Cloud Computing For Intelligence And Defense V6

Adapting Cloud Computing for
Intelligence and Defense

Scaling Performance, Managing Power

September 2008

The Fabric of Business www.appistry.com

Defense, Intelligence Community
Mission Drivers
The DoD vision for net-centric operations and warfare:
• Scalable Net-Centric Computing
• Establish processes and an online mechanism for customers to directly
provision a virtual operating environment on demand within minutes
to meet ad hoc, real time warfighter needs.
• Establish a capability for applications to dynamically scale computing
resources up and down on demand to meet traffic loads.
• Enterprise Computing
• Move toward the concept of virtual or grid computing in which
applications will utilize available computing capacity irrespective of
geographic location.

http://www.disa.mil/strategy/

The Fabric of Business 2 www.appistry.com

DoD Information Sharing Strategy

This DoD Strategy establishes the vision for the future:
Deliver the power of information to ensure mission success through an
agile enterprise with freedom of maneuverability across the
information environment.
To achieve the vision, this Strategy describes four goals that form the
necessary environment across the DoD. These goals are: (1) promote,
encourage, and incentivize sharing; (2) achieve an extended enterprise; (3)
strengthen agility in order to accommodate unanticipated partners and
events; and (4) ensure trust across organizations.

John Grimes, DoD CIO
http://www.defenselink.mil/cio-nii/docs/InfoSharingStrategy.pdf


Appistry EAF: Technology
Infrastructure To Enable Sharing
DoD Information Sharing Strategy:

Goals
3) Strengthen agility, in order to accommodate
unanticipated partners and events (scale, surge,
adaptive technologies)
Approaches
2) Forge information mobility (processing of
information)
3) Make information a force multiplier through
sharing (volume, velocity)



Appistry: Enhancing the Information
Sharing Value Chain QOS


Meeting the need

• On-demand infrastructure
• Virtualization
• Cloud computing
• Enabling Scale - Application and Power
• Enabling Mission Resilience and Reliability
• Hiding Development and Operational Complexity
• Minimal Infrastructure Impact


Cloud as Platform: Characteristics

Cloud offers an emerging commercial best
practice for application/service delivery
based on the Google/Amazon model:
• Incrementally scalable
• Agile & adaptive
• Reliable and fault-tolerant
• Programmable
• Virtualized
• Self-managing
• Commodity infrastructure

A “Google-Like” Platform for Applications

Adapting commercial best practices
to Federal

Public Public Clouds
Cloud E.g.
• GoGrid
• Google AppEngine
• Amazon EC2

Enterprise

Adapting commercial best practices
to Federal
Private (Internal) Clouds
• Cloud characteristics
Public
• Behind the firewall
Cloud
• Secure networks
• Data, applications don’t
leave the enterprise
• Leverages existing
External investment in blades,
virtualization
Internal

Private Cloud Private Cloud

Enterprise

Seamless piece of the puzzle

Services and Applications

?
Virtual Machines Virtual
Machines
… Virtual
Machines
Virtual
Machines
… Virtual
Machines

…
Commodity Commodity Commodity
Infrastructure Infrastructure Infrastructure


Cloud Technology Stack

Services and Applications

Appistry EAF: Cloud Application Platform

Virtual Machines Virtual
Machines
… Virtual
Machines
Virtual
Machines
… Virtual
Machines

…
Commodity Commodity Commodity
Infrastructure Infrastructure Infrastructure

No disruption of your existing server and virtualization investments


Cloud Computing In Your Operational
Environment
• Logical extension to your existing, heterogeneous
computing infrastructure
• A quality of service supplement to your existing
heterogeneous infrastructure
• Reduce risk, improve mission availability
• Scale without fail
• Compute within pre-defined time windows
• Correlate power consumption to application workload
• When to deploy to the Cloud Application Framework?
• When applications, key algorithms or SOA services require
the processing power of multiple CPU’s in order to meet
surges in demand and other SLA parameters.

Seamlessly Integrating the Technology

• Appistry Quick Start - 5 well defined steps
• Assign infrastructure to cloud application framework
• Identify services and capabilities that require scale and
reliability quality of service provided by the fabric.
• Add meta data to place services in the cloud
• Use the Appistry libraries to call the services within the
cloud
• Measure performance, adjust infrastructure as required to
meet service level agreements


Appistry Quick Start Enables:

• People
• Train your operations staff to create, deploy and support the cloud
infrastructure; deploy energy management policy
• Train your developers to cloud-enable their applications and call them
• Process
• Adopt procedures for, adding and subtracting infrastructure from the
fabric, determining which applications benefit from the QOS benefits of
the cloud
• Technology
• Retain your current heterogeneous, virtual and physical architecture
• Add meta data to your applications, services or algorithms
• Use Appistry libraries to call cloud enabled Applications and Services


