Copyright  ©  2014  Splunk  Inc.  

Jon  Rooney  Director  of  Developer  Marke@ng  Splunk  

Applica@on  Lifecycle  Intelligence:  Splunking  the  Product  Development  Lifecycle  and  DevOps  

Disclaimer  

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During  the  course  of  this  presenta@on,  we  may  make  forward-­‐looking  statements  regarding  future  events  or  the  expected  performance  of  the  company.  We  cau@on  you  that  such  statements  reflect  our  current  expecta@ons  and  

es@mates  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  presenta@on  are  being  made  as  of  the  @me  and  date  of  its  live  presenta@on.  If  reviewed  aUer  its  live  presenta@on,  this  presenta@on  may  not  contain  current  or  accurate  informa@on.  We  do  not  assume  any  obliga@on  to  update  any  forward-­‐looking  statements  we  may  make.  In  addi@on,  any  informa@on  about  our  roadmap  outlines  our  general  product  direc@on  and  is  subject  to  change  at  any  @me  without  no@ce.  It  is  for  informa@onal  purposes  only,  and  shall  not  be  incorporated  into  any  contract  or  other  commitment.  Splunk  undertakes  no  obliga@on  either  to  develop  the  features  or  func@onality  described  or  to  

include  any  such  feature  or  func@onality  in  a  future  release.  

Agenda  

!   Introduc@on  and  background  !   Splunk  for  Applica@on  Development  !   Demos!  !   Customer  Examples  !   Live  Demo  !   Q&A    

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Introduc@on  and  Background  

My  Background  and  Role  

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!   Director  of  Developer  Marke@ng  ! Splunker  of  2+  years  !   Veteran  of  MicrosoU,  Bay  Area  start-­‐ups,  Accenture  

!   Philadelphia  na@ve   Screenshot  here  

Splunk  for  App  Development  

Applica@on  Development  Challenges  

Build  Unit  Tes@ng  

Code  

Check-­‐in   Integra@on  Tes@ng   Deploy  

Staging  

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Applica@on  Development  Challenges  

Build  Unit  Tes@ng  

Code  

Check-­‐in   Integra@on  Tes@ng   Deploy  

Staging  

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Lack  of  visibility  across  the  product  development  lifecycle  

Pressure  to  increase  velocity  and  agility  with  DevOps  

Limited  insights  into  behavior  and  performance  from  applica@on  logs  

Quickly  trace  and  iden@fy  errors  anywhere    in  the  codebase  with  real-­‐@me  search    and  monitoring    

Instrument  your  app  logs  to  gain    applica@on  intelligence    

Break  down  dev  tool  silos  with  real-­‐@me  insights  from  machine  data    

GAIN  END-­‐TO-­‐END  VISIBILITY  ACROSS  THE  DEV  TOOL  CHAIN    

FIND  AND  FIX  ISSUES  FASTER    

PUSH  BETTER  CODE  USING  ANALYTICS    

Splunk  for  Applica@on  Lifecycle  Intelligence  

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Real-­‐@me  dashboards  show  error  rate  in  produc@on  and  impact  of  

pushing  new  builds  

Developers  can  search  and  visualize  web  logs,  Java  logs—without  

produc@on  access  

Alerts  no@fy  developers  as  soon  as  a  problem  arises    

Find  and  Fix  Issues  Faster  

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Gain  end-­‐to-­‐end  visibility  to  make  informed  decisions  

Analy@cs  insights  without  the  need  for  addi@onal  analy@cs  tools    

Ask  ques@ons  while  exploring  and  collec@ng  data    

Push  Beger  Code  Using  Analy@cs    void  submitPurchase(purchaseId) !{ !

!log.info("action=submitPurchaseStart, purchaseId=%d", purchaseId)!//these calls throw an exception on error! !submitToCreditCard(...)! !generateInvoice(...)! !generateFullfillmentOrder(...)!

!log.info("action=submitPurchaseCompleted, purchaseId=%d", purchaseId)! } !!

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CI  /  Build  Servers  

Project  and  Issue  Tracking  

Code  Repository  

QA  /  Tes@ng  Tools  

End-­‐To-­‐End  Visibility  Across  The  Dev  Tool  Chain    

Deployment  Servers  

CI  /  Build  Server  

Code  Review  

Task  Tracking  

What  Data  Can  You  Splunk?  

Which  code  has  already  been  reviewed  for  this  release/sprint?  Who  has  completed  the  most  code  reviews?  What  code  has  NOT  been  reviewed?    

Who  is  changing  files?  What  kinds  of  files  are  being  changed?  What  branches  are  most  ac@ve?  What  types  of  ac@vi@es  are  occurring  for  a  branch?  

Version  Control  

How  many  builds  completed  today/this  week/this  month?  Which  check-­‐in  kicked  off  this  build?  Which  tests  ran  against  this  failed  build?  

Which  tasks  are  assigned  to  which  developers?  What  progress  is  being  made  to  complete  assigned  tasks?  What  tasks  remain  for  this  release/sprint?    

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Key  Benefits  of  Applica@on  Lifecycle  Intelligence  

   

   

   

Reduced  Time  to  Market  

Shrink  the  @me  it  takes  to  get  code  through  dev/test  to  market  through  faster  issue  iden@fica@on  and  

resolu@on    

Increased  Agility  

With  real-­‐@me  visibility  into  processes  like  code  check-­‐ins,  builds  and  tests  to  support  

DevOps  prac@ces  like  con@nuous  integra@on    

“Our  devs  are  now  able  to  find  and  fix  issues  five  to  ten  

4mes  faster.”  

