TABLE OF CONTENTS
As a server virtualization administrator, it's your job to read the future in an ever-changing environment. Virtual server capacity planning is a challenging task that requires predicting data center growth, estimating server workloads and application performance objectives, and ensuring that virtual server infrastructure has the hardware capacity to meet those requirements. To boot, all this planning must be cost-efficient without wasting resources or space.
This virtual server capacity planning strategy guide offers tips and best practices on developing strategies, avoiding virtualization management problems and using advanced tools to make a virtual server capacity plan foolproof.
This section explains successful capacity planning strategies. Experts discuss how to plan for growth, achieve capacity planning for a virtualized environment and follow a step-by-step capacity planning strategy.
Capacity planning for virtual environments
A capacity planning strategy for server virtualization must be ongoing. Capacity planning in virtualization environments requires a detailed inventory of the amount of space available and the applications running on current hardware as well as a watchful eye on the virtualized server to anticipate future changes. IT analyst George Crump explains how to begin capacity planning at any point in the server virtualization process.
Expert answers questions on planning for growth
Capacity planning is one of the primary steps when building a virtual environment in a new organization. You must first determine the services the environment will provide, then deploy enough storage to fit the size of the environment. To learn the next steps of this process, read these expert answers on preparing for growth and using Hyper-V backup tools in a capacity planning strategy.
Five pitfalls of virtualization, and how to avoid them
One main danger with deploying virtualization is failing to perform capacity planning prior to building the virtual environment. This article outlines five common mistakes in capacity planning strategies and tips to plan for capacity costs and expectations from the start.
Capacity planning checklist
Learn how to assess your company's current and future hardware needs to plan for growth. It's important to meet with executive management to understand past growth and how it relates to future growth. Be sure that the predicted changes to your infrastructure can support this anticipated growth. And use capacity planning to determine the possible need for possible server consolidation. This five-step checklist outlines a simple, successful capacity planning strategy.
Proper virtualization management requires capacity planning both before deploying virtualization and once the virtual infrastructure is in place. Unlike physical systems, virtual environments create overlap among servers and hardware, making it difficult to determine where to run applications and which underutilized hardware can take on additional load. This section focuses on capacity planning through the lens of virtualization management, providing you with tools to plans for growth in and changes to the virtual environment.
Old management styles don't work with blades, virtualization
Several established management tools won't be as successful in a virtualization environment. Watch out for these potential problems when capacity planning for a virtualization environment.
Using virtual systems management to define server ownership
Virtualized systems make it difficult to keep track of who owns what servers and which business units use which applications on different servers. A successful capacity planning strategy understands resource requirements and uses utilization rates to predict future needs for new hardware. Learn how to plan for growth in a virtualization environment and clarify server ownership through capacity planning.
Network architecture and capacity planning for server virtualization
When capacity planning is done before implementing virtualization, changes during the deployment -- such as a decrease in physical servers -- can cause problems. The capacity planning strategies discussed in this article suggest high-availability and data-replication software to minimize the impact of server problems on the network.
How a proper data capacity planning strategy aids in disaster recovery
Read this firsthand account of an expert's experience with capacity planning strategies -- some that have worked and some that haven't. Learn how a data capacity planning strategy can help with disaster recovery.
This section delves deeper into the best capacity planning strategies, focusing on advanced practices and tools for complex virtual environments. These tips include capacity planning guidance for Microsoft, Linux and Unix systems. Learn how to use million instructions per second (MIPS) to your advantage and watch out for capacity planning pitfalls.
Capacity planning for virtualized Microsoft environments
Use Windows tools to establish a system that monitors performance and helps track growth in a virtualized environment. Microsoft's System Center Virtual Machine Manager analyzes performance data to help administrators determine the capacity of servers and potential problems.
Capacity planning tools tutorial for Linux and Unix
This expert zeroes in on capacity planning strategies for Linux and Unix users. Use data management tools that are optimized for your system to generate historical data from your server. Find a variety of recommended tools for sizing your system and gathering data for capacity planning.
Mainframe capacity planning: More than MIPS
MIPS (millions of instructions per second) are not the only units important in capacity planning. Read this capacity planning scenario to see how problems can arise when you have too many top-priority workloads.
Balancing virtual machine (VM) workloads to improve security and performance
Balancing workloads among virtual machines maximizes a system's utilization and prevents future data leakages. Combine security zones within the same virtualization hosts to create a capacity planning strategy that maximizes available data capacities.
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