Practical IT Research that Drives Measurable Results Manage & Plan Capacity for the Internal Cloud

You cannot afford to assume that the data center has unlimited capacity; this is even more true for the internal cloud Capacity management ensures IT capacity cost effectively meets business requirements. A capacity management process will reduce infrastructure waste while providing a framework for future acquisitions planning and accurate cost accounting. This research is designed for: CIOs or IT directors IT infrastructure / data center managers Internal utility infrastructure / cloud evangelists This research will provide you with: An understanding of why the “lost art” of capacity management is more critical than ever in consolidated proto-cloud infrastructures. A process and workbook for cataloging and assessing current capacity in light of the needs of the business. A process checklist for capacity management with links to relevant additional resources and tools at Info-Tech. A gas gauge model for capacity planning based on reserve capacity and maintenance of service. Capacity management and service tiers have a positive correlation with consolidation success *.36 * Capacity Planning Cost Accounting Capacity Mgmt Service Tiers

Executive Summary Manage capacity by service tiers for cost efficiency. Not all services require the same capacity. Examine variable capacity costs for each tier to see how savings might be realized without compromising service levels. Take a gas gauge approach to capacity planning. Once pools of reserve capacity are established, future capacity acquisitions are based on service maintenance rather than application addition. Capacity management is a process, not a product. Look to system management and internal cloud management tools with an eye to how they might automate your capacity management practice. Understand Assess Plan/Prepare Capacity management is a critical step between simple server consolidation/virtualization and creating the internal infrastructure-as-a-service cloud that enterprises are currently focused on building. In an internal private cloud the organization pays for everything. Unlike an external public cloud, where capacity is open-ended, the organization has to pay for total capacity -- not just capacity that is being used right now. Virtualization does not create capacity or make capacity less expensive. Server virtualization is an important enabler of internal and external cloud computing, but it alone does not make a cost effective cloud service. Turn data center management outside-in. Cloud computing is associated with delivering IT as a service. Assessing the infrastructure for capacity management and planning starts with the business and ends with a model for total cost to serve and capacity management across service tiers. Use Info-Tech’s Capacity Planning Data Collection & Tiering Workbook to assess infrastructure based on dependencies, interdependencies, criticality, and business priority.Capacity Planning Data Collection & Tiering Workbook

Understand This section will help you: Understand why capacity management is a critical activity between consolidation and internal cloud. Put virtualization in its proper place as a tactical enabler, rather than a management strategy. See how capacity management prepares the infrastructure for a cloudy future, and aids in ongoing consolidation and virtualization. This section will help you: Understand why capacity management is a critical activity between consolidation and internal cloud. Put virtualization in its proper place as a tactical enabler, rather than a management strategy. See how capacity management prepares the infrastructure for a cloudy future, and aids in ongoing consolidation and virtualization. Section in Brief Assess Plan/Prepare

Focus on capacity management to optimize cost effectiveness & service, both now and for an increasingly cloudy future An internal cloud is… … infrastructure-as-a-service (IaaS) delivered from internal IT resources. Consolidation and virtualization play a role in building an internal cloud, just as they do in external IaaS in a public cloud service (e.g. Amazon Web Services). Capacity management is important because… … virtualization does not create capacity, nor does it automatically make all capacity cost-measurable and cost-effective. A capacity management strategy will enable a move from infrastructure as asset management to infrastructure as service management. Benefits will include: The capability to document current capacity. The ability to plan capacity in advance. The ability to estimate the impact of new apps and modifications. Cost savings through elimination of over provisioning capacity, and through planned spending rather than reactive spending. Service and spending optimized to match business needs. N= 123 Most IT departments engaged in consolidation and virtualization are focused on internal cloud development first. A third (33%) will focus only on the internal cloud. 76 % focusing on internal cloud External public clouds will play a role in the future of corporate IT, but right now most IT departments are focusing on developing the internal cloud. Interest in the external cloud remains strong but implementation is in early days. Most are looking to the external cloud’s role becoming more important 3- 5 years from now. External cloud in three to five years.

Info-Tech recommends capacity management (infrastructure analysis & planning) to optimize service tiers Capacity management practices lead to greater success in infrastructure consolidation/virtualization projects. Having developed service tiers in infrastructure was the strongest predictor of overall success in consolidation. A capacity management process, such as inventorying resources annually, was also a predictor of success, especially in managing virtual server sprawl, security assurance, and business continuity. Cost accounting and capacity planning were not predictors of current success. However, as we shall see, efficient capacity planning and cost accounting are not direct inputs, but outcomes of capacity management. Correlation with Success in Consolidation/Virtualization Projects Note: * = correlation is significant. N = 88. Source: Info-Tech Research Group *.36 * Capacity Planning Cost Accounting Capacity Management Service Tiers Success was defined as: Reduced capital and facility costs. Reduced man-hours spent on management of infrastructure. Increased uptime and business continuity. Reduced “virtual server sprawl.” Reduced security concerns. Success was defined as: Reduced capital and facility costs. Reduced man-hours spent on management of infrastructure. Increased uptime and business continuity. Reduced “virtual server sprawl.” Reduced security concerns.

