Virtualized Infrastructure Journey – Progressing

to Service Assurance

Xangati Blog

Atchison Frazer Vice President, Marketing

Feb 23, 2015

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The dramatic growth of virtualized infrastructures and cloud architectures is being driven by a

number of trending market conditions and customer requirements. Those market drivers include: an

increase in demand for mobile computing, wider acceptance of hybrid cloud services, and

implementation of so-called bimodal IT (conventional/digital). The associated benefits of the

virtualized movement are reduced costs, increased productivity, business agility and operational

flexibility.

However, there remain a number of significant barriers to widespread VI adoption:

• CISO’s still have a great need for granular security and policy management – at a virtual

machine level, as well as dealing with the threat of untrusted user security, anomalous traffic

patterns and management of failure domains in a virtual environment.

• The end-user experience also has to be top of mind to overcome perceptions that virtual

workspace infrastructure suffers from poor and unreliable performance, negatively affecting

employee productivity.

• Finally, even virtualizing desktops doesn’t necessarily eliminate the inherent weakness of

measuring service assurance if the conventional cross-silo functions (compute, storage,

networking), VI admins, end-users and line-of-business managers lack a common performance

analytics platform.

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Many IT organizations are still struggling with managing multiple interactional functions. For

example, with conventional, siloed management tools, VI admins are unable to perceive how

different functions, shared storage for example, affect all the other VI components, and they also find

it challenging to determine the root cause of performance issues.

What is needed to effectively operate a high performance VI environment in real time is the ability to

optimize the end-user experience from the following factors:

• Resolve performance issues faster by collecting and analyzing data from the entire

infrastructure out to the client devices

• Diagnostics to spot root cause of issues by correlating highly granular data

• Predict future resource contention storms and access dynamic remedial action

recommendations

• Support large VI environments with scalable in-memory architecture, while managing

performance of interrelated components from a single console

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Viewing performance issues through an operational maturity prism, the picture crystalizes in terms

of how leveraging service assurance analytics can become a business critical strategy to moving

from a reactive to a proactive to a predictive performance management posture.

At a baseline level, in which the enterprise finds itself in a totally reactive mode, typically you will see

disparate technology-specific organization silos with strong domain expertise. However, this type of

organization maintains only partial asset control, tends to deploy hardware-based provisioning, and

IT alone tends to define performance management tools.

At the next phase of operational maturity, you will typically see more converged infrastructure

spawned by cross-technology collaboration improvements spanning service support processes but

with limited compliance. Web services are more progressively adopted that allow applications to be

addressed without full understanding of the underlying technology. IT performance management

tools and service support processes are being optimized.

During the mid-journey phase of the continuum, where most enterprises and large organizations fall

today, a corporate virtualization strategy and hybrid-cloud roadmap exists, and a migration plan from

service-oriented architecture to contemporary API management is already defined.

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Additionally, high availability converged infrastructure services for virtualized applications are

delivered with performance information aggregated in real time across all VI components. This

makes it much easier to map applications to converged infrastructure and services, and deploy an

integrated ‘data analytics fabric’ for performance management and business continuity scenarios.

Integrated SLAs and OLAs (operational level agreements) and underpinning contracts are executed

with well-defined, cross-silo metrics captured and measured.

Following the continuum at the most progressive phase, the virtualized infrastructure is fully stable

and services are dynamically provisioned according to business priorities. Autonomic and adaptive

capabilities for self -healing and performance tuning are introduced into the environment. New virtual

applications can be assembled rapidly as composites of existing applications, while performance

management and governance start to converge through implementation of policy-based business

imperatives. At this stage, the organization implements a fully integrated approach to performance

so that end-to-end processes are optimized to meet defined business targets based on real-time

metrics reporting.

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Finally, at the business outcome phase, whereby the enterprise has achieved full operational

maturity in terms of a high performance virtualized infrastructure, infrastructure capacity and

utilization trends can be aligned to right-sizing goals for application services, and policy-based

performance management influences application and process behavior in real time. Unpredictable

peak capacity can be accessed on the fly, internally and/or externally by way of a hybrid-cloud

architecture platform. Key to delivering on service assurance targets is the reliance upon an

intelligent data analytics platform that provides a holistic, 360-degree health status view of the entire

virtualized infrastructure.

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