“We  can  monitor  all  the  automa4on  and  handoffs    it  takes  to  deploy  5-­‐10    

4mes  a  day”  

Applica@on  Insights  

Instrument  customer  applica@on  logs  to  capture  cri@cal  

business  events  and  user  behavior  

“My  code  isn’t  ready  un4l  it’s  Splunk-­‐ready”  

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Demos  

Customer  Examples  

Customer  Success  

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Splunk  Enables  DevOps  Agility  

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!   Challenges:    –  Teams  struggle  to  recognize  errors  in  new  builds  due  to  infrastructure  complexity    –  Logs  are  siloed,  scagered  across  dozens  of  servers,  without  a  single  view  and  with  no  

ability  to  correlate  or  search  other  than  manual  processes  –  Lack  the  ability  to  analyze  trends  and  iden@fy  outliers  

!   With  Splunk:    –  Increased  success  rates  of  deployments  -­‐  lower  errors  for  new  builds  –  Detect  issues  prior  to  them  having  an  affect  on  the  produc@on  process  –  Aler@ng  on  thresholds  for  event  log  errors  -­‐  roll-­‐back  problema@c  deployments  or  

diagnose  a  build  in  a  subset  of  the  produc@on  environment    

“It’s  like  we  were  working  without  peripheral  vision  before  and  now  we  have  it.”  Robert  Gonsalves  Web  Opera4ons  

Splunking  QA  for  Agility  and  Code  Quality  

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!   Challenges:    –  Difficulty  iden@fying  defects  –  finding  and  fixing  issues  took  days/weeks    –  Developers  struggled  to  ensure  that  insights  can  be  gleaned  from  custom-­‐built  

applica@ons  around  user  behavior  and  performance    –  Not  automated  alert  system  to  immediately  no@fy  team  about  errors  

!   With  Splunk:  –  Provide  full  visibility  into  Sanity  and  Load  tes@ng  in  QA  environments    

before  deploying  to  produc@on  –  Assists  in  troubleshoo@ng  if  tests  do  not  contain  the  expected  results    –  New  code  is  not  ready  un@l  the  logs  are  Splunk-­‐friendly  

“Developers  are  now  able  to  look  for  errors  and  troubleshoot  issues  five  to  ten  @mes  faster    by  having  all  their  event  data  centralized  in  Splunk.”   Nate  Smalley  

Principal  Engineer  

Con@nuous  Integra@on  &  Deployment  with  Splunk  

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!   Challenges:    –  No  single  place  to  access  and  visualize  machine  data  –  Manual  diagnosing  and  searching  through  data  generated  by  servers  and  applica@ons  –  To  retrieve  informa@on,  sysadmins  have  to  ssh  into  produc@on  machines  before  

sending  off  to  developers  to  grep  through  the  logs    

!   With  Splunk:  –  Quickly  validate  and  troubleshoot  code  pushes  to  produc@on  –  Ensure  that  new  code  does  not  nega@vely  impact  performance  or  user  experience    –  Reduced  one  applica@on’s  error  rate  by  2  orders  of  magnitude  in  a  mager  of  weeks  

“Dump  all  the  logs  into  Splunk,  and  it  starts  looking  like  one  big  system,  instead  of  a  bazillion  teeny  ones  that  hate  each  other.”   Alison  Perkins  

Senior  Systems  Engineer  

Internet-­‐Scale  Performance  Tes@ng  

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“Splunk  lets  us  quickly  correlate  and  debug  performance  issues  in  a  mul@-­‐@er  environment  so  we  can  track  our  cri@cal  SLAs  in  pre-­‐produc@on.”   Amit  Sehgal  

Performance  &  Scalability  Engineer    

!   Challenges:    –  Difficulty  in  retrieving  log  events  covering  a  specific  @me  range  and  matching  specific  criteria    –  Each  team  has  their  own  set  of  tools  and  homegrown  monitoring  systems—each  a  silo  –  Time-­‐consuming  and  error-­‐prone  tradi@onal  search  methods  led  to  experts  searching  through  

mountains  of  data  to  uncover  issues  

!   With  Splunk:  –  Teams  are  able  to  share  data  and  dashboards  to  gain  insights  on  historical  and  real-­‐@me  data    –  Improved  visibility  and  understanding  of  performance  data  before  code  is  deployed  to  

produc@on  –  Overall  velocity  improvement  –  ability  to  run  2x  number  of  tests  per  day    

Wrap-­‐up  

What  Did  We  Learn  Today?  

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!   Splunk  can  be  valuable  for  applica@on  development  and  DevOps  !   Find  and  fix  issues  with  real-­‐@me  search  and  monitoring    !   Instrument  your  custom  app  logs  with  Seman@c  Logging  to  make  those  logs  more  Splunk-­‐friendly  

!   Splunk  can  correlate  data  from  disparate  tools  across  your  applica@on  lifecycle  to  give  your  real-­‐@me  insights  and  help  reduce  @me  to  market  

!   Lots  of  customers  are  doing  this  –  you  can  too!  

Where  to  go  for  More  Info  

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!   Tutorials,  Code  Samples,  Geung  Started,  Downloads  –  hgp://dev.splunk.com/  

!   Support  –  hgps://www.splunk.com/page/submit_issue    

!   GitHub  –  hgps://github.com/splunk/  

!   Twiger  –  hgps://twiger.com/splunkdev    

!   Blog  –  hgp://blogs.splunk.com/dev/    

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THANK  YOU