= WEEKS, MONTHS, YEARS OF DELAYED APPLICATION VALUE MISSED REVENUE OPPORTUNITIES, INCREASED COST AND RISK DEV QA PACKAGE COMMERCIAL SOFTWARE CUSTOM APPLICATION.

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Presentation transcript:

= WEEKS, MONTHS, YEARS OF DELAYED APPLICATION VALUE MISSED REVENUE OPPORTUNITIES, INCREASED COST AND RISK DEV QA PACKAGE COMMERCIAL SOFTWARE CUSTOM APPLICATION CONSUME MONITOR MANAGE PRODUCTION APPLICATIONS REPEAT WITH EACH RELEASE REQUEST, NEGOTIATE, PROVISION, CONFIGURE, TUNE, CERTIFY, SCHEDULE UPDATES, ETC. The Deployment Gap: Agile Becomes Fragile

The rPath Approach  rPath helps Enterprises and ISVs automate the creation, deployment, management and maintenance of application images that are ready to deploy to any traditional, virtualized or cloud-based environment – Enterprises use rPath to reduce the cost and complexity of deploying and maintaining enterprise applications – ISVs use rPath to produce “virtual appliances” that are sold to end users as complete solutions that run out-of- the-box

Today’s Tension between Speed & Control [CONTROL] H L L H OPS  Zero visibility  Zero control  Unquantifiable risk APPS  Rapid deployment  Rapid innovation  Self-service scalability OPS  Defined standards  Scalable change mgmt  Managed risk APPS  Streamlined deployment  Managed innovation  Self-service scalability OPS  Enforce standards  Control changes  Minimize risks APPS  Slow deployment  Slow innovation  Endless request for variance [SPEED]

Understanding Cloud Alternatives InternalExternalHybrid + — -High control -Potentially lower TCO over time -Low barriers to usage and start- up costs -High start-up costs -Longer time to value -Some security and uptime concerns -Potentially higher TCO over time -“Arbitrage” -“Cloud bursting” -Switching costs unless apps are multi-platform

Leveraging the Cloud to Reduce Capital Costs Virtualizing applications makes it easy to deploy application workloads to cloud services such as Amazon EC2

Portability Enables Flexible Cloud Deployments One more small step enables the use of multiple external providers to get the best service and price

The Cloud Computing Adoption Model Level 1 Virtualization Virtualize infrastructure and applications Level 2 Cloud Experimentation Experiment in Amazon EC2; define reference architecture Level 3 Cloud Foundations Lay foundation for scalable application architecture Level 4 Cloud Exploitation Select cloud environment and begin broad-based deployments; manual provisioning and load balancing Level 5 Hyper- cloud Achieve dynamic sharing of application workload, capacity arbitrage and self-service application provisioning

Level 1: Virtualization Readiness CriteriaActions/Investments Metrics/ReturnsRisk Factors Goal: Virtualize infrastructure and applications Recognized need to deliver applications more rapidly Want to reduce IT operating costs and capital expenditure Select build/ lifecycle system for virtual applications Select hypervisor Improved server capacity utilization Improved agility, time to market for new apps Duplications of effort and VM sprawl VM quality, consistency and control issues Platform “lock-in”

Level 2: Cloud Experimentation Readiness CriteriaActions/Investments Metrics/ReturnsRisk Factors Goal: Experiment in Amazon EC2; define reference architecture IT operational bottlenecks and charge- backs constraining application value Identify and deploy select applications Define reference architecture for apps and ops Educate stakeholders and seek sponsorship Reference architecture experience Baseline metrics and anecdotal returns for momentum building Fear can kill projects Lack of business case or sponsorship can stall projects

Level 3: Cloud Foundations Readiness CriteriaActions/Investments Metrics/ReturnsRisk Factors Goal: Lay foundation for scalable application architecture Documented roles, processes, reference architecture and business case Definition of scalable apps/ops architecture Deploy build and lifecycle management platform Work with ops and architecture to define and codify release policies and practices Significant impacts in time to market for new apps Reductions in LOB charge- backs Reduction in cap ex for IT operations Lack of codified policies and practices can derail deployments Lack of maintenance automation can lead to escalating support burdens Capacity hoarding

Level 4: Cloud Exploitation Readiness CriteriaActions/Investments Metrics/ReturnsRisk Factors Goal: Select cloud environment and begin broad-based deployments Established governance processes and policies for VM development, deployment and mgmt Experience in production application deployment using this model Actively solicit apps for cloud deployment Merchandise successes Build cross- functional and management support by documenting ROI Material reductions in cap ex Material impact on business responsiveness/ agility Impact on LOB profitability through charge- back reductions As volume scales, lack of governance foundation derail projects Cloud lock-in

Level 5: Cloud Actualization – “Hypercloud” Readiness CriteriaActions/Investments Metrics/ReturnsRisk Factors Goal: Achieve dynamic sharing of application workload, capacity arbitrage and self-service application provisioning Experience delivering production scale cloud applications Management buy-in Significant organizational change Dynamic provisioning tools Multiple clouds, internal and/or external Organizational realignments Transformational impact on cap ex and op ex Material impact on LOB profitability Technology readiness Organizational resistance