An introduction into monitoring & logging, for developers. Some theory, a discussion of what to monitor and what not and getting started implementing monitoring & logging using Microsoft Azure

1. Logging
Instrumentation
Dashboards
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?

9. DEVOPS POWERRRR

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?

18. PERCENTILES!
PERCENTILES!
PERCENTILES!

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

24. AddTodo
DeleteTodo
CompleteTodo
UncompleteTodo
GetAllTodos
AddTodoProcessor
DeleteTodoProcessor
CompleteTodoProcessor
UncompleteTodoProcessor IsFeatureFlagEnabled
SQL Database

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