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Copyright © 2014 Splunk Inc. Peter Zadrozny Adjunct Professor San José State University Teaching Splunk in the University Classroom

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Page 1: Teaching*Splunk*in* the*University* Classroom* · 2017-10-13 · Disclaimer* 2 During*the*course*of*this*presentaon,*we*may*make*forwardLlooking*statements*regarding*future*events*or*the*

Copyright  ©  2014  Splunk  Inc.  

Peter  Zadrozny  Adjunct  Professor  San  José  State  University  

Teaching  Splunk  in  the  University  Classroom  

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Disclaimer  

2  

During  the  course  of  this  presentaIon,  we  may  make  forward-­‐looking  statements  regarding  future  events  or  the  expected  performance  of  the  company.  We  cauIon  you  that  such  statements  reflect  our  current  expectaIons  and  

esImates  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  presentaIon  are  being  made  as  of  the  Ime  and  date  of  its  live  presentaIon.  If  reviewed  aUer  its  live  presentaIon,  this  presentaIon  may  not  contain  current  or  accurate  informaIon.  We  do  not  assume  any  obligaIon  to  update  any  forward-­‐looking  statements  we  may  make.  In  addiIon,  any  informaIon  about  our  roadmap  outlines  our  general  product  direcIon  and  is  subject  to  change  at  any  Ime  without  noIce.  It  is  for  informaIonal  purposes  only,  and  shall  not  be  incorporated  into  any  contract  or  other  commitment.  Splunk  undertakes  no  obligaIon  either  to  develop  the  features  or  funcIonality  described  or  to  

include  any  such  feature  or  funcIonality  in  a  future  release.  

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About  Me  

!   CTO/Founder,  Opallios  –  ConsulIng  on  Big  Data,  Performance  

Engineering  and  SoUware  Architecture  

!   Professional  Highlights    –  Started  operaIons  of  WebLogic  in  

Europe  –  Started  operaIons  of  Sun  

Microsystems  in  Mexico  

 3  

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IntroducIon  

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History  

5  

!   Undergraduate  elecIve  from  the  Computer  Science  Department  at  San  Jose  State  University  –  Category:  CS  185C  Advanced  PracIcal  CompuIng  Topics  –  Course:  IntroducIon  to  Big  Data  AnalyIcs  

!   80%  of  the  students  are  from  the  Master  in  Computer  Science  program  –  Qualifies  as  a  graduate  program  elecIve  course  

!   Course  first  taught  on  Fall  2012  !   RegistraIon  limited  to  30  students  

–  First  elecIve  in  the  CS  Department  to  have  a  waiIng  list  

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Course  ObjecIve  

6  

!   Focus  on  creaIng  “Data  Wranglers”  –  They  know  how  to  “massage”  data  –  They  know  which  tool  is  best  for  the  problem  at  hand  –  They  know  how  to  install  these  tools  and  to  manage  them  –  They  know  how  to  use  them  to  do  the  required  analysis  

!   Data  Wranglers  are  paired  with  domain  experts  –  To  achieve  ideal  synergies  for  a  comprehensive  analysis  

!   The  course  was  designed  with  the  employer  in  mind  !   We  consulted  with  a  bunch  of  companies:  

–  Preference  given  to  job  candidates  that  have  gone  through  the  worst  of  the  learning  curve  of  big  data  technologies  

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Course  ObjecIve  

7  

!   The  course  is  focused  on  geing  a  pracIcal  understanding  of  the  most  popular  tools  and  technologies  that  allow  to  process  and  analyze  big  data  –  Hadoop  &  Hive  –  Splunk  

!   They  learn  how  to  use  these  tools  through  exercises  and  real  projects  on  a  real  cloud  –  No  quizzes  or  exams  

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Course  ObjecIve  

8  

!   The  course  is  fully  supported  by  

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Course  OrganizaIon  

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Requirements  

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!   For  Splunk  –  None  

!   For  Hadoop  &  Hive  –  Data  Structures  and  Algorithms  

ê  They  need  to  know  the  basics  of  programming  –  Data  Base  Management  Systems  

ê  Experience  with  SQL  is  required  

!   For  the  cloud  services  –  Unix  system  administraIon  experience  

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Semester  Structure  

11  

!   Three  general  lectures  –  IntroducIon  –  Methodology  for  Big  Data  Projects  

