Speaker: James Staten - VP and Principal Analyst, Forrester Research As a RightScale user you are clearly a leading adopter of cloud computing, but have you matured your use of the cloud to the point that you are fully exploiting the advantages it provides? Most cloud users aren’t. In this session, Forrester Research VP and Principal Analyst James Staten will help you understand how to move from a cloud user to an optimizer to a profit maker as you progress your understanding of cloud economics and evolve your application design and deployment practices.

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The Three Stages of Cloud Adoption
James Staten, Vice President, Principal Analyst

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Scale out turns on the
cloud.
Scaling down turns on cloud
economics.

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The basics of cloud economics are clear
• As demand rises, resources are added.
• Requires apps to scale out
• Load balancing governs
Elastic scale delivers just-in-time capacity.
• No upfront payment
• No commitment whether you use it or not
• Costs aligned to use
Pay-per-use keeps costs low.
• If you can build it, you can deploy it — fast.
• API access drives use of automation.
Self-service fuels productivity.

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Turning cloud economics to your favor is the key
• How quickly can you turn off resources no longer in use?
• How small can you get your base footprint?
• Are you leveraging caching as much as you can?
Elastic scale: Scaling down is key.
• Discrete component scaling drives efficiency.
• Autoscaling cloud services often costs less.
• Where traffic goes affects cost.
What you scale matters.
• Some cloud services have off-peak pricing concepts.
• Some cloud services have better costs for certain services/uses.
When and where you do things matters.

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Three stages of cloud economics

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Leverage the tools of cloud economics
• When you do something
• For how long you do it
Time
• Parts that act independentlyComponentization
• What performs which actions
• What economics it brings
Service choice
• What doesn’t consume storage
• What doesn’t consume bandwidth
Caching
• How the code behaves
• What the code does and how
• Re-architect to activate cloud economics
Code optimization

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How does Netflix use the cloud economics tools?
 Profitability up by cloud optimization
 Three key services
– Movie encoding (movies/watt)
 Batch up encoding processes.
 Not time sensitive; can tap spot instances.
 Optimize storage formats to keep S3 costs low.
– Video streaming service
 Store on S3, stream on multiple CDNs.
– Optimize CDN choice by stream type and customer.
 Split customer login and device identification.
– Log analysis — feeds BI system
 Leverage managed Hadoop from AWS.
 Re-architected BI from the ground up for best
cloud efficiency
Key tools used:
 Time
 Componentization
 Service choice
 Code optimization
For more info, check out http://www.slideshare.net/adrianco/netflix-on-cloud-combined-slides-for-dev-and-ops and
Cloudscaling Blog (http://cloudscaling.com/blog/cloud-computing/cloud-innovators-netflix-strategy-reflects-google-
philosophy).

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NVoicePay taps the cloud to expand its market
AP Assist: Enable electronic payments for SMBs
 90% of B2B invoice payments are still by check.
 Solution: SaaS-based vendor payment
– $0.40 per payment; free vendor sign-up
– Tight integration with key SMB systems (i.e., ADP for car
dealers, First Data payment clearing-house)
 Rich but light client UI — Silverlight
 Needed to push new information to customers quickly
– Needed elastic scalability, fast deploy, and iteration
 Forecasted huge transaction volumes
 Traditional hosting was more expensive — wouldn’t achieve scale.
– Needed reusable cloud services to speed development
 Windows Azure AppFabric, storage, security services
– Needed effectively 100% availability for ―Payment Dial Tone‖
 The alternative was to build a massively expensive data center.
“Building a mission-critical B2B
payment network would have been
nearly impossible without the low
cost, pay-as-you-go . . . Windows
Azure platform.”
— Karla Friede, CEO, NVoicePay
For more info, check out NVoicePay website (http://nvoicepay.com/wp-content/uploads/2010/10/NVoicePay-MS-Case-Study.pdf).

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How is NVoicePay leveraging cloud economics?
 What cloud economics tools are they using?
– Time
– Componentization
– Service choice
– Caching
– Code optimization
For more info, check out NVoicePay website (http://nvoicepay.com/wp-content/uploads/2010/10/NVoicePay-MS-Case-Study.pdf).

