©	
  2015	
  Splunk	
  Inc.
Real	
  World	
  Big	
  Data	
  
Architecture	
  –
Splunk,	
  Hadoop,	
  RDBMS
Naman	
  Joshi	
  – Snr Sales	
  Engineer	
  
Disclaimer
2
During	
  the	
  course	
  of	
  this	
  presentation,	
  we	
  may	
  make	
  forward	
  looking	
  statements	
  regarding	
  future	
  
events	
  or	
  the	
  expected	
  performance	
  of	
  the	
  company.	
  We	
  caution	
  you	
  that	
  such	
  statements	
  reflect	
  our	
  
current	
  expectations	
  and	
  estimates	
  based	
  on	
  factors	
  currently	
  known	
  to	
  us	
  and	
  that	
  actual	
  events	
  or	
  
results	
  could	
  differ	
  materially.	
  For	
  important	
  factors	
  that	
  may	
  cause	
  actual	
  results	
  to	
  differ	
  from	
  those	
  
contained	
  in	
  our	
  forward-­‐looking	
  statements,	
  please	
  review	
  our	
  filings	
  with	
  the	
  SEC.	
  The	
  forward-­‐looking	
  
statements	
  made	
  in	
  the	
  this	
  presentation	
  are	
  being	
  made	
  as	
  of	
  the	
  time	
  and	
  date	
  of	
  its	
  live	
  presentation.	
  
If	
  reviewed	
  after	
  its	
  live	
  presentation,	
  this	
  presentation	
  may	
  not	
  contain	
  current	
  or	
  accurate	
  information.	
  
We	
  do	
  not	
  assume	
  any	
  obligation	
  to	
  update	
  any	
  forward	
  looking	
  statements	
  we	
  may	
  make.	
  
In	
  addition,	
  any	
  information	
  about	
  our	
  roadmap	
  outlines	
  our	
  general	
  product	
  direction	
  and	
  is	
  subject	
  to	
  
change	
  at	
  any	
  time	
  without	
  notice.	
  It	
  is	
  for	
  informational	
  purposes	
  only	
  and	
  shall	
  not,	
  be	
  incorporated	
  
into	
  any	
  contract	
  or	
  other	
  commitment.	
  Splunk	
  undertakes	
  no	
  obligation	
  either	
  to	
  develop	
  the	
  features	
  
or	
  functionality	
  described	
  or	
  to	
  include	
  any	
  such	
  feature	
  or	
  functionality	
  in	
  a	
  future	
  release.
Agenda
Splunk	
  Big	
  Data	
  Architecture
Alternative	
  Open	
  Source	
  Approach
Real-­‐World	
  Customer	
  Architecture
Discussion
Q/A
(Demo)
Who’s	
  This	
  Dude?
Naman	
  Joshi
nbjoshi@splunk.com
Senior	
  Sales	
  Engineer
• Splunk	
  user	
  since	
  2008
• Started	
  with	
  Splunk	
  in	
  Feb	
  2014
• Former	
  Splunk	
  customer	
  in	
  the	
  Financial	
  Services	
  Industry
• Big	
  Data	
  Subject	
  Matter	
  Expert
Big	
  Data	
  Technologies
5
6
Splunk	
  Scalability
7
Splunk	
  Real-­‐Time	
  Analytics
8
Hunk	
  – Analytics	
  Platform	
  for	
  Hadoop
9
HUNK	
  Unique	
  Features
10
HUNK	
  Provides	
  Self-­‐Service	
  Analytics	
  For	
  Hadoop
11
HUNK	
  Provides	
  Self-­‐Service	
  Analytics	
  For	
  Hadoop
Enterprise	
  Architect
• Adapt	
  your	
  architecture	
  for	
  big	
  data
• Hadoop	
  shared-­‐service	
  departments	
  
offer	
  self-­‐service	
  analytics
• Data	
  scientists	
  can	
  focus	
  on	
  custom	
  
analytics,	
  not	
  be	
  data	
  butlers
Business	
  Analyst Developer
• Save	
  time	
  by	
  just	
  pointing	
  at	
  Hadoop	
  
