![]() ![]() ProxyPass /metabase/ ProxyPassReverse /metabase/ ProxyPassReverseCookiePath /metabase/ Now configure Apache to be able to access Metabase with http(s)://fqdn/metabase/ by creating the file /etc/httpd/conf.d/nf with the following content: #set proxy for metabase Podman generate systemd -new -name metabase -f RHEL8), you need to generate a systemd file for the podman container and then register it: cd /etc/systemd/system/ To start up the Docker instance automatically at reboot, register it with systemctl enable docker (if Docker is installed, e.g. Now start the docker with the following parameters: docker run -d -p 3003:3000 \ GRANT ALL PRIVILEGES ON metabase.* TO IDENTIFIED BY '********' ![]() ![]() Then remove this test configuration again with docker rm /metabase.įor production use, you should use an external database to get data persistence – I recommend using the mysql instance already used by GLPI, where you then prepare this DB: CREATE DATABASE metabase CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci If it doesn’t start up, you can find some logs with further information using: docker logs -f metabase (in RHEL8 with podman: podman images and podman ps) Here we use port 3003 because port 3000 is already in use by Grafana in a standard configuration. Then the docker image can be run in its standard configuration with: docker run -d -p 3003:3000 -name metabase metabase/metabase The simplest way to run Metabase is to use its preconfigured docker image: yum install docker So here I would like to give you some hints for a painless installation and first setup of Metabase and its GLPI plugin. Several articles are already available that present the use of Metabase in GLPI, but they miss some practical parts. Statistics from Metabase can be displayed directly in a GLPI dashboard, and the database structure, with all its foreign keys, can be exported to Metabase with one click. In between these two extremes we found Metabase, an Open Source BI tool which is quite easy to install and set up, and that can be integrated into GLPI via the plugin of the same name. Many companies use powerful, but heavy BI tools, which can only be configured by a few key users or external consultants. In the popular OSS asset management system GLPI (which is also contained in NetEye), the dashboards that have been available since version 9.5 give a good overview of the contents of the CMDB, but are hard to configure. Rigor in manual data insertion and the careful integration of automation processes (such as integrations with other tools, network scans, and inventory agents) are the backbone of successful asset management.Ī comprehensive and appealing application of data reporting and visualization would be a huge aid in getting and sharing an overview of all the data and for spotting inconsistencies. The key task is to keep all this data consistent and up to date. ![]() 2023 Mirko Morandini Asset Management, Unified Monitoring Using GLPI with the Metabase Open Source BI Tool for Visualizing Rich Reports and DashboardsĪsset management/CMDB tools play (or should play!) a central role in IT operations and management, gathering data from hardware assets on contracts, software licenses, network configurations, tickets and many more. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |