Report by gartner on server virtualization and things to watch out for and what to do about them. It touches upon all aspects of organizational planning to vitualized infrastructure.
The 10 Key Server Virtualization Unknowns, and
What to Do About Them
We all know that virtualized infrastructures increase capacity utilization. Traditional server infrastructure tightly couples applications to hardware, wasting computing capacity whenever applications use less than 100% of system resources. Virtualized infrastructures decouple applications from hardware, freeing the excess capacity for use by other applications. Gartner clients have reported that single virtualized servers often support ratios from as little as five to 12 VMs on a single server to as many as 70. The result is the ability of IT to consolidate server infrastructure, reduce capital costs associated with server acquisitions and data center infrastructure, and reduce operating costs with improved management, maintenance and energy consumption.
The flip side of the coin is that rapid application provisioning and delivery can create new costs and risks. Reducing the friction from application deployment will likely increase pressures on new application deployment and demand. The well-known real-world equivalent is known as "server sprawl." The analog in the VM world will be known as "VM sprawl." The consequence presents a plenitude of unknowns. Organizations must recognize that they not only may be exchanging one cost and management style for another, but that as physical machines are turned into virtual machines, virtual sprawl is likely to outstrip physical sprawl. Moreover, how VM sprawl acts on the network, storage, I/O and compute power across a network of server nodes, and in an increasingly dynamic model of services, will be a complex multivariant problem.
In addition to being a capacity-planning problem, it presents an integration and architectural problem. For most IT organizations, virtualizing the infrastructure will coexist with the physical and dedicated parts of the infrastructure. Many applications will require the resources of multiple physical servers with the number varying over time, not purely a slice of a single physical server. Invariably, IT organizations will be confronted with some tools that handle dedicated physical environments only, some that handle virtualized environments only, and some that handle both. Some of these issues may be mitigated by intelligent tools that understand the total infrastructure and can move workloads around. However, operational considerations, management and ownership, combined with policies, compliance and security, may restrict movement or, at a minimum, create such complexity that IT operations may decide to keep it simple and minimize too much virtualization.
For example, organizations must understand trade-offs in availability, recoverability, reliability, asset management, agility, cost/chargeback and so on. Most of the tools have emerged piecemeal, many with limited functionality, but good enough for early-stage virtualization deployments. In a few years, when massive virtualization is driven to the top of many IT agendas, many of these tools may not own up to the wider breadth of demand. As dynamic workload placement and increased optimization step to the forefront, the pure performance and utilization aspect will be one of many capabilities that need to be integrated into a unified management console. Tools will need to be self-learning, mindful of security, availability and even power-consumption requirements. Equally important will be the need for transforming data collections into a data repository, linking applications, compliance requirements, and business and performance demands to enable data center planners and architects to create a comprehensive framework for IT resource planning and daily management.
Here, we provide data center planners with a tactical planning guide and insight into the complexity of much higher scales of virtualization. We list the unknowns, or the unpredictables, that inevitably will arise as unintended consequences of interactions, computing and operational patterns that will become combinatorially explosive. From the list, IT organizations will have to create individual parts of a strategic plan that can address each of the potentially unknowable elements in terms of best- and worst-case outcomes. With this advice and these recommendations, IT organizations should be able to minimize surprises and risks as they embark on ever-increasing scale in combined physical and virtual infrastructures, while striving for the ideal of real-time response and service levels.
1. Can 100% of applications be virtualized, and even be practical, in the next few years?
2. How will VM proliferation affect IT organizations' abilities to impose rules and policies?
3. What infrastructurewide behavioral effects can occur as VM creation escalates to thousands of VMs?
4. How and when will dynamic real-time virtualization with continuous load balancing become feasible (if at all)?
5. Can predictable mission-critical service levels with root-cause analysis be applied to VMs in a dynamic and mobile environment?
6. How will virtualization impact ISV licensing terms and practices as resource allocation becomes increasingly dynamic and distributed?
7. How will TCO change as VMs proliferate and scale throughout the enterprise, and what are the main dependencies?
8. How will virtualization impact application design and development to suit modularity, security, OS affinity and configurability?
9. What network constraints will arise from end-to-end application latency as large numbers of VMs are rapidly provisioned from repositories?
10. How will storage management evolve to monitor and manage the expected strong growth induced by VM-driven storage during rapid VM provisioning within and beyond the enterprise (such as clouds)?
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