Ahead of the Stream: How to Future-Proof Real-Time Analytics

Grab some
coffee and
enjoy the
pre-show
banter
before the
top of the
hour!

The Briefing Room
Ahead of the Stream: How to Future-Proof Real-Time Analytics

Twitter Tag: #briefr The Briefing Room
Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh

  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

Topics
August: REAL-TIME DATA
September: HADOOP 2.0
October: DATA MANAGEMENT

The Value of Future-Proofing
Ø  Storm is hot
Ø  Spark is hotter
Ø  More innovation
coming
Ø  But keep in mind the
latency

Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bloorgroup.com
@robinbloor

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

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 - Confidential10
Webinar: Future-Proof Your Streaming Analytics Architecture
Robin Bloor,
Principal Analyst
Aug 25, 2015
Twitter: @
Anand Venugopal,
Product
Head
-‐
StreamAnaly3x

Twi8er:
@streamanaly3x

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

REAL-TIME STREAMING ANALYTICS PLATFORM
Why ?
Build vs.
Buy ?
What to
buy ?
From whom
to buy ?
How to
Integrate ?

TOPICS COVERED TODAY
Business need
for streaming
analytics
Industry
verticals and
use cases
Architecture
Streaming
platform options
StreamAnalytix
approach and
benefits
Some
announcements!

WHY STREAMING ANALYTICS ?
Because it is now
possible! Batch
only is old
Customer
Experience
Operational
Intelligence

WHY ? à BATCH VS. REAL-TIME BUSINESS PROCESS
SENSE Days ANALYSE Weeks ACT
SENSE ANALYSE ACT
Sec/ ms
Batch
Real time
Sec/ ms

WHY ? à CONTEXT AWARE: POSITIVE CUSTOMER EXPERIENCE
Multi-channel
engagement in
real-time
Context
Sensitive service
Happy customers,
Loyalty, Revenue,
Profits, Growth

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

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)

Architecture Considerations

t
now
Hadoop works great back here RT-Ax works
here
BLENDED VIEW – HISTORICAL AND NOW
Blended viewBlended viewBlended View

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
Merge
Real time view
Real time view
All
Incoming
Data Query

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

Streaming Platform Options
and StreamAnalytix approach

“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”

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

StreamAnalytix – GIVES YOU A FUTURE PROOF OPTION
STORM SPARK OTHERS
NOW
Time

Future proof – Enterprise Grade – Open source based – Streaming Analytics platform
NEXT
Unified Business Interfaces Common Utilities Smart Workflows

StreamAnalytix Screenshots

CONFIGURABLE MESSAGE DEFINITION

CONFIGURATION FIELD DEFINITION

CONFIGURABLE ALERT DEFINITION

SAMPLE DATA PIPELINE (USING DATAFABRIC )
Supported
Ingest
Channels

Supported
Processors

Supported
Emi8ers/

Output
Channels

CUSTOM CODE DEVELOPMENT/INTEGRATION
Download

Sample

Project

Custom
Java
Component

Development

Reuse
Exis3ng
Storm
Bolt
Code

UPLOADING WORKFLOW
Conﬁgurable
Workﬂow
Upload

(Ac3vi3
BPM
support
)

MONITORING A PIPELINE

DASHBOARD (SAMPLE)

USER MANAGEMENT

FROM WHOM TO BUY ? IMPETUS
?

Right
size
Independent
Services

Track
record

of
Long
term

partnerships

and
value

Recent

success
stories

Call Center Solution

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

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

Log Monitoring App

LOG-MONITORING DASHBOARD

SYSTEM MONITORING(CPU,MEM,DISK)

SEARCH

Real Time Social Media Analytics

CREATING NEW SEARCH FROM DATA SOURCE

REAL-TIME SENTIMENTS AND CLASSIFICATION

REAL-TIME TOPIC CATEGORIZATION

Thank you.
Questions??
inquiry@streamanalytix.com
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

Perceptions & Questions
Analyst:
Robin Bloor

Of Lakes and Streams
Robin Bloor, PhD

The Division
Analytics and streaming analytics
are not at all the same

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

My Current View
Streaming is more about DATA/
SOFTWARE ARCHITECTURE than
anything else

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?

Upcoming Topics
www.insideanalysis.com
August: REAL-TIME DATA
September: HADOOP 2.0
October: DATA MANAGEMENT

THANK YOU
for your
ATTENTION!
Some images provided courtesy of Wikimedia Commons
and http://arapisacz.blogspot.com/2009/10/floating-house-from-brad-pitt.html

Ahead of the Stream: How to Future-Proof Real-Time Analytics

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