Monitoring your JHipster Applications

JHipster provides several features to get started with the monitoring of your applications :

A “Logs” page to let you adjust log levels at runtime
Metrics collection and instrumentation with Dropwizard Metrics
A special “Metrics” page to vizualize those metrics.

JHipster Metrics page

However, this page can only show you the current value of those metrics whereas users would want to monitor the evolution of those values over time.

Therefore JHipster applications can be configured to forward their metrics to an external monitoring system where they can be graphed over time and analyzed.

To achieve this, JHipster provide :

The JHipster Console, a custom monitoring solution based on the ELK stack and fully integrated with JHipster.
Metrics exporters for JMX, Graphite and Prometheus

Configuring your apps for log and metrics forwarding to a remote server

Forwarding logs to the JHipster Console

To configure a JHipster application to forward their logs to JHipster Console, enable logstash logging in their application-dev.yml or application-prod.yml:

jhipster:
    logging:
        logstash:
            enabled: true
            host: localhost # If using a Virtual Machine on Mac OS X or Windows with docker-machine, use the Docker's host IP here
            port: 5000
            queueSize: 512

To configure metrics monitoring, enable metrics log reporting in your JHipster application:

jhipster:
    metrics:
        logs:
            enabled: true
    	    reportFrequency: 60 # seconds

Setting those properties will enrich your logs with metrics coming from Dropwizard metrics.

Forwarding metrics to a supported monitoring system (JMX, Graphite, Prometheus)

Forwarding metrics to alternative systems is also supported and can also simply be enabled in your YAML configuration files.

jhipster:
    metrics:
        jmx.enabled: true
        graphite: # Send metrics to a Graphite server
            enabled: true
            host: localhost
            port: 2003
            prefix: jhipster
        prometheus: # Expose Prometheus metrics on the /prometheusMetrics endpoint
            enabled: true
            endpoint: /prometheusMetrics

Introducing the JHipster Console

The JHipster Console is a monitoring tool based on the ELK Stack. It provides ready-to-use dashboards and analytics tools to have a real-time overview of your infrastructure’s performance.

The ELK stack is composed of:

Elasticsearch for indexing the data (logs and metrics)
Logstash to manage and process the logs received from the applications
Kibana to visualize the logs with a nice interface

The JHipster Console is a Docker-based project that adds features on top of the official Elasticsearch, Logstash and Kibana Docker images. We have made a few visual changes to Kibana and set-up useful dashboards, so that you can get started to monitor your JHipster applications in minutes instead of the hours that would be needed to set up your own monitoring infrastructure.

JHipster Console Monitoring Dashboard

Setting up JHipster Console

If you already have a JHipster microservice architecture set up with the Docker Compose workflow, the JHipster Console can be automatically set up by the Docker Compose sub-generator.

If you are using the monolithic version of JHipster, you can get the JHipster Console’s Docker-Compose file from GitHub or with the following command:

curl -O https://raw.githubusercontent.com/jhipster/jhipster-console/master/bootstrap/docker-compose.yml

Then you will be able to start the console with:

docker-compose up -d

It will start Elasticsearch, Logstash, Kibana and ElastAlert all at once. You will then be able to access the JHipster Console at http://localhost:5601. It should automatically receive logs from your applications if they have been correctly configured to forward their logs and metrics to Logstash.

Warning: if you use docker-machine to create the Docker host, instead of http://localhost:5601 please use your Docker's host IP here i.e., http://<Dockerhostip>:5601

To stop everything, run:

docker-compose stop

Once stopped, you can remove the containers if you don’t intend to start them again:

docker-compose rm

You can combine the two previous commands in one by running: docker-compose down.

Using JHipster Console

Once your application is running with logs and metrics forwarding enabled, you can view a dashboards by clicking on the Load Saved Dashboards icon ( ) in the Dashboard tab.

Tip: If you encounter the following error with dashboards: Cannot read property 'byName' of undefined, try refreshing the logstash-* index pattern field list under Settings > Indices using the yellow refresh button ()

You can also use Kibana’s Discover and Visualize tabs to explore your data and create new visualizations. To understand how to use Kibana’s interface effectively please refer to its official documentation in particular the Discover, Visualize and Dashboard sections of the Kibana User Guide.

JHipster Console JVM Dashboard

Data persistence with docker volumes

When using JHipster Console you can enable docker volumes in the docker-compose.yml file by uncommenting the appropriate lines. Those volumes are used to share data between containers and the host. They will persist data and configuration even if containers are removed from your system.

Elasticsearch has its data saved to log-data/
Logstash loads its configuration from log-conf/logstash.conf, you can edit this file to add new parsing rules for data received by logstash on UDP port 5000.
Kibana loads dashboards description files in dashboards/ on each startup.

Warning: If you are using Docker Machine on Mac or Windows, your Docker daemon has only limited access to your OS X or Windows file system. Docker Machine tries to auto-share your /Users (OS X) or C:\Users\<username> (Windows) directory. So you have to create the project folder under these directory to avoid any issues with volumes.

Save your custom searches, visualizations and dashboards as JSON for auto import

Searches, visualization and dashboards created in Kibana can be exported using the Settings > Objects menu. You can then extract the JSON description of a specific object under the _source field of the export.json file. You can then put this data in a JSON file in one of the jhipster-console/dashboards sub-folder for auto-import.

If you have created useful dashboards and visualizations for your JHipster applications please consider contributing those back to the community by submitting a Pull Request on the JHipster Console’s GitHub project.

Alerting with Elastalert

JHipster Console comes with built-in alerting by integrating Elastalert, an alerting system that can generate alerts from data in Elasticsearch. Elastalert is simple to use and able to define complex alerting rules to detect failures, spikes or any pattern based on an Elasticsearch Query.

Enable alerting

To enable alerting, setup the jhipster-alerter container by adding the following lines to your docker-compose.yml.

jhipster-alerter:
    build: jhipster/jhipster-alerter
    # Uncomment this section to load your alerting configuration for a volume
    #volumes:
    #    - ./alerts/config.yaml:/opt/elastalert/config.yaml
    #    - ./alerts/rules/:/opt/elastalert/rules

Configure alerting

Elastalert configuration can be modified in alerts/config.yaml. For example, you can configure the alerting frequency and the buffer period, by changing the following properties:

run_every:
    minutes: 1
buffer_time:
    minutes: 5

Then you will need to write some rules that define when alerts will be thrown.

Write alertings rules

To define new alerts, add new YAML rule files in alerts/rules and then test them over past data with:

./test-alerting-rule.sh rule.yaml

Note that those YAML files should have a .yaml file extension. Read more on how to write rules at Elastalert’s official documentation.

Alerting dashboard

Go to localhost:5601/app/kibana#/dashboard/alerting-dashboard to see the history of all your alerts.