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Unified	
  Monitoring	
  with	
  
AppDynamics
Dus$n	
  Whi*le	
  
@AppDynamics
52% of Fortune 500 firms
since 2000 are gone
Login
Flight Status
Search Flight
Purchase
Mobile
Big data
SOA
NOSQL
Cloud
Agile
Web
Application complexity is exploding
Up7me	
  is	
  cri7cal	
  for	
  enterprises	
  and	
  consumers
Performance	
  impacts	
  the	
  bo=om	
  line
How	
  fast	
  is	
  fast	
  enough?
§ Performance	
  is	
  key	
  to	
  a	
  great	
  user	
  experience	
  	
  
-­‐ Under	
  100ms	
  is	
  perceived	
  as	
  reac$ng	
  instantaneously	
  
-­‐ A	
  100ms	
  to	
  300ms	
  delay	
  is	
  percep$ble	
  
-­‐ 1	
  second	
  is	
  about	
  the	
  limit	
  for	
  the	
  user's	
  flow	
  of	
  thought	
  to	
  stay	
  uninterrupted	
  
-­‐ Users	
  expect	
  a	
  site	
  to	
  load	
  in	
  2	
  seconds	
  
-­‐ ADer	
  3	
  seconds,	
  40%	
  will	
  abandon	
  your	
  site.	
  
-­‐ 10	
  seconds	
  is	
  about	
  the	
  limit	
  for	
  keeping	
  the	
  user's	
  a*en$on	
  
§ Modern	
  applica7ons	
  spend	
  more	
  7me	
  in	
  the	
  browser	
  than	
  on	
  the	
  server-­‐side
Who	
  cares	
  about	
  performance?
How	
  many	
  enterprise	
  monitoring	
  products	
  would	
  you	
  es7mate	
  your	
  IT	
  org	
  owns?
The	
  war	
  room	
  response	
  team
The	
  problems	
  with	
  monitoring	
  tools
§ Root	
  cause	
  isola7on	
  is	
  elusive	
  as	
  monitoring	
  lives	
  in	
  silos	
  
-­‐ Infrastructure	
  
-­‐ Hardware	
  +	
  Logs	
  +	
  Network	
  +	
  Storage	
  +	
  Containers	
  +	
  VMs	
  
-­‐ Applica$on	
  
-­‐ Load	
  Balancers	
  +	
  Web	
  Servers	
  +	
  App	
  Servers	
  +	
  File	
  Servers	
  
-­‐ Databases	
  +	
  Caches	
  +	
  Queues	
  +	
  Third	
  party	
  services	
  
-­‐ End	
  Users	
  
-­‐ CDN	
  
-­‐ Web	
  +	
  Mobile	
  
§ Metrics	
  lack	
  the	
  context	
  of	
  impact
Monitoring	
  lacks	
  the	
  business	
  context
The	
  struggle	
  of	
  modern	
  monitoring
§ Organiza7ons	
  focus	
  on	
  availability	
  +	
  raw	
  metrics	
  and	
  not	
  end	
  user	
  experience	
  /	
  impact	
  
§ Complex	
  apps	
  built	
  on	
  micro-­‐services	
  in	
  containers	
  living	
  in	
  elas7c	
  cloud	
  environments	
  
§ Too	
  many	
  graphs	
  from	
  too	
  many	
  metrics	
  
-­‐ Understanding	
  the	
  signal	
  from	
  the	
  noise	
  is	
  difficult	
  
-­‐ No	
  topology	
  awareness.	
  No	
  transac$onal	
  visibility.	
  No	
  root	
  cause.	
  
