Logging, Instrumentation, Dashboards and Alerts - for developers
- 2. WONDERING WHO IS THAT GUY? HENRY BEEN Independent Devops & Azure Architect E: consultancy@henrybeen.nl T: @henry_been L: linkedin.com/in/henrybeen W: henrybeen.nl
- 3. Very boring part Pretty boring part Maybe boring part Amazing part Really amazing part Mindblowing part LOGGING, INSTRUMENTATION, DASHBOARDS & ALERTS
- 4. A bit of monitoring theory What to monitor Demo’s! LOGGING, INSTRUMENTATION, DASHBOARDS, ALERTS
- 5. MONITORING -or- KNOWING WHAT BE HAPPENING
- 6. Instrumentation Most often forgotten Concerned with metrics • (Timestamp, value) tuples • Events & values • Dimensions • Used for Dashboards & Alerts Rolled up over time Logging Often combined with tracing Concerned with state changes • When • By who • What changed • Can a source of metrics Retained for longer or indefinitly Tracing Used for troubleshooting What we developers call logging • When • Code location • Very, very verbose message • Can a source of metrics Retained for a limited time MONITORING
- 7. VM / container Timeseries Database Application Instance Agent SDK Logging Database Https endpoint Visualization Engine Your Dashboards Query Engine Your Alerts Streaming Data Engine
- 8. BUT HEY THAT STUFF IS OPERATIONS… WHY WOULD I CARE?
- 10. • DevOps is the union of people, process, and products to enable continuous delivery of value to your end users. “ ” DEVOPS
- 11. OKAY, OKAY I CARE… NOW, WHAT TO MONITOR?
- 12. OKAY, OKAY I CARE… NOW, WHAT NOT TO MONITOR?
- 13. WHAT NOT TO DO FOCUS ON AVERAGES Averages are lying cheats and hide real issues! • Use dimensions to find outliers • Use maximums or percentiles to identify spread FOCUS ON YOUR SYSTEMS Do you think your users care? At all? • Is the amount of disk IO really interesting? • Does page file usage predict conversion? To add some nuance: - Some system metrics are handy, just don’t start there maybe - Same goes for averages
- 14. 0 20 40 60 80 100 120 Database load(%) DO WE HAVE AN ISSUE? Proposed alert
- 15. ARE MY USERS HAPPY? 0 20 40 60 80 100 120 140 160 Average response time
- 16. 0 200 400 600 800 1000 1200 Average response time and maximum response time Average response time Maximum response time ARE MY USERS HAPPY?
- 17. 0 100 200 300 400 500 600 700 800 900 Average response time and response time per operation Average response time View item AddToBasket ARE MY USERS HAPPY?
- 19. MEASURE THINGS THE USER CARES ABOUT AND THINK IT THROUGH!
- 20. Let’s do a Quick Demo! Demo
- 21. A VERY GOOD BOOK ALSO QUITE THIN
- 22. FOR THOSE USING AZURE HOW WOULD YOU DO IT?
- 23. DEMO TIME! A Todo Application… ALMOST
- 25. VM / container Timeseries Database Application Instance Agent SDK Logging Database Https endpoint Visualization Engine Your Dashboards Query Engine Your Alerts Streaming Data Engine
- 26. Two more things “YOU CAN USE THE DEMOS!” “AND YOU CAN USE THE DEMOS!” “EVERYBODY CAN USE THE DEMOS!” DASHBOARDS AND ALERTS AS CODE
- 27. DO TRY THIS AT HOME! HENRY BEEN Independent Devops & Azure Architect E: consultancy@henrybeen.nl T: @henry_been L: linkedin.com/in/henrybeen W: henrybeen.nl