data centers, delivering substantial additional infrastructure savings
• Increased average server utilization from less than 10 percent to 60 percent, and an average total cost of ownership (TCO) reduction of 70 percent

The System z platform has been a crucial player in IBM’s IT transformation. It shows the highest utilization, the greatest TCO reduction and is responsible for 60 percent of the financial savings in the project so far.

 

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