ê  Used  for  grading  the  projects  –  Use  and  rules  of  the  GoGrid  cloud  services  

!   13  lectures  for  Hadoop  and  Hive  –  Start  with  this  because  it’s  substanIally  more  difficult  –  Academic  work  load  is  less  at  the  beginning  of  the  semester  

!   13  lectures  for  Splunk  !   At  least  three  guest  speakers  throughout  the  semester  

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Course  Work  

12  

!   One  individual  lab  –  Set  up  a  high  availability  Splunk  cluster  in  the  GoGrid  cloud  

ê  1  master  ê  1  search  head  ê  3  indexers  ê  3  forwarders  

–  Monitor  the  /var/log  directory  on  the  indexers  and  forwarders  –  Create  a  report  that  shows  all  the  failed  login  aoempts  on  all  monitored  

servers  –  Write  a  “setup”  document  that  can  be  used  by  another  person  

ê  Presents  step-­‐by-­‐step  instrucIons  for  this  lab  exercise  

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Course  Work  

13  

!   Team  Project  –  Teams  of  three  students,  randomly  chosen  –  They  must  find  the  data  sets  and  define  the  analyIcs  

ê  AnalyIcs  must  be  reviewed  by  instructor  –  Typical  sources  

ê  Yelp  ê  www.data.gov  ê  data.sfgov.org  (City  of  San  Francisco)  ê  data.cityofchicago.org  (City  of  Chicago)  ê  data.cityofnewyork.us  (City  of  New  York)  ê  data.ca.gov  (State  of  California)  ê  data.ny.gov  (State  of  New  York)  

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Splunk  Lectures  

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Splunk  Lectures  

15  

!   Originally  used  the  Splunk  EducaIon  materials  –  For  the  first  two  semesters  

!   The  dynamics  of  corporate  educaIon  assume  –  8  hours  a  day  for  4  or  5  days    –  Exclusive  dedicaIon  to  the  course  

!   This  does  not  work  in  an  academic  seing  –  Two  75-­‐minute  lectures  a  week  –  Students  have  addiIonal  courses  

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Splunk  Lectures  

16  

!   MoIvaIon  to  write  a  book  –  PracIcal  hands-­‐on  projects  –  Using  Splunk  –  Based  on  the  experiences  of  teaching  this  course  –  NOT  an  academic  text  book  

!   Provides  the  necessary  –  Theory  –  Methodology  –  PracIcal  projects  used  to  teach  Splunk  commands  

ê  Machine  Data  ê  Social  media  

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Splunk  Lectures  

17  

!   Content  of  lectures  is  synchronized  with  due  dates  of  –  Individual  lab  –  Team  project  schedule  of  delivery  

!   Schedule  of  delivery  for  the  project  report  is  based  on  the  methodology  –  Phase  1  –  Loading  the  Data  –  Phase  2  -­‐  WriIng  the  searches  –  Phase  3  –  VisualizaIon  of  the  results  –  Final  PresentaIons  

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Splunk  Lectures  

18  

Lecture   Ac,vity   Content  

1   What  is  Splunk?    (C1)  Geing  data  into  Splunk  (C2)  

2   Remote  Data  CollecIon  (C15)  

3   Project  selecIon  due   Scaling  and  high  availability  (C16)  

4   The  FAA  Project:  Geing  the  flight  data  into  Splunk  (C9)  

5   Individual  lab  due   The  FAA  Project:  Geing  the  flight  data  into  Splunk  (C9)  

6   The  FAA  Project:  Analyzing  airlines,  airports,  flights  and  delays  (C10)  

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Splunk  Lectures  

19  

Lecture   Ac,vity   Content  

7   The  FAA  Project:  Analyzing  airlines,  airports,  flights  and  delays  (C10)  

8   Phase  1  due   The  FAA  Project:  Analyzing  a  specific  flight  over  the  years  (C11)  

9   Analyzing  Tweets  (C12)  

10   Analyzing  Foursquare  Check-­‐Ins  (C13)  

11   Phase  2  due   SenIment  Analysis  (C14)  

12   Using  log  files  to  create  advanced  analyIcs  (C7)  

13   Phase  3  due   Final  presentaIons  

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Grading  

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Grading  

21  

!   Individual  lab  –  Full  credit  if  the  report  presents  the  failed  logins  for  all  the  servers  being  

monitored  –  The  objecIve  is  for  the  student  to  install  and  understand  the  different  roles  

in  a  Splunk  cluster  –  Get  familiar  with  the  basic  use  of  indexing  and  search  

