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Java IoT: Article

Four Steps and 90 Days to Transform a Datacenter to the Cloud

An Enterprise View...

All this while the IT team is faced with another reality, the main corporate datacenter has 6-18 months left in terms of shelf life. The datacenter's power distribution and patch panel design was not built to handle the massive density and cooling power requirements. The sprawl of unstructured data, app servers, web servers and now virtual machines is proliferating at a pace that will force a space crunch in a time frame that is counter to the challenge from the business in terms of capital preservation and opex reduction.

What does a firm do? The standard playbook is consolidate, virtualize and automate. This strategy is absolutely critical and is part of a target foundation that must be built. However, it will NOT solve the challenge of above.

A different approach needs to be taken.  The approach starts with a fundamental principle - IT delivery must be "as needed-when needed" AND all things IT are services that should be delivered in a real time enterprise cloud utility model.  With this as the fundamental theory, below outlines four (4) key steps for firms to institute and apply in 90 day building blocks to achieve radical results. It important to note these steps can be executed in parallel and in a continuous, iterative and concurrent manner.


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Step 1 - Identify the most critical business applications & largest consuming applications in terms IT resources in the datacenter.  These become the primary targets for driving a demand driven optimization approach to transforming the datacenter.  Rule of thumb is 30% of applications typically consume or create need for 70% or greater of the datacenter infrastructure.  Apply a decomposition process to these applications one at a time or in group of similar types.  Measure and map the workload across the IT supply chain in terms of performance, consumption and attributes of how the work execution is managed and what infrastructure does it actually use.  This linkage approach of demand and supply creates a data driven, objective view to drive change.  By changing how you manage the application (dynamically at runtime, virtualized across all layers - work, information and infrastructure) and changing what it runs on (standardized and purpose driven infrastructure that leverages network and computing physics) firms can consistently find they can do twice the work on ½ the infrastructure.  That math alone will drive radical impacts quickly.

Step 2 - Institute a discipline immediately (in parallel to step 1) that measures and monitors consumption, performance AND understands the IT supply chain dependencies of every application. If you don't understand what an end to end application view and dependency looks like, then how can you virtualize or optimize. You are more likely to create further problems in terms of user experience and sev 1 incidents than improve things.

Step 3 - Standardize your management strategy of the IT Supply chain across the datacenter from a top down perspective.  Incorporate building blocks of runtime management and service orchestration WITH holistic virtualization (it is very important to note the "with and holistic".  Firms who do implement just infrastructure virtualization without workload and information virtualization will negate the optimization they are trying to achieve as they will create new bottlenecks for the delivery of IT from the datacenter.  Firms who do not implement dynamic runtime management of workloads will not exploit the elasticity of their virtualization efforts.  You have to bring demand to supply as it happens not force demand into a pre-defined supply model.

The second building block is a purpose built combination of datacenter footprints that provide optimized physics - from energy draw, to heat dissipation, to quantity and types of cables required to connect, communicate and run workloads.  A unified footprint of network, compute, storage, appliances and software runtime that matches the types of workloads the enterprise supports creates a simpler, leaner platform engineering model.

The third building block is the lifecycle management of provisioning, repurposing and re-provisioning standard builds on top of the unified footprints.  This automation gives the business the ability to flex the infrastructure to meet the fluctuating demands while exploiting optimized footprints and matching dynamic workload management needs of the business behavior.

Step 4 - Operationalize these building blocks into a new delivery paradigm.  Processes need support instantaneous adjustments of IT delivery to accommodate business behavior.  Approval processes and standard operating procedures need to accommodate this model.  Finally, IT must learn from business intelligence and constantly mine, analyze and leverage behavior data to proactively predict, tune and adjust the infrastructure.

By leveraging this approach, firms can rapidly make large quality and quantity impacts with very targeted efforts. This model can be leveraged globally now, since industry leading firms such as Unisys, Cisco and Adaptivity are bringing such thought leadership and strategy to enterprise IT groups through datacenter transformation solution offerings.

More Stories By Tony Bishop

Blueprint4IT is authored by a longtime IT and Datacenter Technologist. Author of Next Generation Datacenters in Financial Services – Driving Extreme Efficiency and Effective Cost Savings. A former technology executive for both Morgan Stanley and Wachovia Securities.

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