Appistry EAF Architecture

Cloud Dynamic / Distributed Load Balancing
Application
Middleware Process Orchestration Batch Scheduling

Policy Definition & Enforcement
Policy Definition & Enforcement
Management & Monitoring
Management & Monitoring
Deployment & Provisioning
Deployment & Provisioning
Application Java .NET Legacy External
Components POJO PONO (Web) …
Service

Cloud Services
FAM
FAM …
Queues

Cloud
Package Tomcat Apache IIS JBoss Mule …
Management

Self-Organization (Discovery, Availability)

Any Cloud

Solution Value
• Scale Application Performance
• Scale SOA services and existing applications
• Scale applications across multiple CPUs (2-1000’s)
• Logically isolate processing without creating physical stove pipes
• Create Operational Efficiencies
• Achieve QOS of HA (High Availability) solutions on existing commodity infrastructure
• Monitor and control license distribution within the fabric
• Use fabric metadata to dynamically restore high-value capabilities under cyber-attack
• Isolate and pre-provision dynamic COI’s (Communities of interest)
• Hot plug-in of server resources
• Reduce Operational And Program Risk
• Distribute transparently
• Reduce application IOC (Initial Operational Capability) to FOC (Full Operational Capability),
development time , scaling for FOC usually gets in the way
• No need to re-perform security accreditation; applications are cloud-enabled via meta data
• Reduce Power Consumption (Scale Power Utilization)
• Performance based power management, defined by user policy
• Correlate power consumption to data center workload

Scaling SOA
• Improve Mission Availability
• Reducing application down time due to hardware failure
• Completing processing within pre-defined time windows
• Maintain Required Service Availability And Performance
Objectives
• During high demand
• During peak demand
• Unanticipated demand
• Reduce Costs
• Utilizing existing commodity hardware infrastructure
• Streamlining operational processes to deploy based on performance
Leading-edge enterprises looking for advanced platforms to support XTP requirements
should consider grid-based application platforms when their major concern is scale-out
scalability, and nearly 100% availability for transactional and analytical applications
- Gartner -

Compute Intensive Activities

• Image, data compression/decompression
• Encryption/decryption
• Image processing
• Scheduling, logistics planning
• Search
• Matching (data mining, business intelligence)
• Simulation
• Parallel computations (matrix calculations, Fourier
transforms, spectral and signal analysis)
• Pattern recognition


Case Study:
Decreasing development complexity for a high-volume image
processing application

The leading provider of satellite imagery for
Appistry EAF at GeoEye
government and commercial applications,
GeoEye is building its next-generation image
processing applications on Appistry EAF.
Data Process Result
Challenges:
• Multi-core / SMP development complexity
• Risk, cost and agility of traditional platforms
• Meeting customer SLAs
Results:
• Imaging applications now able to process in
excess of 5 TB of satellite imagery per day
• Developers able to focus on core competencies
• Capital savings greater than $1.2 million
• Easily meet customer requirements for
maximum processing time
“ By relying on the application fabric to provide
scalability, reliability and manageability, we can
leave our infrastructure concerns behind and focus
on providing maximum value to our customers. ”
– Ray Helmering,
VP Photogrammetric Engineering at GeoEye


Case Study:
Cloud-Enabled Logistics Solution

Customer:
Leading Transportation Services Provider
Data Process Result Worldwide
• 2+ Million Stops
• 60,000 Employees
• 2,000 Developers

Application:
Mission-critical logistics planning
application

Challenges:
• Bringing strategic application to market quickly
• Supporting existing application code
• Ensuring predictable request execution
Results:
• Application deployed in one day
• Predictably processes all shipments in
required timeframe
• Application to save tens of millions of dollars
per year


Gartner Says
• Appistry in the visionary Magic
Quadrant for Enterprise Application
Servers, 2Q08 - Strengths
• Leading-edge, grid-based application Platform
(Appistry Enterprise Application Fabric (EAF))
targeting transactional and analytical
applications
• High-profile, large scale (more than 400 CPU
cores in one case) and business-critical
deployments in large, Global 2000 class
companies
• Support for .NET and Java environments
• Aggressive “razor and blade” strategy (Appistry
Open distribution) based on free Appistry EAF
use (development, testing and production) and
sales of add-ons for managing large scale
deployments and infrastructure energy savings


Energy Consumption Projections

“50 Percent of Data Centers
Will Have Insufficient Power
and Cooling Capacity by
2008”

“The energy use of the nation’s servers and
data centers in 2006 is estimated to be more
than double the electricity that was consumed
for this purpose in 2000… Under current
efficiency trends, national energy
consumption could nearly double again in
another five years”


Google’s U.S. Data Center Locations
and Placement Criteria

Operating costs drive
Google data centers to the
center of country

• Large volumes of cheap electricity.
• Green energy. Focuses on renewable power sources.
• Proximity to rivers and lakes. They use a large amount of water for cooling
purposes.
• Large areas of land. Allows for more privacy and security.
• The distance to other Google data centers (for fast connections between data
centers).

