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How	
  monitoring	
  can	
  improve	
  
the	
  rest	
  of	
  the	
  company	
  
	
  
	
  
Monitorama	
  EU	
  2013	
  
@jeff_weinstein	
  
I
real-time 
and batch 
data analytics
Monitoring	
  can	
  wildly	
  improve	
  	
  
the	
  whole	
  company	
  by	
  
sharing	
  data	
  	
  
and	
  sharing	
  techniques.	
  
Monitoring	
  Folks	
  
Developers	
  
Business	
  	
  
Analysts	
  
ExecuIves	
  
&	
  Product	
  
Data	
  	
  
ScienIsts	
  
Data	
  
Apps	
  &	
  
Services	
  &	
  
Systems	
  
Users	
  
Data	
  
Code	
  &	
  
Config	
  
Monitoring	
  
Some	
  problems…	
  
Data	
  Processing	
  
Apps	
  
Systems	
  
Logs	
  /	
  
Events	
  
Metrics	
  
Graphs	
  
&	
  Alerts	
  
Apps	
  
3rd	
  Party	
  
Reports	
  &	
  
Queries	
  
ETL	
  
AnalyIc	
  
Systems	
  
Monitoring:	
  Streaming	
  
BI:	
  Batch	
  
Data	
  Needs	
  
Logs	
   Metrics	
   Logs	
   Metrics	
  
Streaming	
   Batch	
  
Data	
  
Monitoring	
  
BI	
  
Data	
  Tools	
  Stack	
  
Monitoring	
  
•  Ad	
  hoc	
  
–  sed,	
  grep,	
  awk	
  
–  ES,	
  LogStash,	
  Splunk,	
  …	
  
•  Storage	
  
–  Hosts,	
  Ganglia,	
  OTSDB	
  
–  Central	
  syslog	
  server	
  
•  VisualizaIon/ReporIng	
  
–  Graphite,	
  RRDTool,	
  3rd	
  party	
  
–  Homegrown	
  
•  AlerIng/EscalaIon	
  	
  
–  Nagios,	
  Sensu,	
  PagerDuty,	
  …	
  
Rest	
  of	
  company	
  
•  Ad	
  hoc	
  
–  Excel,	
  SQL,	
  Hive	
  
–  MapReduce,	
  …	
  
•  Storage	
  
–  Lots	
  o’	
  databases,	
  Excel	
  
–  Hadoop,	
  RDBMS…	
  
•  VisualizaIon/ReporIng	
  
–  Excel,	
  R,	
  Tableau	
  ...	
  
–  Dinosaur	
  apps,	
  …	
  
•  AlerIng/EscalaIon	
  	
  
–  nada	
  
Metrics	
  
Views	
  
Unintelligible	
  generated	
  views	
  Too	
  granular	
  for	
  long	
  term	
  trends	
  
Lack	
  of	
  historical	
   Intolerant	
  to	
  anomalies	
  
Team	
  and	
  incenIves	
  
•  What	
  team?	
  
•  Change	
  vs.	
  reliability	
  
•  Planning	
  
•  Budget	
  
•  Churn	
  
Good	
  or	
  bad?	
  
•  Specific	
  Tools	
  
•  Decentralized	
  
•  Focus	
  
•  Ownership	
  
•  Lost	
  context	
  
•  Siloed	
  work	
  
•  Data	
  dark	
  
•  Misunderstanding	
  
Some	
  fixes	
  
End	
  to	
  End	
  Data	
  Pipeline	
  
ü Structured	
  logs	
  
ü (Config)	
  
ü Measure	
  once	
  
ü AutomaIc	
  metrics	
  
ü API	
  
ü Graph	
  tools	
  
ü Glossary	
  
ü AnnotaIons	
  and	
  tags	
  
ü Pipeline	
  
Structured	
  events	
  
•  JSON	
  (or	
  whatever)	
  
