Our architecture migration from a monolithic to a distributed system at dmTECH entailed a lot of challenges. One of the main topics was observability. An increasing distribution of the systems demands for centralized logging to correlate events and analyze business processes. Dependencies of services can be tracked by request based tracing. Metrics and monitoring are prerequisites to capture the reliability of applications and to take action on anomalies. Establishing a devops culture the product team is forced to face the challenges as every member of the team has holistic responsibility of their product. In our talk we present some tools to handle the aforementioned challenges, especially those which fit best for our Spring-Boot-Stack.

2. 3 Amigos

3. “Where is my order?“
“Why is the cart slow?“

5. What's the deal?
Where is the bu?

6. Drawback of Resilience

7. Known Unknowns
v.
Unknown Unknowns

8. O11y
to the rescue

9. Observe ability

11. Building Blocks
Centralized Logging
Metrics
Tacing

13. Goal
be epared
to answer the why

18. Collecting and storing data over a
period of time

19. Readers Perspective

20. Log Level
log.debug -> log.forTestPurpose
log.info -> log.asExpectedByDefault
log.warn -> log.toInvestigateTomorrow
log.error -> log.wakeMeUpInTheMiddleOfTheNight

21. Log Rotation

22. Unstructured Log

23. Structured Log

24. Mapped Diagnostic Context
MDC.put("CartEntry", cartEntry.toString());

25. Debugging

26. Insight for Non-Dev

27. Container

28. Centralized Data Correlation

30. Inspect and Adapt
xisting Knowledge
Configuration
Adaptability
Dependency
OpenSource

43. Data obtained from measuring
events
Response Time
Request Rate

44. Explicit instrumentation

45. Tools
Actuator natural choice for Spring Boot apps
Since 2.0 based on Micrometer.io
Backport available for Spring Boot <2.0

46. Counter

47. Gauge

48. Timer

49. Usage

50. Transport
Application metrics need to be exported

51. Dimensional vs Non-dimensional
http_server_requests_seconds_count{status="200"}
http.server.requests.status.200

52. Fallacies with probabilities
0.99
100
≈ 0.37

62. Request scoped information

63. Correlation via unique IDs

64. Spans and Traces

65. Span Propagation

66. Spring cloud sleuth
Tracing instrumentation for Spring Boot apps

67. What you get
Span/Trace-Id generation
Log integration
API for managing custom spans
Zipkin integration