!   Team  Project  –  Team  deliverable  is  a  report  document  –  Grading  rubric  based  on  the  project  methodology  –  Big  data  pracIIoners  parIcipate  in  grading  

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Grading  Rubric  

22  

Phase/Item   Points   Phase  Total  

Phase  1  –  Loading  and  Verifying  Data   21  

         Data  input   9  

         VerificaIon  of  loaded  data   7  

         Report  quality   5  

Phase  2  –  Building  and  Verifying  Searches   33  

         Searches   20  

         VerificaIon  of  searches   8  

         Report  quality   5  

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Grading  Rubric  

23  

Phase/Item   Points   Phase  Total  

Phase  3  –  VisualizaIon  of  results   20  

         VisualizaIons   15  

         Report  quality   5  

Final  PresentaIon   10  

         Delivery  of  presentaIon   5  

         Quality  of  presentaIon   5  

Team  member  grade   16  

TOTAL   100  

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Project  Examples  

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Bay  Area  Bike  Share  

25  

!   Analysis  of  transportaIon  paoerns  of  the  users  of  this  bicycle  rental  company  

!   17  million  log  entries  !   Approximately  150,000  “trips”  

!   6  months  worth  of  data  !   610MB  

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Analysis  of  311  Calls  

26  

!   A  comparison  of  311  calls  of  New  York  City  and  San  Francisco  

!   6  years  worth  of  data  –  July  2008  to  April  2014  

!   San  Francisco  –  900,000  events  –  300MB  

!   New  York  City  –  9,000,000  –  3GB  

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Beer  Advocate  Reviews  

27  

!   A  comprehensive  analysis  of  best  rated  beers  by  season,  alcohol  content,  specialty  and  brewery  locaIon  

!   Total  of  1,586,614  reviews  !   From  July  1998  to  January  2012  

!   1.43GB  

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Yelp  –  Analysis  of  Phoenix  Reviews  

28  

!   11,537  business  in  the  Phoenix  metropolitan  area  

!   8,282  check-­‐in  sets  !   43,873  users  !   229,907  reviews  

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University  Campus  Safety  and  Security  

29  

!   Data  provided  by  the  US  Department  of  EducaIon  

!   Data  includes  6  years  –  2006  to  2011  

!   Used  three  files  –  Campus  crime  data  –  Campus  violaIons  

data  –  Campus  fire  data  

Top  15  Most  Dangerous  UniversiIes  

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                                           A  Week  in  

30  

!   A  broad  analysis  of  interesIng  facts  found  in  Foursquare  check-­‐ins  

!   September  8  to  14,  2012  !   24,187,615  Check-­‐Ins  !   10GB    

Most  Popular  Coffee  Shops  

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US  Office  of  Foreign  Labor  CerIficaIon  

31  

!   A  detailed  analysis  of  H1B  visas  and  corporate  sponsorships  for  permanent  residency  

!   From  2006  to  2013  !   745MB  

Permanent  Residency  Sponsorships  

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Splunk  Academic  Partner  Program  

32  

More  than  100  universiIes  are  teaching  Splunk…        Launch  Splunk  learning  in  your  university  today  by  leveraging  the  resources  of  the    Splunk  Academic  Partner  Program    www.splunk.com/goto/academic      ! Licensing    –  Free,  5gb  one-­‐year  Splunk  licenses  for  your  classroom  and  students  ! Free  training  courses  –  Leverage  free  web-­‐based  training  courses  to  jump-­‐start  learning  ! Instructor  content    –  Get  watermarked  PDF’s  of  the  slides  that  professional  Splunk  

trainers  use  ! Community    –  Network  with  peers  at  other  schools  to  share  content  and  best  pracIces  

QuesIons?  Contact  Rob  Reed,  Worldwide  EducaIon  Evangelist,  at  [email protected]    

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THANK  YOU