A Java EE 8 web application for managing JAWS alarm registrations and notifications built with the Smoothness web template.
Alarm system registration data consists of locations, categories, classes, and instances. Collectively the data forms effective registrations.
- Grab project
git clone https://github.com/JeffersonLab/jaws-admin-gui
cd jaws-admin-gui
- Launch Compose
docker compose up
- Launch web browser
http://localhost:8080/jaws
Note: Login with demo username "tbrown" and password "password".
Note: The docker-compose services require significant system resources - tested with 4 CPUs and 4GB memory.
This application requires a Java 11+ JVM and standard library to run, plus a Java EE 8+ application server (developed with Wildfly).
- Install service dependencies
- Download Wildfly 26.1.3
- Configure Wildfly and start it
- Download jaws.war and deploy it to Wildfly
- Navigate your web browser to localhost:8080/jaws
Wildfly must be pre-configured before the first deployment of the app. The wildfly bash scripts can be used to accomplish this. See the Dockerfile for an example.
The following environment variables are required:
| Name | Description |
|---|---|
| BOOTSTRAP_SERVERS | Host and port pair pointing to a Kafka server to bootstrap the client connection to a Kafka Cluser; example: kafka:9092 |
| SCHEMA_REGISTRY | URL to Confluent Schema Registry; example: http://registry:8081 |
This project is built with Java 17 (compiled to Java 11 bytecode), and uses the Gradle 7 build tool to automatically download dependencies and build the project from source:
git clone https://github.com/JeffersonLab/jaws-admin-gui
cd jaws-admin-gui
gradlew build
Note: If you do not already have Gradle installed, it will be installed automatically by the wrapper script included in the source
Note for JLab On-Site Users: Jefferson Lab has an intercepting proxy
See: Docker Development Quick Reference
In order to iterate rapidly when making changes it's often useful to run the app directly on the local workstation, perhaps leveraging an IDE. In this scenario run the service dependencies with:
docker compose -f deps.yaml up
# OR if on JLab network use control system config with `jlab-deps.yaml` instead.
Note: The local install of Wildfly should be configured to proxy connections to services via localhost and therefore the environment variables should contain:
KEYCLOAK_BACKEND_SERVER_URL=http://localhost:8081
FRONTEND_SERVER_URL=https://localhost:8443
Further, the local DataSource must also leverage localhost port forwarding so the standalone.xml connection-url field should be: jdbc:oracle:thin:@//localhost:1521/xepdb1.
The server and app setup scripts can be used to setup a local instance of Wildfly.
- Bump the version number in the VERSION file and commit and push to GitHub (using Semantic Versioning).
- The CD GitHub Action should run automatically invoking:
- The Create release GitHub Action to tag the source and create release notes summarizing any pull requests. Edit the release notes to add any missing details. A war file artifact is attached to the release.
- The Publish docker image GitHub Action to create a new demo Docker image.
At JLab this app is found at ace.jlab.org/jaws and internally at acctest.acc.jlab.org/jaws. However, those servers are proxies for jaws.acc.jlab.org and jawstest.acc.jlab.org respectively. This app makes up one service in a set of services defined in a compose file that make up the JAWS system and deployments are managed by JAWS.