• Avoid	
  fixed-­‐schemas	
  and	
  low-­‐level	
  tooling
• Answer	
  questions	
  iteratively	
  without	
  
waiting	
  for	
  MapReduce	
  jobs	
  to	
  finish	
  
• Build	
  scalable	
  big	
  data	
  apps	
  on	
  top	
  
of	
  data	
  in	
  Hadoop
• Use	
  the	
  development	
  languages	
  
and	
  tools	
  you	
  know	
  and	
  like
Pivot
Data	
  
Model
Development	
  
Environment
Interactive	
  
Search
12
What	
  about	
  Structured	
  Data?
13
Use	
  Cases	
  for	
  Structured	
  Data	
  in	
  Splunk
14
Machine	
  Data	
  – Delivers	
  Real-­‐time	
  insights
15
Structured	
  Data	
  – Contains	
  Business	
  Context
16
Splunk	
  DB	
  Connect
17
Case	
  Study	
  –
Open	
  Source	
  Alternative
Hadoop	
  Ecosystem	
  Options
19
Hadoop	
  Advantage/Disadvantage
20
Easy	
  storage	
  but	
  hard	
  analytics:	
  
difficult	
  to	
  explore,	
  analyze,	
  
visualize
Complex	
  technology:	
  many	
  open	
  
source	
  projects
Hard-­‐to-­‐staff	
  skills:	
  must	
  write	
  
MapReduce	
  jobs	
  or	
  fixed	
  schemas	
  
21
Hadoop	
  
(MapReduce	
  
&	
  HDFS)
YARN
DataFu
H
i
v
e
Mahout Pig
Sqoop
Wide	
  Range	
  of	
  Open	
  Source
Projects	
  for	
  Hadoop	
  Analytics
Azkaban
Getting	
  Value	
  from	
  Hadoop	
  Data	
  is	
  Challenging
What	
  Does	
  Gartner	
  Say?
22
TROUGH  OF  
DISILLUSIONMENT
TECHNOLOGY  
TRIGGER
PEAK  OF  
INFLATED  
EXPECTATIONS
SLOPE  OF  
ENLIGHTENMENT
PLATEAU  OF  
PRODUCTIVITY
VISIBILITY
TIME
My	
  most	
  advanced	
  Hadoop	
  clients	
  are	
  also	
  getting	
  
disillusioned	
   …	
  The	
  only	
  consistent	
  success,	
  reported	
  by	
  
my	
  clients,	
  is	
  with	
  Splunk.
Svetlana	
  Sicular,	
  Gartner	
  Research	
  Director,	
  January	
  22,	
  2013
“ “
Many  
Hadoop  
customers
22
Case	
  Study	
  –
Real	
  World	
  Architecture
Summary	
  Architecture
24
Splunk	
  Deployment	
  Architecture
25
Hadoop	
  Architecture
26
Splunk	
  +	
  HUNK	
  =	
  All	
  The	
  Data
27
DB	
  Connect	
  Architecture
28
Summary	
  Architecture
29
Discussion
©	
  2015	
  Splunk	
  Inc.
Thank	
  You
www.splunk.com/bigdata