§ Alert	
  storming	
  with	
  too	
  many	
  false	
  alarms	
  
-­‐ Aler$ng	
  is	
  based	
  on	
  sta$c	
  thresholds	
  —	
  lacks	
  intelligent	
  anomaly	
  detec$on	
  +	
  correla$on	
  
-­‐ Lack	
  of	
  historical	
  context	
  or	
  rela$onships	
  between	
  metrics	
  and	
  events	
  
§ A	
  single	
  pane	
  of	
  glass	
  across	
  the	
  performance	
  stakeholders	
  
-­‐ Not	
  able	
  to	
  quan$fy	
  the	
  impact	
  of	
  performance	
  degrada$on	
  —	
  Not	
  self-­‐service
Context	
  is	
  king:	
  Unified	
  Monitoring
Breaking	
  down	
  the	
  silos
Situa7on-­‐aware	
  data	
  and	
  views
Web Ops App
Owner
Server
Admin
DBA
IT Ops
Monitor	
  the	
  end	
  user	
  experience
§ Real	
  User	
  Monitoring	
  vs	
  Synthe7c	
  Monitoring	
  
-­‐ Synthe$c	
  tests	
  provide	
  24/7	
  assurance	
  
-­‐ RUM	
  provides	
  insights	
  into	
  actual	
  users	
  
-­‐ Mobile	
  device	
  segmenta$on	
  
-­‐ Unexpected	
  behavior/trends	
  
§ Real	
  User	
  Monitoring	
  
-­‐ Naviga$on	
  Timing	
  API	
  
-­‐ Resource	
  Timing	
  API	
  
-­‐ User	
  Timing	
  API	
  
-­‐ Javascript	
  Errors
Metrics	
  +	
  logs	
  help,	
  but	
  intelligence	
  is	
  be=er
Moving	
  from	
  reac7ve	
  to	
  proac7ve
§ Resolving	
  before	
  the	
  red	
  =	
  fixing	
  in	
  the	
  yellow	
  
-­‐ Automa$c	
  runbook	
  automa$on	
  integrates	
  with	
  your	
  devops	
  stack	
  
§ Intelligent	
  anomaly	
  detec7on	
  across	
  end-­‐user,	
  applica7on,	
  database,	
  server	
  metrics	
  
-­‐ Automa$cally	
  calculates	
  dynamic	
  baselines	
  for	
  all	
  of	
  your	
  metrics,	
  which,	
  based	
  on	
  actual	
  
usage,	
  define	
  what	
  is	
  "normal"	
  for	
  each	
  metric	
  
-­‐ Smart	
  aler$ng	
  based	
  on	
  any	
  devia$on	
  from	
  the	
  baselines	
  
§ Understand	
  trends	
  and	
  pa=erns	
  in	
  failures	
  -­‐	
  automa7cally	
  learn	
  from	
  the	
  past	
  
-­‐ Understand	
  what	
  are	
  the	
  most	
  impacaul	
  issues	
  to	
  resolve	
  
-­‐ Ocen	
  $mes	
  external	
  services	
  are	
  the	
  root	
  cause	
  with	
  limited	
  visibility	
  
-­‐ Enforce	
  SLAs	
  
Moving	
  from	
  reac7ve	
  to	
  proac7ve
-­‐ Automa7c	
  discovery	
  of	
  environment	
  and	
  applica7on	
  changes	
  
-­‐ New	
  APIs,	
  transac$ons,	
  services,	
  clouds	
  
§ Leverage	
  analy7cs	
  to	
  be	
  smarter	
  about	
  using	
  the	
  data	
  you	
  already	
  have	
  
-­‐ System	
  Logs,	
  Metrics	
  from	
  events	
  and	
  infrastructure	
  stats	
  
-­‐ Transac$ons	
  with	
  request	
  parameters	
  +	
  User	
  state	
  from	
  cookies/sessions	
  
§ Performance	
  monitoring	
  isn’t	
  just	
  about	
  the	
  tech	
  
-­‐ Visibility	
  into	
  the	
  impact	
  of	
  business	
  -­‐	
  aler$ng	
  when	
  revenue	
  is	
  down
AppDynamics	
  leverages	
  and	
  embraces	
  open-­‐source
Leading	
  companies	
  invest	
  in	
  performance
§ Etsy	
  =	
  Kale	
  =	
  Statsd	
  +	
  Skyline	
  +	
  Oculus	
  (stats	
  collec$on	
  +	
  anomaly	
  detec$on/correla$on)	
  