Where this solution set fits: Capacity management is a critical part of the larger picture of building the internal cloud 1 Alignment is Software 1 Alignment is Software 2 Hardware is Capacity 2 Hardware is Capacity 3 Management is a Differentiator 3 Management is a Differentiator Three Laws of Cloud Infrastructure Investment How do you slice this cake? Related sets that address aspects of building an internal cloud Build a Server Acquisition Strategy for the Internal Cloud Build an Optimized Infrastructure-as-a- Service Internal Cloud Mitigate Costs & Maximize Value with a Consolidated Network Storage Strategy Craft a Converged Data Center Network Strategy Evaluate a Backup Architecture Strategy Select a Consolidated Storage Platform This set is one of a series dedicated to building converged utility infrastructure (see below right). All these sets reference Info- Tech’s layer cake model of consolidation (right) and our three laws of utility/cloud investment (below left). A management process that starts with business needs, works through capacity optimization, and ends with a plan for tiered service pooling adheres with Info- Tech’s three laws because it relates capacity management directly with servicing the needs of the business. Info-Tech’s layer cake model for the internal cloud shows how infrastructure layers and virtualization all contribute to service, but an additional element is efficient management of capacity across the layers. For more detail on the three laws and how they relate to a capacity planning process see slide 18.

Compare & contrast the clouds – for the internal cloud, your enterprise pays for everything and shoulders all the risk The internal and external clouds are both abstracted environments where applications are provisioned with available and scalable compute capacity. Abstracted compute resources (processor cycles, memory, storage) are typically derived from aggregated and virtualized hardware. Compute resources are presented to the customer as a service. Both models are highly agile and responsive to changing business demands. The internal and external clouds are both abstracted environments where applications are provisioned with available and scalable compute capacity. Abstracted compute resources (processor cycles, memory, storage) are typically derived from aggregated and virtualized hardware. Compute resources are presented to the customer as a service. Both models are highly agile and responsive to changing business demands. Infrastructure is owned by an external third party. They are responsible for managing capacity and mitigating risk. Application workloads are provisioned by these abstracted resources which are elastic (they scale up with need). Customers share access to these resources (typically via the Internet) in a multi-tenant environment and pay only for what they use. Infrastructure is owned by an external third party. They are responsible for managing capacity and mitigating risk. Application workloads are provisioned by these abstracted resources which are elastic (they scale up with need). Customers share access to these resources (typically via the Internet) in a multi-tenant environment and pay only for what they use. External “Public” Compute Cloud VS. Infrastructure is entirely owned by the enterprise and managed by IT. Application workloads are provisioned by resources that can also be elastic, but scaling is limited by available capacity. The business – the sole customer of internal IT infrastructure –pays for the whole cloud regardless of how much is used. Infrastructure is entirely owned by the enterprise and managed by IT. Application workloads are provisioned by resources that can also be elastic, but scaling is limited by available capacity. The business – the sole customer of internal IT infrastructure –pays for the whole cloud regardless of how much is used. Internal “Private” Compute Cloud Key Differences Similarities

It hurts to be alone – total ownership of limited capacity imposes an expensive box that can be invisible to the business Unused capacity costs are ongoing overhead for the internal cloud. In an internal Infrastructure as a Service cloud, the enterprise pays for all capacity, not just a share of a larger third-party pool. Justifying the IT spend for total capacity is difficult when the business is used to a 1 to 1 relationship between an application and a hardware purchase. Risk mitigation is a significant component of total cost. In the external cloud, the third party provider is responsible for risk mitigation of the capacity it rents (availability, recoverability, security). In the internal cloud, IT bears this responsibility. Significant cost drivers are the hardware and data redundancy that are needed to mitigate risk. When the capacity limits are reached, physical infrastructure needs to be acquired ad hoc. The public cloud is open ended. The third-party provider maintains a practically unlimited pool of capacity that is available on demand. In the private cloud, capacity is limited. Concern about “hitting the wall” of internal capacity limits leads to over provisioning. Acquiring more capacity than is needed means wasted spending and maintenance time.

Draw a clear line from business need through software & hardware needs - transparency is not the same as invisibility The goal of capacity management is to optimize performance and efficiency of the current infrastructure, to plan for future capacity requirements, and to justify the financial investment in the infrastructure. The classic steps in capacity management are: Analyze current capacity – find out how apps are currently provisioned and what the performance and availability requirements are for each one. Optimize the infrastructure to ensure the most efficient use of existing capacity. Analyze the impact of new or updated apps on capacity. Analyze demand to model service requirements of the infrastructure and predict future growth in demand. Develop a capacity plan that relates future growth in capacity to maintenance of service levels. These steps will guide our recommendations in section 3 of this report. Capacity Management vs. Planning One Leads to the Other Capacity management is a tactical activity focused on the present. It enables cost effective provisioning of IT services by helping organizations match their IT resources to business demands. Capacity planning is a strategic activity focused on the future. It is the process determining the amount of hardware resources that will be required to deliver the appropriate level of service for the defined workload at the least cost.

Rediscover the lost art of capacity management & planning after decades of inefficient distributed processing Capacity management in IT matured in the mainframe environment, where resources were costly and it took considerable time to upgrade. Applications needed to be provisioned from a share of the centrally maintained and expensive compute resource. Resource partitions needed to be rigidly cost justified and cost managed because of the high cost of the total capacity. Expanding capacity in this environment was expensive and time consuming. As data centers transitioned to a distributed environment supported by inexpensive UNIX, Linux and Windows servers, a brute force approach to provisioning became the norm. Cheap industry standard servers could be assigned to provision specific new or expanding applications or services. Capacity management and planning skills atrophied in companies accustomed to this “throw some more hardware at it” approach. Unregulated distributing processing bred increased complexity in unregulated server sprawl, and waste in poorly utilized silos of processing and storage. That was then…This is now…

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