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How NVoicePay activates cloud economics
If it’s running, it’s cutting into profitability.
 Profits are pennies on each $0.40 transaction.
 Mission: Lower the cost of each payment.
– Scale only when necessary.
 Scale only what needs to be scaled when necessary.
– Chatter can cost you.
 Traffic flowing out of the cloud costs $$.
 Keep this traffic to a minimum using:
– Caching, Batching, Rich-client actions.
– Use cloud services to speed development.
 Windows Azure AppFabric Service Bus and Access Control
 Windows Azure Blob, Table, and Queue Storage
 Windows Azure Connect — secure extra cloud connectivity
 Silverlight client takes actions that ease cloud-premise
integration.
Key tools used:
 Time
 Componentization
 Service choice
 Caching
For more info, check out NVoicePay website (http://nvoicepay.com/wp-content/uploads/2010/10/NVoicePay-MS-Case-Study.pdf).

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What code are we seeing in the cloud
1: Forklift 2: Elastic 3: Native
Redeploy Apps ―As-
is‖ to the cloud
IAAS: EC2
PAAS: CloudBees,
Engineyard
• Simple
• Quick
• Low- initial cost
• Low elasticity
Load-balance, add
OSS infrastructure
IAAS: EC2
PAAS: Azure
• Let provider
auto-scale
• Some
refactoring
• OPEX savings
Designed with the
Internet as the OS
Service composition
• Facades
• State migrates to
edge of systems
• Designed for failure,
self healing
• Continuous
deployment
~70% ~20% ~10%

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Why traditional applications struggle to run on true
clouds
Cloud Platforms
 Commodity, low HA HW
 Assume all resources will be
shared
 Assume shared use of the
network and no performance SLA
 Can be run anywhere
 And instance can take over
 Are services to other elements
Traditional enterprise
applications
 Assume stable, reliable HW
 Assume sole ownership of the
resource
 Assume uninterrupted network
access
 Assume place
 Assume they are primary
 Have static interrelationships

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App architectures must evolve to exploit scale out
November 2012 “Don’t Move Your Apps To The Cloud ”

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A Digest of Evernote Architecture
 150M HTTP requests via Apache
Thrift based Service API
 Multiple failover points
 90+ shards of Debian/Java/
Tomcat/Hibrnate/Ehcache/
Stripes/GWT/MySQL
 VM images replicated to another
server
 User based sharding reduces noisy
neighbor
 Imaging search indexing service is
separated into different endpoint
 Additional endpoint each have their
own scale
Cloud Native Elements

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What powers Instagram
 0-14M users in year 1
 Ubuntu running on EC2
 AWS Elastic Load Balancer + Route 53 +3 NGINX instances
 Django(Python)+gunicorn for App servers
 Sharded PostgreSQL for Data Storage
 Photos stored to AWS S3
 Cloudfront as CDN for acceleration
 Redis for feeds, Memcache
 Munin for monitoring
Cloud Native Elements

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What powers Linked-in Mobile
 Node.js for high scale asynchronous
eventing to clients
 Mobile server intermediates
between client and LinkedIn
platform
 Screen API (JSON) – Domain API
(Thrift)
 Nginx for higher throughput of
messages
Cloud Native Elements
iOS
JS/HTML +
Native
Android
Native
Mobile Web
JS/HTML
Other
Wrap
JS/HTML
Load Balancer
Nginx Nginx
Node JS
Server
Node JS
Server
LinkedIn Core Platform
Mongo
DB
Logging
Server
Tracking
Server
Screen-based REST API
Domain REST APIMobileServer

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The NPR API architecture
 43M pageviews in 2010 to 88M
– 30M mobile
 Following a COPE strategy
 Appservers, Java, JSP, Struts
 MySQL as data management
layer
 NoSQL XML repo for API
staging
 PHP 5 /Linux in the API
handling layer
 Memcache to accelreate
reponses
Cloud Native Elements

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What about legacy apps?

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Link to the legacy, then cut it loose
Web infrastructure
Legacy

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Recommendations
• How does it generate revenue?
• What actions are taken to get that revenue?
• What components are involved?
• What does the transaction flow cost?
Understand the profitability profile of your cloud service.
• Can you improve its scalability model?
• How can its action timing be improved?
• What alternative means (services, caching, reusable
components) can be leveraged?
Analyze its performance profile.
• Improve cloud coding practices through architectural adherence.
• Architect in how to use the cloud economic tools — not the
specific uses.
• Revisit this process often — as the cloud matures quickly.
Bake the lessons learned into your cloud architecture.

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What’s your cloud use case?
 What defines success for this service?
 What drives its profitability?
 What cloud economics tools are you using today?
 Discussion: How can you use them more
efficiently tomorrow? Cloud tools:
 Time
 Componentization
 Service choice
 Caching
 Code optimization
For more info, check out NVoicePay website (http://nvoicepay.com/wp-content/uploads/2010/10/NVoicePay-MS-Case-Study.pdf).

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Thank you
James Staten
+1 650.581.3824
Twitter: Staten7
www.forrester.com