The document discusses moving corporate computing to the cloud to reduce costs and inefficiencies. While security and integration concerns prevent fully moving to public clouds, companies can learn from cloud providers like Amazon and Google. The document proposes a solution using a cloud of commodity infrastructure to automatically provision and optimize applications on demand according to performance, costs and changing requirements. It argues this could reduce costs, improve utilization and agility compared to traditional datacenter models.

1. Cloud Computing For the Corporate Data Center

2. Internet Companies: An Arms Race The Dalles, Oregon

3. Is this the end of Corporate Computing So why doesn’t company X tear down their data centers and move everything to Amazon cloud? Security, integration with enterprise and proprietary systems, performance and control requirements will prohibit this from happening But can Company X learn from Google and Amazon?

4. But what if ….. All running on a cloud of commodity infrastructure, automated to respond to changing requirements and optimized for performance and costs. … . You could operate like Google ? Services in the cloud that could be activated on demand … for an unlimited set of users With great user experience

5. Modern Datacenters Build-Out: Standard Technologies – Poor Results Standards in Datacenter Yet Poor Economic Results Over provisioned Complex sprawl Inefficient operations Not agile Expensive IT-Driven Business Web Apps Everywhere Big IT Budgets Commodity X86 Machines Migration to Linux Cheap Energy

6. Analyst View “ As grid deployments have matured and become more integrated with other activities, drivers for adoption have evolved ….. cost control, revenue generation, better utilization, support for additional workloads and the ability to more quickly respond to changing needs are all benefits that can now be realized. This is no longer a one-dimensional world of performance improvement.”

7. CC for the CDC Business Perspective

8. Datacenter Spend Data center facilities spend is a large, quickly growing and very inefficient portion of the total IT budget in many technology intensive industries….. Drivers Poor demand and capacity planning within and across functions Significant failings in asset management (6% average server utilization, 56% facility utilization) Boards, CEOs, and CFOs are not holding CIOs accountable for critical data center facilities and operational efficiency Source: McKinsey

9. Constrained by Inefficiency – Impacts Profitability

10. Middleware As A Service Network Compute and Storage VM VM VM VM VM VM VM VM Dynamic Application Service Management Packaging Provisioning Activation Management Developers Tools Tools Tools C L O U D Customers L O C A L On-Demand

11. Cost Reduction Prioritize cost cutting opportunities Lifecycle methodology for identifying, prioritizing and realizing business value (DART) Visualize infrastructure and cost models Integrated reporting on application service levels, costs and infrastructure utilization Eliminate waste and human errors Standardized, re-usable approach to dynamic application assembly and provisioning Lower app dev costs Automated configuration and packaging for market-leading applications and platforms Lower infrastructure cost Buy only what you need Dynamically allocate infrastructure according to business policies Cost Reduction Benefits Key DASM Features

12. Utilization VMware or Physical X86 or non Leverages investments in virtualization (servers / apps / networks / storage) Works with what you have New technologies integrate with existing investment (servers / apps / networks / storage) Visibility Platform that reports on application cost, utilization & performance across shared infrastructure Automated Dynamic Policy-driven virtual application service level management Transportable across infrastructure Standardized packaging and provisioning of virtualized applications Utilization Benefits Key DASM Features

13. Given current design and architecture: Questions for the Data Center …. To monitor infrastructure costs To minimize growth rates To maximize response time To speed deployment To control utilization How do you meter and chargeback shared application services based on SLA? How do you optimize application performance based on changing demand in real time? How do you provision applications on demand? How do you standardize and automate application packaging and configuration? How do you define and enforce business service levels for critical applications?