SplunkSummit 2015 - Real World Big Data Architecture

  • 1.
    ©  2015  Splunk  Inc. Real  World  Big  Data   Architecture  – Splunk,  Hadoop,  RDBMS Naman  Joshi  – Snr Sales  Engineer  
  • 2.
    Disclaimer 2 During  the  course  of  this  presentation,  we  may  make  forward  looking  statements  regarding  future   events  or  the  expected  performance  of  the  company.  We  caution  you  that  such  statements  reflect  our   current  expectations  and  estimates  based  on  factors  currently  known  to  us  and  that  actual  events  or   results  could  differ  materially.  For  important  factors  that  may  cause  actual  results  to  differ  from  those   contained  in  our  forward-­‐looking  statements,  please  review  our  filings  with  the  SEC.  The  forward-­‐looking   statements  made  in  the  this  presentation  are  being  made  as  of  the  time  and  date  of  its  live  presentation.   If  reviewed  after  its  live  presentation,  this  presentation  may  not  contain  current  or  accurate  information.   We  do  not  assume  any  obligation  to  update  any  forward  looking  statements  we  may  make.   In  addition,  any  information  about  our  roadmap  outlines  our  general  product  direction  and  is  subject  to   change  at  any  time  without  notice.  It  is  for  informational  purposes  only  and  shall  not,  be  incorporated   into  any  contract  or  other  commitment.  Splunk  undertakes  no  obligation  either  to  develop  the  features   or  functionality  described  or  to  include  any  such  feature  or  functionality  in  a  future  release.
  • 3.
    Agenda Splunk  Big  Data  Architecture Alternative  Open  Source  Approach Real-­‐World  Customer  Architecture Discussion Q/A (Demo)
  • 4.
    Who’s  This  Dude? Naman  Joshi nbjoshi@splunk.com Senior  Sales  Engineer • Splunk  user  since  2008 • Started  with  Splunk  in  Feb  2014 • Former  Splunk  customer  in  the  Financial  Services  Industry • Big  Data  Subject  Matter  Expert
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
    Hunk  – Analytics  Platform  for  Hadoop 9
  • 10.
  • 11.
    HUNK  Provides  Self-­‐Service  Analytics  For  Hadoop 11
  • 12.
    HUNK  Provides  Self-­‐Service  Analytics  For  Hadoop Enterprise  Architect • Adapt  your  architecture  for  big  data • Hadoop  shared-­‐service  departments   offer  self-­‐service  analytics • Data  scientists  can  focus  on  custom   analytics,  not  be  data  butlers Business  Analyst Developer • Save  time  by  just  pointing  at  Hadoop   • Avoid  fixed-­‐schemas  and  low-­‐level  tooling • Answer  questions  iteratively  without   waiting  for  MapReduce  jobs  to  finish   • Build  scalable  big  data  apps  on  top   of  data  in  Hadoop • Use  the  development  languages   and  tools  you  know  and  like Pivot Data   Model Development   Environment Interactive   Search 12
  • 13.
  • 14.
    Use  Cases  for  Structured  Data  in  Splunk 14
  • 15.
    Machine  Data  –Delivers  Real-­‐time  insights 15
  • 16.
    Structured  Data  –Contains  Business  Context 16
  • 17.
  • 18.
    Case  Study  – Open  Source  Alternative
  • 19.
  • 20.
  • 21.
    Easy  storage  but  hard  analytics:   difficult  to  explore,  analyze,   visualize Complex  technology:  many  open   source  projects Hard-­‐to-­‐staff  skills:  must  write   MapReduce  jobs  or  fixed  schemas   21 Hadoop   (MapReduce   &  HDFS) YARN DataFu H i v e Mahout Pig Sqoop Wide  Range  of  Open  Source Projects  for  Hadoop  Analytics Azkaban Getting  Value  from  Hadoop  Data  is  Challenging
  • 22.
    What  Does  Gartner  Say? 22 TROUGH  OF   DISILLUSIONMENT TECHNOLOGY   TRIGGER PEAK  OF   INFLATED   EXPECTATIONS SLOPE  OF   ENLIGHTENMENT PLATEAU  OF   PRODUCTIVITY VISIBILITY TIME My  most  advanced  Hadoop  clients  are  also  getting   disillusioned   …  The  only  consistent  success,  reported  by   my  clients,  is  with  Splunk. Svetlana  Sicular,  Gartner  Research  Director,  January  22,  2013 “ “ Many   Hadoop   customers 22
  • 23.
    Case  Study  – Real  World  Architecture
  • 24.
  • 25.
  • 26.
  • 27.
    Splunk  +  HUNK  =  All  The  Data 27
  • 28.
  • 29.
  • 30.
  • 31.
    ©  2015  Splunk  Inc. Thank  You www.splunk.com/bigdata