Monetizing PaaS and Implementation Models!

1. Monetizing PaaS and Implementation
Models
Sachin Sancheti
Principal Architect – Windows Azure
13-Apr-2012

2. IT Responsibility Matrix
Collaboration, New Markets,
Strategic
Research, New Business Models,
Process Optimization New Cost Models
Monetization
Vision
Demands,
Competitions,
Innovation,
Time to Market
Tactical
Keep the lights on, Global Access,
Maintenance,
Infrastructure Device Integration,
Optimization Disaster Recovery
Scope
Internal External

3. Challenges and Trends
New way
• Give me more for less of
operating
• Innovation is not a choice
• Keep up the business growth
• Cost - Reduction and Optimum utilization
• Competition and Time to Market
• Operational Challenges Better
Online
New Experience
Business
Models

4. •

5. Cloud Workload Patterns
On and Off Growing Fast
Compute
Compute
Inactivity On off
Period
Average Usage
Average Usage
Time Time
• •
• •
• •
Unpredictable Bursting Predictable Bursting“
Compute
Compute
Average Usage Average Usage
Time Time
• •
• •
• •

6. Application and Data

7. Cloud Computing Taxonomy The Windows Azure
Platform fits here
Traditional IT IaaS PaaS SaaS
You manage
Applications Applications Applications Applications
Data You manage Data Data Data
Runtime Runtime Runtime Runtime
Managed by vendor
Middleware Middleware Middleware Middleware
You manage
Managed by vendor
O/S O/S O/S O/S
Managed by vendor
Virtualization Virtualization Virtualization Virtualization
Servers Servers Servers Servers
Storage Storage Storage Storage
Networking Networking Networking Networking
Higher Cost, Less Agility Lower Cost, Agile

8. Monetization - Implementation Models
ISVs targeting new customer markets through SaaS
Solution
SaaS •
•
Develop the multi-tenant SaaS solution on Azure
Manage and operate
• Business consulting - licensing, pricing
Gather data from multiple sources at a central location to enable decision making
Solution
Data Hub •
•
Azure as a “data hub”
Provide real time data to drive decision making, thereby resulting in operational efficiency
improvement
A disaster response system with humongous scale in the wake of a disaster
Second largest
Disaster Solution
• Identified an open-source CMS (Umbraco). Nuclear Power
Response •
•
Extended CMS’ functionality to auto-provision & auto-scale
Minimal cost during peaceful times. Ability to scale within minutes, when needed
Generator
Compress time to run complex data intensive operations
Solution
High Compute •
•
Utilized Azure storage for input and output files
Integration with on-premise systems
• Cost saving of over 50% in 3 months
Infrastructure to onboard partners
Solution
Partner Platforms • Partner portal site on Azure providing the ability to handle heavy traffic (predictable burst) &
high compute in the cloud with permanent data storage on-premise
• Developed SDKs for multiple products to enable partners to develop applications on Azure
Seasonal + unpredictable spikes in traffic & bandwidth
Solution:
Burst for Online • Home page on Azure. On-demand provisioning of compute instances
• Hybrid Azure to handle peak capacity.
8

9. Depth Of Experience Across Verticals
SAAS
DATA HUB
SURGE
COMPUTE
MOBILE
MANUFACTURING ENERGY /
HEALTHCARE FINSERV RETAIL ONLINE EDUCATION
UTILITY

10. Azure Adoption Cycle
BUSINESS
ADITI/CUMULUX
ADITI/CUMULUX
TECHNOLOGY
10

11. Common Concerns?
• Security Aspects
• Physical
• Application
• Data
• Compliances
• Windows Azure
• Windows Azure ISO 27001 Certification
• E.U. Data Protection Directive within ISO/IEC
27001:2005
• Trusted Data Services – Coming Soon

12. Thanks