Microservices architecture has many benefits. But it comes at a cost. Running microservices and monitoring what’s going on is tedious. That’s why MicroProfile adopts monitoring as a first-class concept. In this session, learn how MicroProfile runtimes collect metrics and how to seamlessly collect them with tools like Prometheus and Grafana. Learn how MicroProfile makes it easy to connect information about interrelated service calls, how to gather the information and analyze system bottlenecks, how to deploy and scale MicroProfile applications with Kubernetes and how to react to their health status to detect and automatically recover from failures.

1. Deploy, monitor, and take control of
your micro-services with MicroProfile

2. • How do you monitor this?
• Observability
Octo Blog

3. What You’ll Learn Today
• Metrics Background
• MicroProfile: Metrics - Fault Tolerance
• Application Metrics - Prometheus - Grafana

4. Rudy De Busscher
• Payara
• Service team
• JSR-375
• MicroProfile committer
• Committer in Eclipse EE4J groups - Jakarta EE
• Java EE Security API Expert group member
@rdebusscher
https://blog.payara.fish/
https://www.atbash.be

5. Observability
• Measure of the internal states of a system
• Monitor system(s)
• Metrics
• Tracing
• Health
• Data on the behaviour of systems
• Proactive
• Automation
• Application Performance Management (APM)

6. Metrics
• Telemetry data
• Gather data and collected centrally for monitoring
• Just collecting data
• No decisions made
• Collect upfront
• Data need to be available when investigation needed
• Start when there are already issues?
• Base line

7. Tracing
• Understanding your application’s behaviour
• Trace single client request
• Details of request flowing though different micro-services
• Debugging purposes
• Finding bottlenecks
• Monitoring

8. Health
• Mostly based on metrics
• Kill the server?
• “Treat your servers like cattle not pets”

9. MicroProfile
• MicroProfile can make your Java EE application more MicroService-ish
• Specifications for
• Configuration
• TypeSafe Rest Client
• Security (JWT Auth)
• Metrics
• OpenTracing
• Fault tolerance
• Health
• OpenAPI
• …

10. Test system
Payara
Server
Prometheus Grafana
Time series DB
Graphics
Dashboards
Expose metrics
Using Docker containers

11. Setup demo environment
• Creating containers
• Connecting them together
• ‘service’ simulation
• Create load through ‘bad’ parallel Prime values calculation.

12. Demo

13. MP Metrics
• Expose metrics with Rest endpoint
• Built on CDI only
• Included in MicroProfile 1.2+
• Automatic instrumentation
• No developer code required
• Integration with other MicroProfile specs
• Like Fault Tolerance
• Custom developer metrics

14. MicroProfile Metrics
• /metrics endpoint
• Prometheus or JSON format
• Different categories
1. System based (default)
2. On events indicated by developer
3. On Fault Tolerance events.
4. Custom defined (business related)

15. • Why Not JMX?
• Polyglot nature of Micro-services
• JMX difficult for non-java systems.
MicroProfile metrics

16. Default MP Metrics
• Required by specification
• System based
• CPU
• Memory - Garbage Collection
• Threads
• Class count
Freepik
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17. Prometheus
• Open Source
• Started by SoundCloud in 2012
• Now Cloud Native Computing Foundation.
• Multi-dimensional data model with time series
• Query Language
• Pull data
• Alert Manager

18. Prometheus alternatives
• Graphite
• Need to push metrics to it
• Influx DB
• Needs rest of stack (Telegraf - Chronograf - Capacitor)

19. Grafana
• Open Source tool for visualization
• query, visualize, alert on
• For time series

20. • Kibana
• Recent improved support for time-series
• Works only on top of ElasticSearch
Grafana alternatives

21. On events
• Invocation Count
• @Counted
• Execution time information
• @Timed
• @Metered
• More detailed information with Tracing
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22. Fault Tolerance
• Number of retries
• @Retry
• @CircuitBreaker
• Open, Half-Open, Closed
• @BulkHead
• Accepted, Rejected
• @Callback
• # calls
Freepik
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24. Developer defined
• Custom defined values
• @Gauge
• On field or getter
• If business value, store them somewhere
Freepik
4

25. Kubernetes
• Orchestration
• Docker-compose
• Ideal for smaller ‘installations’
• Open-Source Platform to Manage containers
• Not only docker containers
• Core tasks
• Deployment
• Scale
• Monitoring

27. Kubernetes Monitoring
• Metrics
• Metrics for k8s processes/actions
• Metrics-server
• Scaling
• Horizontal Pod scaling (kubectl autoscale )
• Monitoring
• Restart pods
• Keep system ‘healthy'

28. K8s monitoring
• Demo
• Kill server
• Automatic recovering

29. Demo
K8s monitoring
• K8S
• Kill server/container/pod
• Automatic recovering
• Prometheus within k8s

30. Take aways
• Get Metrics from your app/‘server’
• Connect to Prometheus
• Show time series with Grafana
• Different types of metrics
• System
• ‘Events’
• From other MP
• Kubernetes
• Keep app healthy

31. Code
• MicroProfile
• https://microprofile.io
• Demo code
• https://github.com/rdebusscher/mp-metrics-demo

32. Q & A

33. Thank You
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source software: Payara Server or Payara Micro
https://payara.fish/downloads
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