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AppDynamics Unified Monitoring

AppDynamics Unified Monitoring

AppDynamics Unified Monitoring presented at Velocity 2015

Dustin Whittle

May 28, 2015

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  1. Login Flight Status Search Flight Purchase Mobile Big data SOA

    NOSQL Cloud Agile Web Application complexity is exploding
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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  
  7. 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
  8. 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)
  9. 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
  10. Go  back  and  inves7gate  how  your  company   can  break

     down  the  monitoring  silos  and  be   more  impac]ul  with  applica7on  intelligence.