AboutKimai is a free open source timetracker. It tracks the time you spend with various pre-set projects and prints out a summary of your activities on demand. The automated docker Kimai time tracker image “linuxconfig/kimai” can be used to instantly deploy the Kimai time tracker on your docker hosts.
ConfigurationThe Kimai runs on Debian GNU/Linux system featuring Apache web server, MariaDB ( MySQL ), database and PHP5. After creating a docker container based on “linuxconfig/kimai” docker image, a port 80 will be exposed which can be access on the docker host for an immediate Kimai web configuration/installation as well as later access.
Configured MySQL users:passwords:
- root:"empty password"
DeploymentThe below command can be used to download and create a new docker container called
kimaiand link your docker host system's port 80 with container's exposed port 80.
# docker run -d --name=kimai -p 80:80 linuxconfig/kimai
UsageOnce you deploy a new docker
kimaicontainer using the above command, you can immediately access its installation wizard by pointing your browser to
http://localhost. From here, simply follow Kimai's installation wizard by using the configuration settings provided above. Once your installation is complete Kimai will complain about the existence of the
installerdirectory. To stop this message from appearing simply remove
# docker exec kimai rm -fr /var/www/html/installer
Change MariaDB PasswordUse the following command to update or reset MariaDB user password. The below command will set a new
# docker exec -it kimai mysqladmin -uadmin -ppass password abc123To create a new database eg.
# docker exec -it kimai mysqladmin -uadmin -ppass create kimai2
Backup DatabaseIn order to be able backup MySQL database from a docker host we need to expose MySQL port locally when creating a new docker container. Example:
# docker run -d --name=kimai -p 80:80 -p 4444:3306 linuxconfig/kimaiAfter that we are able to simply create a database backup with:
# mysqldump --host=127.0.0.1 --port=4444 -u admin -ppass kimai > kimai.sql