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https://github.com/devsu/docker-tao
Docker images for building and running TAO Assessment Platform
https://github.com/devsu/docker-tao
Last synced: 14 days ago
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Docker images for building and running TAO Assessment Platform
- Host: GitHub
- URL: https://github.com/devsu/docker-tao
- Owner: devsu
- License: mit
- Created: 2020-08-21T19:46:29.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-07-20T08:22:31.000Z (over 3 years ago)
- Last Synced: 2024-11-12T01:12:56.025Z (2 months ago)
- Language: Dockerfile
- Size: 35.2 KB
- Stars: 3
- Watchers: 6
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# docker-tao
Docker images for building and running [TAO Assessment Platform](https://www.taotesting.com/)
## Usage
The image is published in docker hub at devsu/tao. The easiest way to run tao is using docker-compose.
1. Clone this repo (or just copy the files in the `example` folder).
2. Modify the `tao/docker-compose.yml` and `tao/nginx` according to your needs.
3. Then just run `docker-compose up` from the `example` folder.
Then just head to http://localhost to start installation.
At installation make sure that you choose the following folder to store data: `/var/lib/tao/data`. As you can see in `Dockerfile`, a volume has been defined for this folder.
Since this folder is created only in the `tao` image, it won't be accessible by the `web` container, which is good for security reasons.
If you don't want to use docker-compose, you can also install and run TAO using the following command:
```
docker run --env DB_HOST=https://example.org --env DB_NAME=myDB --env DB_USER=myDBUser --env DB_PASSWORD=myDBPass --env USER=myTaoAdminUser --env PASSWORD=myTenLengthAlfanumericTaoAdminPassword devsu/tao
```
It's necessary to define the next environment variables:
- `DB_HOST`: Database location. You can use a hostname like localhost or an IP address like 127.0.0.1.
- `DB_NAME`: Name of the database used to store data from TAO platform.
- `DB_USER`: Login to access to database.
- `DB_PASSWORD`: Password to access to database.
- `USER`: The login of the administrator to be created.
- `PASSWORD`: The password of the administrator. This password must alphanumeric with 10 characters length.
Other enviroment variables that you can define are:
- `FILE_PATH`: Path to where asset files should be stored. The default is /var/lib/tao/data.
- `DB_DRIVER`: Driver engine to connect TAO platform with a database. The default is pdo_mysql. You must add other engines as pdo_pgsql, pdo_sqlsrv or pdo_oci in the docker file in order to use it.
- `DB_PORT`: Network port used to connect database host. The default is 3306.
- `URL`: The URL to access to platform from web browser. The default is http://localhost but you use it other with https protocol once you defined in DNS configuration.
The image is using docker-compose-wait (https://github.com/ufoscout/docker-compose-wait/) in order to wait until have a successfull database connection and proceed to install the platform. The environment variables that we can define for this tool are:
- `WAIT_HOSTS_TIMEOUT`: Max number of seconds to wait for all the hosts/paths to be available before failure. The default is 30 seconds.
- `WAIT_SLEEP_INTERVAL`: Max number of seconds to sleep between retries. The default is 1 second.
- `WAIT_HOST_CONNECT_TIMEOUT`: The timeout of a single TCP connection to a remote host before attempting a new connection. The default is 5 seconds.
`WAIT_HOSTS` is the main variable used for docker-compose-wait to know which hosts needs to wait, but our image build this variable automatically from DB_HOST and DB_PORT variables.
## Approach
The `tao` image is built using [multi-stage builds](https://docs.docker.com/develop/develop-images/multistage-build/).
- The **builder** image downloads the code and install all required packages
- The **runner** image copies the code generated by the builder and installs the runtime dependencies.
The runner is a `php-fpm` image, and thus it requires a **nginx** instance in front of it to serve the application.
The `example/docker-compose.yml` shows how to use it. It defines 2 services:
- **tao**: The container that will run the application.
- **web**: An nginx web server.
Both images share a named volume, which contain the application code.
All images are built in top of Linux alpine, to avoid issues of different ids for the `www-data` user.
## Building TAO
As you can see in the Dockerfile, TAO is built from the source code releases at https://github.com/oat-sa/package-tao/releases.
It's published in docker-hub at https://hub.docker.com/repository/docker/devsu/tao, but if you want, you can build it yourself.
```
docker build --target builder -t tao
```
TAO platform is configured to use the latest tao version at moment, but you can easily change the version by passing the `TAO_VERSION` argument.
```
docker build --target builder -t tao --build-arg TAO_VERSION=3.3-rc02
```
The version must match the version used in the name of the source code zip file.
## Development
If you want to test the docker files as you change them, you need to use the `docker-compose-dev.yml` file instead.
```
docker-compose -f docker-compose-file-dev.yml up --build
```
## Credits
Thanks to [Open Assessment Technologies](https://www.taotesting.com/about-us/) for the awesome work, and for sharing it with the world.
Inspired on https://github.com/Alroniks/docker-tao.
This repo is maintained by Devsu, and it's used to take assessments to [find the best software developers](https://devsu.com/about-us/).
## License
MIT License - Copyright (c) 2020 Devsu LLC.