§ Nealix	
  =	
  PCP	
  +	
  Vector	
  +	
  Servo	
  +	
  Atlas	
  (dashboards,	
  data	
  collec$on,	
  root	
  cause	
  analysis)	
  
§ Twi*er	
  =	
  Zipkin	
  (distributed	
  tracing)
Recommenda7ons
§ Treat	
  performance	
  as	
  a	
  feature	
  	
  
-­‐ Create	
  a	
  performance	
  budget	
  with	
  milestones,	
  speed	
  index,	
  page	
  speed	
  
-­‐ Capacity	
  plan	
  and	
  load	
  test	
  the	
  server-­‐side	
  	
  
-­‐ Op$mize	
  and	
  performance	
  test	
  the	
  client-­‐side	
  	
  
§ Monitor	
  performance	
  in	
  development	
  and	
  produc7on	
  	
  
-­‐ Instrument	
  everything	
  
-­‐ Measure	
  the	
  difference	
  of	
  every	
  change	
  
-­‐ Understand	
  how	
  failures	
  impact	
  performance	
  
§ Make	
  monitoring	
  cri7cal	
  and	
  test	
  in	
  your	
  con7nuous	
  delivery	
  process	
  	
  
§ Connect	
  the	
  exec/dev/ops	
  performance	
  perspec7ves	
  to	
  align	
  on	
  business	
  impact
Go	
  back	
  and	
  inves7gate	
  how	
  your	
  company	
  
can	
  break	
  down	
  the	
  monitoring	
  silos	
  and	
  be	
  
more	
  impac]ul	
  with	
  applica7on	
  intelligence.
Ques7ons?
Thank	
  you!	
  Enjoy	
  the	
  rest	
  of	
  Velocity	
  2015.
http://www.appdynamics.com/

