Our Keynote presentation at Gartner Catalyst

1. Secure Big Data Analytics
Combining APIs, Security and Big Data
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Data Center Software Division
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2. Two Red Hot Trends - How do they Intersect?
API Management Big Data Analytics
• Enterprise extending reach • Increased Volume, Variety,
?
through APIs Velocity of unstructured data
• API traffic overtaking web traffic • Drivers: mobile, cloud, social
• Defacto communication for • Tremendous ROI
mobile to server
How does this effect application architecture to support growth?
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3. Big Data Fundamentals
Traditional Data Analysis Big Data Analysis
Unstructured Cluster
Relational Data Analyze
Database Warehouse Organize
Analyze
Transaction Batch Streaming
Devices (MapReduce)
• Structured data • Unstructured, variety of data: “mashup”
• Data ~ GBs to TBs • Data ~ TBs to PBs
• Centralized: Data moves to analytics • Distributed: Analytics move to the data
• Batch analytics • Streaming analytics
Focus ventures in one of two “Only business model tech has left”
areas: monetization of data or
infrastructure to enable
monetization of data March 12, 2012
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4. Today’s Big Data Tools & Hurdles
New BI Tools
“Big Data” includes tools like Hadoop, NOSQL technologies,
massive parallel processing, and in-memory databases
Existing Hurdles with Hadoop
• Job Control - Enable clients to run jobs with security controls
• Data On-ramping - Get data into Hadoop for processing, from internal
sources, cloud services or network-connected devices
• Data Off-ramping - Data availability to clients via APIs, suitable for
mobile applications
• Security and Compliance - Big Data processing provides PII protection,
data security and PCI compliance
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5. Connecting Data Movement:
Back End to Device to ALL Departments
1 Problem: Today’s platforms are 2 Problem: Data and Potential value
fragmented and not securely locked in fragmented solutions inhibit
connected, limiting scale E2E analytics
Dept Dept Dept Dept Dept Dept Dept Dept
A B A B A B A B
Retail platform Home Energy Platform Telco Service Provider Smart City
10k devices, 1M customers 300K home pilot in Germany Real-time CDR: 12TB/ day 3000+ cameras, 1PB/3mo
API Control Point
Analytics
Edge Devices
NB/ULT Phone Cameras Kiosk PoS DS API Control Point
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6. API/Service Gateway Fundamentals
Service API Data
Mediation Management Transformation
• Consistent policy enforcement
for API CENTRALIZED across Service Gateway
Central Proxy
departments Enterprise
• Use Models: CSB, ESB-light,
Edge Security, API Gateway
Monetization/Charge Back App Service Gov & Integration Security, Access, Compliance Developer Community
• Meter usage • API management • Edge threat protection • Configuration not code
• Throttle per SLAs • Policy creation & exe • Data Loss Protection • Discovery of aggregated
• API Analytics • Legacy & SOA integration • Federated ID Brokering services from IT
• Orchestrate & transform • PCI PII Data Tokenization • Meta data
• Protocol translation
Move from Line of Business to “Enterprise” Wide
6 API Mgt & Utilization of Analytics

7. Last Mile Device Mobile Middleware
• High Performance
• Version Management
• Content Optimization
• Quality of Service
• Ubiquitous Compatibility
• External Cloud Service Support
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8. Information Greed
• Greedy Users: Instant response from
touch-screens, context aware smart
phones, etc
• Greedy Business: Expect real time
intelligence on the consumer derived
from social, data warehouses, and
data mining
Addressing this greed requires new thinking for how to build Composite Applications
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9. Composite Distributed Application Apps
• Hybridized – New functionality with legacy code and data
• Location Independent- 1-n clouds (private and public) and
datacenters simultaneously
• Knowledge Complete - Access to disparate “Big Data” warehouses owned by the business
• Contextual – Produces just-in-time results based on client context, e.g. identity and location
• Accessible & Performs – Produces data compatible with any client on any operating system,
and does it instantaneously
• Secure and Compliant - Meets compliance and security requirements for data in transit and
data at rest
Realizing composite apps can be done with a service gateway, which secures, brokers and
mediates data for API access, and a Hadoop Cluster which provides data analysis and processing
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10. “APIfication” of real-time Hadoop datasets
PaaS Services
Internal Client (Storage, RDMS)
Users
HTTP/REST
Smartphone interactions with Network-
& JSON Results Connected
Tablet Clients Devices
Partner Web
Services
Data On-ramping from the cloud with
Types of Clients selective protection (FPE/Tokenization)
Service Gateway
Gateway Control Point
DMZ
Hadoop API
Job Scheduler
Legacy Apps and RDBMS IDM
Web Services
Metadata Server
Existing Apps, Data and
Infrastructure
Node1 Node2 Node3
HDFS
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11. Pulling it all Together: Ref Arch for Composite Apps
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12. Field Case Study
Secure ‘Big Data’ Storage and REST API
• Authenticate IP cameras based on IP address, 2-way
SSL or message security
• Codeless insertion and retrieval to and from HBase.
Drag and drop with no Java coding
• Expose ‘Big Data’ using a REST facade, ideal for
native mobile applications and partner services
• Provide a secure REST API with authentication and
authorization based on OAuth and internal identity
stores such as LDAP
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13. Suggested Roadmap to Composite Apps & Big Data
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14. More: www.cloudsecurity.intel.com
Gartner Cloud Service Broker API Patterns Secure Big Data
Hype Cycle White Paper Solution Brief
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