Power Transmission Geography
Constrains and Dictates Choices

The National Security Agency plans
to put a data center in San Antonio,
Texas - 3rd in the nation for
operational cost efficiency -

U.S. Rep. Charlie Gonzalez
March 2007


Power and Cooling: Mission Critical
Constraint For Intelligence and DoD
NSA electricity crisis gets Senate scrutiny - Baltimore Sun, January, 2007
• NSA expects its power demands to exceed its supply within the next two
years - an issue it has been aware of since the late 1990s. NSA Director Lt.
Gen. Keith B. Alexander has acknowledged the problem
• The NSA’s impending electricity shortfall is quot;sort of a national
catastrophe,quot; Sen. John D. Rockefeller IV, the chairman of the Senate
Intelligence Committee
Power supply still a vexation for the NSA - Baltimore Sun, June, 2007
• Referring to the NSA's power shortage. quot;It got to a point where it became
a serious problem. We're attempting to deal with it now.” Rep. C.A.
Dutch Ruppersberger, Maryland Democrat, House Intelligence
Committee
Trend: BRAC (Base Realignment and Closure) consolidations and physical
security considerations condense data centers into burdened power grids;
NGA, DISA, etc.

Security Need: Disrupt The Trend
Relocating Data Centers Is Not a Sustainable Model

State-of-the- art All measures in “Best practice” scenario, plus: • Aggressively consolidate servers •
Aggressively consolidate storage • Enable power management at data center level of applications,
servers, and equipment for networking and storage
http://www.energystar.gov/ia/partners/prod_development/downloads/EPA_Datacenter_Report_Congress_Final1.pdf


Appistry: Scaling Power Without Fail

Performance-Based Power Management
A user policy based, application-aware approach to
power management ensuring the highest levels of
application performance while minimizing
infrastructure power consumption.

Appistry Energy Saver “In a typical data center,
Correlates power electricity usage hardly varies
consumption to at all, but application load
data center workload varies by a factor of 3x or
more.”
-Rocky Mountain Institute
http://www.govtech.com/gt/312792

Fabric Technology Enables
Performance-Based Power Mgmt
“The chief performance attributes of data
centers - availability, reliability and sheer
horsepower (performance) - are at odds with
Appistry Energy Saver:
the conservation-based assumptions of Decoupling applications
sustainability”
Suggestion 9: When not in use, turn it off from infrastructure:
How to Cut Data Center Energy Consumption, May 2008
Application performance,
reliability ensured by fabric
Utilizes your existing
infrastructure – does not require
a complete hardware refresh
Within user defined policy,
Appistry knows what to turn on
and off, and when


Appistry Energy Saver Scales Power

1. EnergySaver constantly 2. EnergySaver compares current
monitors system system performance to policy
workload targets set by administrator

3. EnergySaver dynamically
adjusts number of active
computers

Application A Application B Application C

Appistry EAF + EnergySaver Result: data center power
consumption correlates to
application workload


Customer Scenario: GeoEye

• New satellite, GeoEye-1, with
unprecedented resolution
Image importance, processing
• Input Process Output

varies based on tasking, The leading provider of satellite imagery
coverage for government and commercial use.

• Appistry EnergySaver will Appistry EAF at GeoEye
reduce number of “on” CPUs
when satellite is looking at
ocean!


Customer Scenario: Clearent

• Fabric-based applications for
authorization (online) and
settlement (batch) Output
Input Process

• Batch settlements have Fast-growing credit-card payment
stringent completion-time processor.
SLAs requiring additional Appistry EAF at Clearent
compute power
• Appistry EnergySaver will
automatically bring on
additional capacity, when
needed


Appistry Customers/Partners


For More

Sam Charrington <sam@appistry.com>
VP Product Management & Marketing
http://www.appistry.com/blogs/sam
http://twitter.com/samcharrington

Dan Wilbricht <dan@appistry.com>
Director of Federal Programs
direct: 703-318-0930


The Green Grid Opportunity
DECREASING DATACENTER AND OTHER IT ENERGY
USAGE PATTERNS

Gartner analysts advise
enterprises to make the
most efficient use of
existing systems with
technologies such as
workload balancing and
virtualization, and to plan
for greener datacenter
designs in the years
ahead.

http://www.thegreengrid.org/gg_content/Green_Grid_Position_WP.pdf


Cloud Computing For Intelligence And Defense V6

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