Analysis And Optimization; Automation; Resilience And Availability; Hp Adaptive Infrastructure Strategy And Portfolio - Compaq BL10e - HP ProLiant - 512 MB RAM Introduction Manual

servers, networks, and storage are often separate administrative roles, the elements interact across the
data center, which can lead to management complexity. By viewing the infrastructure as a collection
of isolated regions, with carefully specified interactions, an architecture that isolates certain regions
could potentially reduce management and maintenance costs.
Furthermore, administrators should be able to isolate the design of data center solutions from their
deployments. For example, IT specialists could design specific application solutions and then allow
other administrators or users to deploy the resources on demand.

Analysis and optimization

The architecture should incorporate data collection and analysis tools to optimize behavior against a
number of objective functions, particularly performance (peak performance of an application or
throughput in a scale-out environment); and power management (peak capping or average
consumption).

Automation

Automation is one of the most overused terms in the industry, with connotations of a technology that
magically allows complex systems to respond to changes in their environment, reconfiguring
themselves and marshalling resources to meet defined goals and policies. In reality, automation is
more like a continuum of technologies that reduces (or eliminates) response time to planned or
unplanned events. Automation can be classified according to its overall architecture, its complexity,
and its statefulness:
• Architecture - automation can be goal-oriented (sometimes called policy-based), or one-to-many
push automation. Most common models are one-to many operations such as: patching and multiple
system deployments, cloning to deploy a duplicated resource in a cloud or grid, or moving existing
systems in a disaster recovery scenario. One-to-many operations such as volume provisioning and
site failover are likely to continue as the most common models for the next two to three years.
• Complexity –An automation operation can range in complexity from a single element—such as
automatically adjusting the scheduling of a single job or system— to multiple elements of the
infrastructure, such as a failover cluster or a Virtual Connect profile migration. At the fringes of
current practice is the automation of entire applications or services which span a distributed suite of
server, storage, and network resources.
• Statefulness – The requirement for detailed state information, particularly for in-process transactions,
substantially complicates any automation process. In practice, stateful automation, (primarily
failover) is limited to very carefully designed cluster-aware applications or application servers
running on tightly-coupled failover clusters.

Resilience and availability

Application availability has traditionally revolved around the twin architectural pillars of fail-over
clustering and the ability to do site disaster recovery. As enterprises move to distributed and scale-out
architectures and newer physical and virtual infrastructures, they have new options for high
availability and disaster recovery. These new options can range from moving a failed service onto
another virtual or physical resource, to wide-area storage replication that can capture and migrate
configuration metadata and reconstitute both physical and virtual production resources at a remote
site.

HP Adaptive Infrastructure strategy and portfolio

The HP strategy and portfolio for delivering a flexible, business-ready data center architecture is
called Adaptive Infrastructure. Adaptive Infrastructure delivers a set of architectural principles that
impact data center design and delivers a set of technologies that can be incrementally deployed in
existing environments. The ultimate Adaptive Infrastructure is a highly automated environment. It
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