•  (opIonal)	
  config	
  
•  Tags	
  per	
  key	
  
– Type	
  
– Tag:	
  latency,	
  funnel,…	
  
– DescripIon	
  
– Storage	
  
Auto:	
  Graphs,	
  Glossary,	
  &	
  Storage	
  
•  Graphs	
  and	
  dashboards	
  
•  *	
  templates	
  
•  Views	
  and	
  stats	
  
•  Glossary	
  
•  Batch	
  analyIcs	
  
•  Long	
  term	
  storage	
  
build	
  
learn	
  
communicate	
  
inspire	
  
Developers	
  
•  Logging	
  toolkit	
  
•  Data	
  pipeline	
  
•  Pain	
  points	
  
•  Outage	
  causes	
  
•  Deployment	
  pracIces	
  
•  EscalaIon	
  playbook	
  
•  Measurement	
  as	
  TDD	
  
•  Monitor	
  staging	
  env	
  
Business	
  Analysts	
  
•  Structured	
  logs	
  	
  
•  Config	
  for	
  ETL	
  
•  Metrics	
  definiIons	
  	
  
•  Slices	
  and	
  visualizaIons	
  
•  Data	
  size	
  and	
  cardinality	
  
•  Outages	
  and	
  delays	
  
•  Flexibility	
  
•  VisualizaIon	
  and	
  tools	
  
Data	
  ScienIsts	
  
•  Access	
  to	
  (meta)data	
  
•  Query	
  monitoring	
  
•  StaIsIcs	
  and	
  models	
  
•  New	
  data	
  streams	
  
•  Context	
  of	
  data	
  issues	
  
•  What’s	
  in	
  the	
  logs	
  
•  Validate	
  algorithms	
  
•  Teach	
  stats	
  and	
  models!	
  
Product	
  &	
  ExecuIves	
  
•  Curated	
  dashboards	
  
•  Graph/alert	
  tools	
  
•  Learn	
  the	
  business	
  
•  PrioriIze	
  alerts	
  by	
  $	
  
•  Incident	
  post	
  mortems	
  	
  
•  Metrics	
  granularity	
  
•  Data	
  driven	
  decisions	
  
•  Recognize	
  and	
  celebrate	
  
Monitoring	
  can	
  become	
  the	
  data	
  
plahorm	
  and	
  improve	
  all	
  teams	
  
with	
  its	
  techniques.	
  
Icons	
  from	
  The	
  Noun	
  Project:	
  Dmitry	
  Baranovskiy,	
  Benjamin	
  Orlovski,	
  Luis	
  Prado,	
  MikaDo	
  Nguyen,	
  Yarden	
  Gilboa,	
  Javier	
  Cabezas,	
  Icons	
  Pusher,	
  Jeremy	
  Bristol,	
  Blake	
  Thomas,	
  RiIka	
  Khasgiwale,	
  
Mayene	
  de	
  Leon,	
  Yorlmar	
  Campos,	
  Sergey	
  Shmid	
  
@jeff_weinstein	
  
Thanks!	
  hiring	
  ;)	
  

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Monitorama: How monitoring can improve the rest of the company

