Monitoring JHipster applications
with the JHipster Console
with the JHipster Console
Pierre Besson
JHipster Conf, June 21th 2018
Who am I ?
- FullStack & DevOps @IpponTech
- JHipster core team member
- 🍃 Spring
- 🐳 Docker
- ☸️ Kubernetes
Introduction to microservice monitoring
Problems
Solutions
The JHipster Console
problems when monitoring microservices
- Distributed system -> More complex to observe
- Logs are dispersed in many log files
- Hard to locate the microservice that caused a problem
- Hard to follow the chain of requests
- 🐇/🐢 Studying latency is hard
- 💂 Resiliency mechanism are hard to configure properly
The solutions
the 3 ways of Observability
- Logs : discrete event
- Metrics : numerical values (business or technical)
- Traces : chains of calls in the system (spans)
- Store everything in one place, with proper metadata
- Use a search engine to query and aggregate monitoring data
- Visualize using graphs and dashboards
- Navigate around highly correlated data
The JHipster Console
jhipster.tech/monitoring/
- Setup the ZELK stack (Zipkin, Elasticsearch, Logstash, Kibana) in docker
- Enable reporting from any JHipster app with a few properties
- Logs + metrics forwarded with logback-logstash-encoder
- Traces are forwarded to Zipkin using Spring Cloud Sleuth
- Logs are enriched with trace information (Trace ID)
- Data is stored in Elasticseach for a certain number of days (Curator)
JHipster Console Architecture
