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Virtualizing Enterprises: Challenges Harrick M. Vin Vice President and Chief Scientist Tata Research Development and Design Centre, Tata Consultancy Services.

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Presentation on theme: "Virtualizing Enterprises: Challenges Harrick M. Vin Vice President and Chief Scientist Tata Research Development and Design Centre, Tata Consultancy Services."— Presentation transcript:

1 Virtualizing Enterprises: Challenges Harrick M. Vin Vice President and Chief Scientist Tata Research Development and Design Centre, Tata Consultancy Services (TCS) January 2010 Harrick M. Vin Vice President and Chief Scientist Tata Research Development and Design Centre, Tata Consultancy Services (TCS) January 2010

2 Enterprise Goals 2 Adapt easily to different business contexts, regulations, M&A, … Responsiveness to market and customer needs Adaptive Rapid introduction of new products / services / business processes Agile Meet & exceed business and customer expectations (service levels) Minimize total cost of operations Efficient Enterprise Goals

3 January 2010 Enterprise Transformations Key message: –Many “how to transform” mechanisms … Yet, transformation is difficult –Challenge: What, when and why ! (It’s all about policies) Analytics-led automation Key discussion topics: 3 Key Message Why analytics-led transformations? How does it work? What can it do? Virtualization in Enterprise: Example

4 January 2010 Enterprise IT Transformation Challenges 1 No single optimization mechanism meets all requirements 2 Many different realizations of each mechanism Different implementations are suited for different environments 3 Each optimization mechanism has cost, benefits, risks, and side effects Key challenge: Deciding on what, when and why? “One-size-does-not-fit-all”  Custom strategy reqd for each environment Suitability depends on “as-is” state 4 Scale and complexity of “as-is” state 4 Why Analytics? Today’s best practice: Manual, intuition-based strategy derivation Implication: Many implementation “surprises”  Many failed transformation programs

5 January 2010 Analytics-led Transformations Analyze PlanTransform Prepare 5 Transformation planner; Address the “what”, “when” and “why” questions Execute the transformation strategy using various “how” mechanisms & processes Monitor an operational enterprise; data cleansing and preparation for analytics Analyze “as-is” state; Joint analysis of business process, applications & infrastructure Understand operations support Industry Best Practices Industry Best Practices Emerging Technologies Emerging Technologies How Does It Work? 4 2 1 Analytics-led Transformation: Fact-based & Automated Strategy Derivation 3

6 January 2010 Virtualization in Enterprises Large numbers of dedicated, under-utilized servers The pain: High cost of operating enterprise IT Virtualization  Consolidation of physical servers  Higher utilization Virtualization benefit: Right-sizing of server environment What target server platform and configuration should one select? Which servers should one consolidate together? What will the target server utilization be? What, if any, will be the impact on application performance? In what order should one migrate to the virtualized state? What will the benefits of server consolidation be? … Many “strategy derivation” questions: 6 Virtualization

7 January 2010 Deriving Enterprise Virtualization Strategy Many choices Many different target server platforms and configurations Many virtualization technology implementations (w/ cost & applicability constraints) Many constraints Business constraints Technology refresh plan and processes (depreciation and refresh intervals) Data center consolidation strategy and schedule; application retirement Restrictions on consolidating infrastructure for different business processes Technology constraints Restrictions on consolidating different architectural and OS platforms Applications requiring special-purpose hardware Usage constraints Separate development and production environments Consolidate servers with out-of-phase resource utilization patterns Requires systematic exploration of the solution space 7 Virtualization

8 January 2010 iTransform What does it do?What does it do? How does it do it?How does it do it? 8 Virtualization iTransform: A transformation strategy planner What to do? When to do? Why to do? Example: Right-sizing and placing of servers The what: Select target platform(s) and virtualization technologies Determine the consolidation plan: Technology, business and workload constraints The when: Derive a transformation schedule: Minimize risk … maximize rewards The why: Derive a business case Input data Application & infrastructure inventory, utilization, growth plans & cost (CapEx and OpEx) Approach: Systematic exploration of the design space Codify constraints, benefits and side effects of transformation implementations

9 January 2010 Beyond Virtualization Clouds offer different deployment options for virtualized environments Many different cloud providers Different cost-benefit tradeoffs and constraints From virtualization to clouds … Mainframe, storage, network, desktop, application/tech stack, labor, … … And beyond Lots of optimization dimensions and mechanisms Scale and complexity of as-is state Challenges Automate as-is state analysis Formalize transformation strategies: cost, benefits, risks, side effects Dependencies between transformation strategies Systematize and automate strategy derivation Research opportunities 9 Concluding Remarks

10 For more information, contact: Harrick Vin (harrick.vin@tcs.com)

11 January 2010 Infrastructure Fact: Scale & Complexity 11 30,000+ servers 5+ OS w/ 20+ versions 10+ database products 2500+ app server instances 25+ middleware envr. 35+ programming languages 200,000+ desktops 10+ petabytes of storage 197,000 e-mail boxes, … Infrastructure Inventory 4000+ business apps Average age: 3.5+ years 10-20 years: 190+ 20+ years: 60+ Significant overlaps 25+ account opening apps 10+ authentication apps 12+ credit decision engines 15+ BI tools, … Top-tier bank in the US The Problem

12 January 2010 Infrastructure Fact: Scale & Complexity 12 The Problem

13 January 2010 Infrastructure Fact: Scale & Complexity 13 Silo-based understanding  Little understanding of the global picture ! Application Dev Teams Capacity Planning Operation Support Compliance Plant Mgmt Security The Problem

14 For more information, contact: Harrick Vin (harrick.vin@tcs.com)


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