  • 1. How  monitoring  can  improve   the  rest  of  the  company       Monitorama  EU  2013   @jeff_weinstein  
  • 2. I real-time and batch data analytics
  • 3. Monitoring  can  wildly  improve     the  whole  company  by   sharing  data     and  sharing  techniques.  
  • 4. Monitoring  Folks   Developers   Business     Analysts   ExecuIves   &  Product   Data     ScienIsts   Data  
  • 5. Apps  &   Services  &   Systems   Users   Data   Code  &   Config   Monitoring  
  • 7. Data  Processing   Apps   Systems   Logs  /   Events   Metrics   Graphs   &  Alerts   Apps   3rd  Party   Reports  &   Queries   ETL   AnalyIc   Systems   Monitoring:  Streaming   BI:  Batch  
  • 8. Data  Needs   Logs   Metrics   Logs   Metrics   Streaming   Batch   Data   Monitoring   BI  
  • 9. Data  Tools  Stack   Monitoring   •  Ad  hoc   –  sed,  grep,  awk   –  ES,  LogStash,  Splunk,  …   •  Storage   –  Hosts,  Ganglia,  OTSDB   –  Central  syslog  server   •  VisualizaIon/ReporIng   –  Graphite,  RRDTool,  3rd  party   –  Homegrown   •  AlerIng/EscalaIon     –  Nagios,  Sensu,  PagerDuty,  …   Rest  of  company   •  Ad  hoc   –  Excel,  SQL,  Hive   –  MapReduce,  …   •  Storage   –  Lots  o’  databases,  Excel   –  Hadoop,  RDBMS…   •  VisualizaIon/ReporIng   –  Excel,  R,  Tableau  ...   –  Dinosaur  apps,  …   •  AlerIng/EscalaIon     –  nada  
  • 11. Views   Unintelligible  generated  views  Too  granular  for  long  term  trends   Lack  of  historical   Intolerant  to  anomalies  
  • 12. Team  and  incenIves   •  What  team?   •  Change  vs.  reliability   •  Planning   •  Budget   •  Churn  
  • 13. Good  or  bad?   •  Specific  Tools   •  Decentralized   •  Focus   •  Ownership   •  Lost  context   •  Siloed  work   •  Data  dark   •  Misunderstanding  
  • 15. End  to  End  Data  Pipeline   ü Structured  logs   ü (Config)   ü Measure  once   ü AutomaIc  metrics   ü API   ü Graph  tools   ü Glossary   ü AnnotaIons  and  tags   ü Pipeline  
  • 16. Structured  events   •  JSON  (or  whatever)   •  (opIonal)  config   •  Tags  per  key   – Type   – Tag:  latency,  funnel,…   – DescripIon   – Storage  
  • 17. Auto:  Graphs,  Glossary,  &  Storage   •  Graphs  and  dashboards   •  *  templates   •  Views  and  stats   •  Glossary   •  Batch  analyIcs   •  Long  term  storage  
  • 19. Developers   •  Logging  toolkit   •  Data  pipeline   •  Pain  points   •  Outage  causes   •  Deployment  pracIces   •  EscalaIon  playbook   •  Measurement  as  TDD   •  Monitor  staging  env  
  • 20. Business  Analysts   •  Structured  logs     •  Config  for  ETL   •  Metrics  definiIons     •  Slices  and  visualizaIons   •  Data  size  and  cardinality   •  Outages  and  delays   •  Flexibility   •  VisualizaIon  and  tools  
  • 21. Data  ScienIsts   •  Access  to  (meta)data   •  Query  monitoring   •  StaIsIcs  and  models   •  New  data  streams   •  Context  of  data  issues   •  What’s  in  the  logs   •  Validate  algorithms   •  Teach  stats  and  models!  
  • 22. Product  &  ExecuIves   •  Curated  dashboards   •  Graph/alert  tools   •  Learn  the  business   •  PrioriIze  alerts  by  $   •  Incident  post  mortems     •  Metrics  granularity   •  Data  driven  decisions   •  Recognize  and  celebrate  
  • 23. Monitoring  can  become  the  data   plahorm  and  improve  all  teams   with  its  techniques.  
  • 24. Icons  from  The  Noun  Project:  Dmitry  Baranovskiy,  Benjamin  Orlovski,  Luis  Prado,  MikaDo  Nguyen,  Yarden  Gilboa,  Javier  Cabezas,  Icons  Pusher,  Jeremy  Bristol,  Blake  Thomas,  RiIka  Khasgiwale,   Mayene  de  Leon,  Yorlmar  Campos,  Sergey  Shmid   @jeff_weinstein   Thanks!  hiring  ;)