This paper presents the network and hardware section of a Google IT strategic plan, focusing on the company's transition toward cloud computing as a core revenue driver. It examines Google's global data center footprint, projected server growth requirements to support a 20% annual expansion in cloud services, and the infrastructure demands of Google AppEngine and Platform-as-a-Service (PaaS) offerings. The paper also addresses contingency planning through a formal business continuity planning methodology and recommends that senior management review the IT strategic plan on a six-month cycle tied to performance incentives. Together, these elements form a framework for sustaining reliability, scalability, and long-term profitability.
The paper demonstrates applied strategic planning writing: it moves from a high-level business objective (cloud revenue growth) down through operational specifics (data center locations, server counts, virtualization standards) and then to risk management (business continuity methodology). This top-down structure is characteristic of well-organized IT strategy documents and shows how academic sources can be woven into a professional planning framework.
The paper opens with a framing section that establishes the strategic context for the entire plan, followed by an introduction that defines the overarching IT goals. The core analytical section covers Google's global data center network and server growth forecasts, supported by tables and citations. A contingency planning section applies a formal business continuity methodology. The paper closes with a brief governance recommendation about plan update cycles. This structure mirrors a real corporate IT strategic plan document.
Orchestrating the global network of hardware, systems, and services to ensure continual stability, reliability, and fault tolerance — so that business strategies can be supported and sustained — is the overarching goal of the Google IT Strategic Plan. The network and hardware section concentrates on how all available IT resources can be used to support and strengthen the strategic plans, initiatives, and strategies of the company (Google Investor Relations, 2014).
With cloud computing becoming an increasingly larger percentage of Google's annual revenues and profits, this section of the strategic plan focuses on optimizing the network and hardware infrastructure to maximize AppEngine performance. The Google AppEngine has the potential to dominate enterprise cloud computing given its inherent scalability, support across the Google series of fabric controllers that optimize searches, and deep Application Programming Interface (API) expertise (Prodan, Sperk, & Ostermann, 2012). One of the most critically important strategic goals of this plan is creating an optimal architecture to streamline and ensure the highest performance possible for Google AppEngine running in heterogeneous, complex enterprise software environments. This requirement is driven by the depth and breadth of applications that many Google enterprise-class customers maintain and the ubiquity of support necessary for them to productively build AppEngine-based applications. The network and hardware infrastructure must reliably and securely scale to support Google AppEngine as a result.
A second strategic initiative that the Google IT plan must support and continually scale to optimize is the corporate-wide performance of Platform-as-a-Service (PaaS) offerings, which have grown into a significant business over the last two years (Google Investor Relations, 2014). PaaS services provide the potential for Google to move beyond its heavy dependence on advertising and shift its competitive focus directly toward Amazon Web Services, IBM, and others who are defining the broader enterprise cloud computing landscape (Beimborn, Miletzki, & Wenzel, 2011). Creating an optimized IT infrastructure to enable excellent Google AppEngine performance in enterprises (Prodan, Sperk, & Ostermann, 2012) — while also supporting the scalability and enterprise security requirements for PaaS-based platform development and sales — is essential for Google's long-term profitability and financial growth (Google Investor Relations, 2014).
Google's global business model must serve as the foundation on which the IT strategic plan is built, starting with the data center strategy. Defining the optimal data center strategy will in turn define the optimal level of network services, support, servers, and application support. As the Google AppEngine and PaaS-based businesses continue to accelerate, additional data centers are anticipated to be required.
The first Google data center was constructed in 2003 in Douglas County, Georgia, followed by locations in Oregon and North and South Carolina. In 2008, the first European data center opened in St. Ghislain, Belgium (Google Investor Relations, 2014). As of 2014, Google operated approximately 2.4 million servers installed across twelve data centers worldwide.
Google's cloud business has been growing at a consistent rate of approximately 20% per year, with the majority of cloud computing enterprises located throughout the United States. With the bulk of cloud computing growth occurring in North America, continued investment in commodity-class servers that include virtualization options for scaling across excess, unused computing capacity is a requirement for driving greater Return on Invested Capital (ROIC) relative to strategic planning assumptions in the Google operating budget (Google Investor Relations, 2014).
Based on the 20% annual growth assumption, Google senior management needs to budget for an incremental 1,743,360 servers over the next five years to support the growth of cloud-based business models and new services. This forecast of IT system requirements over the next five years is intended to support the revenue and profit objectives for the cloud computing business (Google Investor Relations, 2014).
Within five years, all of these systems will need to be fully compliant with internal virtualization standards and requirements, while also having the ability to conform fully to Google Mesh architectural standards. The continual efforts of Google Engineering to define virtualization standards and mesh computing algorithms show potential to drastically reduce ROIC on these servers over a seven-year depreciation period (Google Investor Relations, 2014). Google Mesh standards and APIs will also support ongoing efforts to expand into enterprise cloud computing in organizations dominated by a wide variety of diverse applications and systems that need to be cloud-enabled (Paul, Jain, Samaka, & Pan, 2014).
This approach to creating a unified cloud computing architecture will require intensive investments in servers and predominantly open-source operating systems, which Google has historically standardized on to reduce licensing costs (Google Investor Relations, 2014). The Google File System and Grid — which forms the foundation of the search engine, apps platform, Google ID membership system, APIs, and application layer of the architecture — must all be orchestrated together to ensure scalability and security over time. This strategic plan concentrates on forecasting server requirements across all current and future data centers as the cloud computing business is projected to grow significantly over the next five years.
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