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Twitter Tag: #briefr The Briefing Room
Reveal the essential characteristics of enterprise software, good and bad
Provide a forum for detailed analysis of today’s innovative technologies
Give vendors a chance to explain their product to savvy analysts
Allow audience members to pose serious questions... and get answers!
Mission
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Topics
August: REAL-TIME DATA
September: HADOOP 2.0
October: DATA MANAGEMENT
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The Value of Future-Proofing
Ø Storm is hot
Ø Spark is hotter
Ø More innovation coming
Ø But keep in mind the latency
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Analyst: Robin Bloor
Robin Bloor is Chief Analyst at The Bloor Group
[email protected] @robinbloor
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Impetus
Founded in 1991, Impetus offers a variety of products and services across the big data ecosystem
StreamAnalytix is its open source real-time streaming capability for big data analytics
The platform leverages multiple Apache components, including YARN, Spark, Storm and Kafka
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Guest: Anand Venugopal
Anand Venugopal Product Head - StreamAnalytix, Impetus Technologies Anand Venugopal has been working with Fortune 1000 enterprises to deliver real business benefits and ROI from Big Data Solutions at Impetus. He has been helping IT and line-of-business executives in large enterprises understand and extract the enormous value embedded in their static and "in-motion" Big-Data assets. Before Impetus, since 1995 – Anand has been in techno-business evangelism roles in various industries including telecom, gaming, media and entertainment and hi-tech.
© 2015 Impetus Technologies - Confidential 10
Webinar: Future-Proof Your Streaming Analytics Architecture
Robin Bloor, Principal Analyst
Aug 25, 2015
Twitter: @
Anand Venugopal, Product Head -‐ StreamAnaly3x Twi8er: @streamanaly3x
© 2015 Impetus Technologies - Confidential 11
IMPETUS INTRODUCTION
Mission critical technology
solutions since 1996
Global Leaders are our Big Data clients
1600 people – US, India,
Global reach
Unique mix of Big Data
products and Services
© 2015 Impetus Technologies - Confidential 12
REAL-TIME STREAMING ANALYTICS PLATFORM
Why ?
Build vs. Buy ?
What to buy ?
From whom to buy ?
How to Integrate ?
© 2015 Impetus Technologies - Confidential 13
TOPICS COVERED TODAY
Business need for streaming
analytics
Industry verticals and
use cases Architecture
Streaming platform options
StreamAnalytix approach and
benefits
Some announcements!
© 2015 Impetus Technologies - Confidential 14
WHY STREAMING ANALYTICS ?
Because it is now possible! Batch
only is old
Customer Experience
Operational Intelligence
© 2015 Impetus Technologies - Confidential 15
WHY ? à BATCH VS. REAL-TIME BUSINESS PROCESS
SENSE Days ANALYSE Weeks ACT
SENSE ANALYSE ACT
Sec/ ms
Batch
Real time
Sec/ ms
© 2015 Impetus Technologies - Confidential 16
WHY ? à CONTEXT AWARE: POSITIVE CUSTOMER EXPERIENCE
Multi-channel engagement in
real-time
Context Sensitive service
Happy customers, Loyalty, Revenue,
Profits, Growth
© 2015 Impetus Technologies - Confidential 17
TYPICAL USE CASES FOR STREAMING ANALYTICS
• Predictive Maintenance • Clinical care and patient management • Sensor analytics • Fleet operations • Fraud and anomaly detection • Gaming • Churn Analytics • Network traffic analysis and optimization • Internet Advertising
Verticals
• Customer experience • Clickstream Analytics • Context-sensitive offers and recommendations • IT Log analytics • Security
Horizontals
• Internet of Things • Mobile app analytics • Call Center Monitoring and Analytics
Combo
© 2015 Impetus Technologies - Confidential 18
BUILD Vs BUY ?
• Needs time, skills, budget
• Upfront costs and long term maintenance costs
• Total flexibility and control
• Do you have the time to wait ?
Build
Vs
Buy
• Are ready options available that meet your needs ?
• Selection Criteria ? (Show Thumbnail of Ten considerations white paper)
© 2015 Impetus Technologies - Confidential 20
t
now
Hadoop works great back here RT-Ax works here
BLENDED VIEW – HISTORICAL AND NOW
Blended view Blended view Blended View
© 2015 Impetus Technologies - Confidential 21
LAMBDA ARCHITECTURE : BIG AND FAST DATA COMBINED
Batch Layer
All data Pre-computed information
Batch re-compute
Speed Layer
All data Pre-computed information
Real time increment
Batch view
Serving Layer
Batch view
Mer
ge
Real time view
Real time view
All Incoming
Data Query
© 2015 Impetus Technologies - Confidential 22
AN INTEGRATED APPROACH BLENDING CURRENT AND NEXT GENERATION TECH
Landing and ingestion
Structured
Unstructured
External Social
Machine Geospatial
Time Series
Streaming
Provisioning, Workflow, Monitoring and Security
Enterprise
Data Lake
Predictive applications
Exploration & discovery
Enterprise applications
Real-Time applications
Traditional
data repositories
RDBMS MPP
Compliance, Governance, Information Lifecycle, Data Lineage, Enterprise Meta Data Management
© 2015 Impetus Technologies - Confidential 23
Streaming Platform Options and StreamAnalytix approach
© 2015 Impetus Technologies - Confidential 24
“DEFAULT” APPROACHES TO STREAMING ANALYTICS
• No leverage of open source • Vendor lock-in • Could be high cost • Limited flexibility
Proprietary Platforms
• Native Open source • No Vendor Support • Integration & maintenance
nightmare • Significant delays in time-to-market
“Do it yourself”
© 2015 Impetus Technologies - Confidential 25
THE 3RD APPROACH: BEST OF BOTH WORLDS
StreamAnalytix mitigates the disadvantages of the "default" approaches and offers the benefits of both worlds to enterprises for streaming analytics.