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  • 6.
  • 7. Up7me  is  cri7cal  for  enterprises  and  consumers
  • 9. How  fast  is  fast  enough? § Performance  is  key  to  a  great  user  experience     -­‐ Under  100ms  is  perceived  as  reac$ng  instantaneously   -­‐ A  100ms  to  300ms  delay  is  percep$ble   -­‐ 1  second  is  about  the  limit  for  the  user's  flow  of  thought  to  stay  uninterrupted   -­‐ Users  expect  a  site  to  load  in  2  seconds   -­‐ ADer  3  seconds,  40%  will  abandon  your  site.   -­‐ 10  seconds  is  about  the  limit  for  keeping  the  user's  a*en$on   § Modern  applica7ons  spend  more  7me  in  the  browser  than  on  the  server-­‐side
  • 10. Who  cares  about  performance?
  • 11.
  • 12.
  • 13.
  • 14. How  many  enterprise  monitoring  products  would  you  es7mate  your  IT  org  owns?
  • 15. The  war  room  response  team
  • 16. The  problems  with  monitoring  tools § Root  cause  isola7on  is  elusive  as  monitoring  lives  in  silos   -­‐ Infrastructure   -­‐ Hardware  +  Logs  +  Network  +  Storage  +  Containers  +  VMs   -­‐ Applica$on   -­‐ Load  Balancers  +  Web  Servers  +  App  Servers  +  File  Servers   -­‐ Databases  +  Caches  +  Queues  +  Third  party  services   -­‐ End  Users   -­‐ CDN   -­‐ Web  +  Mobile   § Metrics  lack  the  context  of  impact
  • 17. Monitoring  lacks  the  business  context
  • 18. The  struggle  of  modern  monitoring § Organiza7ons  focus  on  availability  +  raw  metrics  and  not  end  user  experience  /  impact   § Complex  apps  built  on  micro-­‐services  in  containers  living  in  elas7c  cloud  environments   § Too  many  graphs  from  too  many  metrics   -­‐ Understanding  the  signal  from  the  noise  is  difficult   -­‐ No  topology  awareness.  No  transac$onal  visibility.  No  root  cause.   § Alert  storming  with  too  many  false  alarms   -­‐ Aler$ng  is  based  on  sta$c  thresholds  —  lacks  intelligent  anomaly  detec$on  +  correla$on   -­‐ Lack  of  historical  context  or  rela$onships  between  metrics  and  events   § A  single  pane  of  glass  across  the  performance  stakeholders   -­‐ Not  able  to  quan$fy  the  impact  of  performance  degrada$on  —  Not  self-­‐service
  • 19.
  • 20. Context  is  king:  Unified  Monitoring
  • 22.
  • 23.
  • 24.
  • 25. Situa7on-­‐aware  data  and  views Web Ops App Owner Server Admin DBA IT Ops
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31. Monitor  the  end  user  experience § Real  User  Monitoring  vs  Synthe7c  Monitoring   -­‐ Synthe$c  tests  provide  24/7  assurance   -­‐ RUM  provides  insights  into  actual  users   -­‐ Mobile  device  segmenta$on   -­‐ Unexpected  behavior/trends   § Real  User  Monitoring   -­‐ Naviga$on  Timing  API   -­‐ Resource  Timing  API   -­‐ User  Timing  API   -­‐ Javascript  Errors
  • 32. Metrics  +  logs  help,  but  intelligence  is  be=er
  • 33.
  • 34.
  • 35.
  • 36. Moving  from  reac7ve  to  proac7ve § Resolving  before  the  red  =  fixing  in  the  yellow   -­‐ Automa$c  runbook  automa$on  integrates  with  your  devops  stack   § Intelligent  anomaly  detec7on  across  end-­‐user,  applica7on,  database,  server  metrics   -­‐ Automa$cally  calculates  dynamic  baselines  for  all  of  your  metrics,  which,  based  on  actual   usage,  define  what  is  "normal"  for  each  metric   -­‐ Smart  aler$ng  based  on  any  devia$on  from  the  baselines   § Understand  trends  and  pa=erns  in  failures  -­‐  automa7cally  learn  from  the  past   -­‐ Understand  what  are  the  most  impacaul  issues  to  resolve   -­‐ Ocen  $mes  external  services  are  the  root  cause  with  limited  visibility   -­‐ Enforce  SLAs  
  • 37.
  • 38. Moving  from  reac7ve  to  proac7ve -­‐ Automa7c  discovery  of  environment  and  applica7on  changes   -­‐ New  APIs,  transac$ons,  services,  clouds   § Leverage  analy7cs  to  be  smarter  about  using  the  data  you  already  have   -­‐ System  Logs,  Metrics  from  events  and  infrastructure  stats   -­‐ Transac$ons  with  request  parameters  +  User  state  from  cookies/sessions   § Performance  monitoring  isn’t  just  about  the  tech   -­‐ Visibility  into  the  impact  of  business  -­‐  aler$ng  when  revenue  is  down
  • 39. AppDynamics  leverages  and  embraces  open-­‐source
  • 40. Leading  companies  invest  in  performance § Etsy  =  Kale  =  Statsd  +  Skyline  +  Oculus  (stats  collec$on  +  anomaly  detec$on/correla$on)   § Nealix  =  PCP  +  Vector  +  Servo  +  Atlas  (dashboards,  data  collec$on,  root  cause  analysis)   § Twi*er  =  Zipkin  (distributed  tracing)
  • 41. Recommenda7ons § Treat  performance  as  a  feature     -­‐ Create  a  performance  budget  with  milestones,  speed  index,  page  speed   -­‐ Capacity  plan  and  load  test  the  server-­‐side     -­‐ Op$mize  and  performance  test  the  client-­‐side     § Monitor  performance  in  development  and  produc7on     -­‐ Instrument  everything   -­‐ Measure  the  difference  of  every  change   -­‐ Understand  how  failures  impact  performance   § Make  monitoring  cri7cal  and  test  in  your  con7nuous  delivery  process     § Connect  the  exec/dev/ops  performance  perspec7ves  to  align  on  business  impact
  • 42. Go  back  and  inves7gate  how  your  company   can  break  down  the  monitoring  silos  and  be   more  impac]ul  with  applica7on  intelligence.
  • 44. Thank  you!  Enjoy  the  rest  of  Velocity  2015.