MicroXchg: Logging and Metrics in Microservice Architectures

You can find more information about this talk at https://www.innoq.com/en/talks/2016/02/microxchg-2016-microservices-logging-metrics/

1. Don’t Fly Blind Logging and Metrics in Microservice Architectures Tammo van Lessen | tammo.vanlessen@innoq.com Alexander Heusingfeld | alexander.heusingfeld@innoq.com #microxchg #logging #metrics www.innoQ.com
2. The Talk Today > Motivation > Distributed Logging > Distributed Metrics > Conclusions
3. Breaking the monolith
4. If you review a monolithic application … © innoQ/Roman Stranghöner
5. …and look into the black box… © innoQ/Roman Stranghöner
6. …you’ll find it consists of multiple Bounded Contexts. © innoQ/Roman Stranghöner
7. If you’re able to treat every Bounded Context as a separately deployable, independent component… © innoQ/Roman Stranghöner
8. … you’ll have a self-contained system - which can lead to a 
 microservice architecture Introduction to self-contained systems: https://www.innoq.com/de/links/self-contained-systems-infodeck/
9. A Broken Monolith
10. Architectural Decisions > Domain Architecture
 
 > Macro Architecture
 
 > Micro Architecture
11. Logging in a Distributed Environment
12. Requirements > Apply a well-thought logging concept > Aggregate logs in different formats from different systems > Search & Correlate > Visualize & Drill-down > Alerting
13. Use Thread Contexts / MDCs %-5p: [%X{loginId}] %m%n ThreadContext.put("loginId", login); logger.error("Something bad happened!"); ThreadContext.clear(); + Layout: ERROR: [John Doe] Something bad happened! Log:
14. Use Thread Contexts / MDCs { "@version" => "1", "@timestamp" => "2014-04-29T14:21:14.988-07:00", "logger" => "com.example.LogStashExampleTest", "level" => "ERROR", "thread" => "Test worker", "message" => "Something bad happened!", "Properties" => { "loginId" => "John Doe" } } ThreadContext.put("loginId", login); logger.error("Something bad happened!"); ThreadContext.clear(); + JSON Layout Log:
15. Define QoS for Log Messages > Log messages may have different QoS > Use Markers and Filters to enable fine- grained routing of messages to dedicated appenders > Use Filters and Lookups to dynamically configure logging https://www.innoq.com/en/blog/per-request-debugging-with-log4j2/
16. Requirements > Apply a well-thought logging concept > Aggregate logs in different formats from different systems > Search & Correlate > Visualize & Drill-down > Alerting
17. Logstash Architecture
18. Default ELK-Stack Setup Shipper / 
 Logstash Forwarder Storage & Search Visualize https://www.elastic.co/products/logstash Push
19. Distributed Logstash Setup Shipper / 
 Logstash Forwarder Broker Indexer Storage & Search Visualize https://www.elastic.co/products/logstash Push Pull
20. Requirements > Apply a well-thought logging concept > Aggregate logs in different formats from different systems > Search & Correlate > Visualize & Drill-down > Alerting
22. Requirements > Apply a well-thought logging concept > Aggregate logs in different formats from different systems > Search & Correlate > Visualize & Drill-down > Alerting
23. Filter Log Stream For Alerts input { … } filter { if [message] =~ /.*(CRITICAL|FATAL|ERROR|EXCEPTION).*/ { mutate { add_tag => "alarm" } } if [message] =~ /.*(?i)ignoreme.*/ { mutate { remove_tag => "alarm" } } } output { if [type] == "production" { if "alarm" in [tags] { pagerduty { description => "%{host} - %{log_level}: %{log_message}" details => { "timestamp" => "%{@timestamp}" "host" => "%{host}" "log_level" => "%{log_level}" "message" => "%{log_message}" "path" => "%{path}" } … } } } }
24. Logging is cool… And I can use it to collect metrics as well, right? © http://www.flickr.com/photos/dkeats/3128150892/
25. Logging is cool… And I can use it to collect metrics as well, right? Watch out! © http://www.flickr.com/photos/dkeats/3128150892/
26. Metrics
27. Kinds of Metrics
28. Kinds of Metrics > Business Metrics
29. Kinds of Metrics > Business Metrics > Application Metrics
30. Kinds of Metrics > Business Metrics > Application Metrics > System Metrics
31. Why should a developer care?
34. Types of Metrics
35. Gauges A gauge is an instrument that measures a value. © https://secure.flickr.com/photos/profilerehab/4974589604/
36. Counters A counter is a simple incrementing and decrementing integer. © https://secure.flickr.com/photos/mwichary/2273099939/
37. Meters A meter measures the rate at which a set of events occur. © https://www.flickr.com/photos/springfieldhomer/1244320899
38. Histograms A histogram measures the distribution of values. © https://secure.flickr.com/photos/boulter/3998842325/
39. Timers A timer is a histogram over a duration. © https://secure.flickr.com/photos/psd/4686988937/
40. Distributed Metrics Architecture Measure Collect & Sample Store Query & Graph Anomaly Detection Alerting CEP Dashboards
41. Grafana for Technicians © http://grafana.org/
42. Grafana for Technicians © http://grafana.org/
43. Dashing for Management Dashboards © https://shopify.github.io/dashing/
44. + producer unaware of target + multiple targets possible + flexible interval - might miss short-lived services - requires service-discovery P T P Push + event-based de-/registration + routable event stream + producer pushes when ready - producer aware of target - packet-loss might be missed Pull P T P vs.
45. Some Recommendations > Think about what metrics are of importance for operating your application > Consider retention policies > Carefully design your dashboards > Think about non-standard graph types
46. Sample architecture
48. Conclusions > Create and document concepts for logging and metrics > Collect & aggregate distributed logs and metrics > Create dashboards tailored for your audience > Correlate your data to make conscious decisions > Don’t create your very own big data problem
49. Prevent the apocalypse! Logging shows events. Metrics show state. Don't fly blind! © http://www.flickr.com/photos/pasukaru76/5067879762
50. Tammo van Lessen | @taval tammo.vanlessen@innoq.com Alexander Heusingfeld | @goldstift alexander.heusingfeld@innoq.com Thank you! Questions?
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