Abstraction of functional components like Ingest, CEP, Analytics, Visualization
© 2015 Impetus Technologies - Confidential 26
StreamAnalytix – GIVES YOU A FUTURE PROOF OPTION
STORM SPARK OTHERS
NOW
Time
© 2015 Impetus Technologies - Confidential 27
Future proof – Enterprise Grade – Open source based – Streaming Analytics platform
NEXT
Unified Business Interfaces Common Utilities Smart Workflows
© 2015 Impetus Technologies - Confidential 32
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported Ingest Channels
© 2015 Impetus Technologies - Confidential 33
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported Processors
© 2015 Impetus Technologies - Confidential 34
SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported Emi8ers/ Output Channels
© 2015 Impetus Technologies - Confidential 35
CUSTOM CODE DEVELOPMENT/INTEGRATION
Download Sample Project
Custom Java Component Development
Reuse Exis3ng Storm Bolt Code
© 2015 Impetus Technologies - Confidential 36
UPLOADING WORKFLOW
Configurable Workflow Upload (Ac3vi3 BPM support )
© 2015 Impetus Technologies - Confidential 40
FROM WHOM TO BUY ? IMPETUS
?
Right size Independent Services
Track record of Long term partnerships and value
Recent success stories
© 2015 Impetus Technologies - Confidential 42
HOSTED CALL CENTER SOLUTION
• Call “Stitching” in real-time
• IVR dominant path analytics
• Analyze behaviour of Call Centre infrastructure
• Business driven SLA based alerts in real-time
• Historical reports for future pricing models
• Trace complete call flow
• Advanced Search on Call facets
• Sentiments and alerts on email/chat conversations
• Individual events scattered in different media servers.
• Change the SLA alert definition and apply new definition in real-time without restart.
• Sequence of events to be maintained at processing, storage and query level.
• Media server logs contains only 1% of data which is relevant. Platform should have capability to filter the data at source level.
Key Features
Challenges Solved
© 2015 Impetus Technologies - Confidential 46
ACCESS FREE VERSION OF STREAMANALYTIX
StreamAnalytix Lite
A production-ready version of StreamAnalytix for Developers to use a powerful visual tool-kit for developing real-time streaming analytics applications free of cost. • Limited Functionality • Unlimited Scale • Free for ever
StreamAnalytix Developer Fully functional version of 'StreamAnalytix Enterprise' for Developers to quickly try out all the platform features by putting all their data at work to uncover new insights. • Full Functionality • Restriction on scale • Free for 1 year
Enterprise Trial Fully loaded version of StreamAnalytix with a rich set of advanced visualization tools to easily develop & analyze real-life enterprise applications with minimal coding.
• Full Functionality • Unlimited Scalability • 60 days trial
For more details visit at http://streamanalytix.com/download
Platform Editions
© 2015 Impetus Technologies - Confidential 56
Thank you. Questions? ?
[email protected] www.StreamAnalytix.com
Contact us for an On-premise OR Cloud based trial and/or Proof of concept
Meet us at Strata Hadoop World in New York in September
The Biological Analog
u Our human control system works at different speeds: • Internal systems – enteric nervous system • Instant external reflex – spinal cord • Fast external response – motor systems • Considered response – the brain
u Swift external response is predictive analytics & triggers
u Considered response is analytics
Then Spark Disrupts Hadoop
u Spark has become the de facto vehicle for many distinct Hadoop projects because of its in-memory scale-out capability
u It can do streaming to a degree, but it is not ideal for very low latency applications
u For that you need to scale-up, not out, and a high level of optimization is necessary
u Nevertheless, it has its place
Spark and Storm
u Along with Spark comes with Shark (a Hive-compatible version of Spark)
u Storm provides batch and streaming (event processing capabilities) concurrently via the lambda architecture
u Lambda: batch layer, serving layer, speed layer
u Spark now also has lambda architecture and can thus behave in a similar manner
u Spark currently seems to be more fashionable
u There’s clearly a trend to low latency analytics. How do you see this developing?
u Aside from predictive analytics and typical CEP applications, are there any other application areas that you are encountering?
u Please describe a typical implementation, from adoption through development to implementation.
u How much integration work is necessary?
u What is your current largest customer in terms of streaming volume, and what is the application?
u Do you find yourselves competing directly with Spark or Storm?
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Upcoming Topics
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August: REAL-TIME DATA
September: HADOOP 2.0
October: DATA MANAGEMENT