The Deployment Gap: Agile Becomes Fragile DEV QA PACKAGE COMMERCIAL SOFTWARE REQUEST, NEGOTIATE, PROVISION, CONFIGURE, TUNE, CERTIFY, SCHEDULE UPDATES, ETC. CONSUME MONITOR MANAGE PRODUCTION APPLICATIONS CUSTOM APPLICATION REPEAT WITH EACH RELEASE WEEKS, MONTHS, YEARS OF DELAYED APPLICATION VALUE = MISSED REVENUE OPPORTUNITIES, INCREASED COST AND RISK
The r. Path Approach § r. Path 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 r. Path to reduce the cost and complexity of deploying and maintaining enterprise applications – ISVs use r. Path 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 OPS § Zero visibility § Zero control § Unquantifiable risk [SPEED] H OPS § Defined standards § Scalable change mgmt § Managed risk APPS § Streamlined deployment § Managed innovation § Self-service scalability § Rapid deployment § Rapid innovation § Self-service scalability H L OPS § Enforce standards § Control changes § Minimize risks APPS L § Slow deployment § Slow innovation § Endless request for variance [CONTROL]
Understanding Cloud Alternatives Internal + — External Hybrid - High control - Potentially lower TCO over time - Low barriers to usage and startup costs - “Arbitrage” - “Cloud bursting” - High start-up costs - Longer time to value - Some security and uptime concerns - Potentially higher TCO over time - 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 EC 2
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 5 Hyper- Achieve dynamic sharing of application workload, capacity arbitrage and self-service application provisioning cloud Level 4 Level 3 Level 2 Level 1 Cloud Exploitation Cloud Foundations Cloud Experimentation Virtualization Select cloud environment and begin broad-based deployments; manual provisioning and load balancing Lay foundation for scalable application architecture Experiment in Amazon EC 2; define reference architecture Virtualize infrastructure and applications
Level 1: Virtualization Goal: Virtualize infrastructure and applications Actions/Investments Metrics/Returns Risk Factors • Recognized need to deliver applications more rapidly • Select build/ lifecycle system for virtual applications • Improved server capacity utilization • Duplications of effort and VM sprawl • Want to reduce IT operating costs and capital expenditure • Select hypervisor • Improved agility, time to market for new apps • VM quality, consistency and control issues Readiness Criteria • Platform “lock-in”
Level 2: Cloud Experimentation Goal: Experiment in Amazon EC 2; define reference architecture Readiness Criteria Actions/Investments Metrics/Returns • IT operational bottlenecks and charge-backs constraining application value • Identify and deploy select applications • Reference architecture experience • Define reference architecture for apps and ops • Baseline metrics and anecdotal returns for momentum building • Educate stakeholders and seek sponsorship Risk Factors • Fear can kill projects • Lack of business case or sponsorship can stall projects
Level 3: Cloud Foundations Goal: Lay foundation for scalable application architecture Readiness Criteria • Documented roles, processes, reference architecture and business case • Definition of scalable apps/ops architecture Metrics/Returns Risk Factors • Deploy build and lifecycle management platform • Significant impacts in time to market for new apps • Lack of codified policies and practices can derail deployments • Work with ops and architecture to define and codify release policies and practices • Reductions in LOB chargebacks Actions/Investments • Reduction in cap ex for IT operations • Lack of maintenance automation can lead to escalating support burdens • Capacity hoarding
Level 4: Cloud Exploitation Goal: Select cloud environment and begin broad-based deployments Metrics/Returns Readiness Criteria Actions/Investments • Established governance processes and policies for VM development, deployment and mgmt • Actively solicit apps for cloud deployment • Material reductions in cap ex • Merchandise successes • Material impact on business responsiveness/ agility • Experience in production application deployment using this model • Build crossfunctional and management support by documenting ROI • Impact on LOB profitability through chargeback reductions Risk Factors • As volume scales, lack of governance foundation derail projects • Cloud lock-in
Level 5: Cloud Actualization – “Hypercloud” Goal: Achieve dynamic sharing of application workload, capacity arbitrage and self-service application provisioning Readiness Criteria • Experience delivering production scale cloud applications • Management buy-in • Significant organizational change Actions/Investments • Dynamic provisioning tools • Multiple clouds, internal and/or external • Organizational realignments Metrics/Returns • Transformational impact on cap ex and op ex • Material impact on LOB profitability Risk Factors • Technology readiness • Organizational resistance
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