This section briefly describes currently implemented features. For details on a certain feature, follow detailed corresponding description page.

Features planned to be implemented in future releases are listed in section Roadmap.


There are 2 options to install and run ogamma Visual Logger: using Docker image, and using distribution package.


Docker image of the ogamma Visual Logger for Linux containers is available at Docker Hub.

Docker-compose.yml file is available at GitHub here.

For details on how to deploy Docker images, please refer section Getting Started.

Distribution packages for various target platforms.

ogamma Visual Logger is distributed as portable zip file for various target OSs. For details on installing from distribution packages, please refer section Deploy. After downloading, unpack the archive, adjust basic configuration settings following section Configure, and run executable.


  • Web GUI

    Web based GUI is provided to edit OPC UA Server connection settings, browse server address space, modify data collection parameters such as publishing interval, sampling rate, deadband, queue size.

  • Bulk configuration.

    Import and export of configuration settings from/to CSV files using SQL server tools is possible.


ogamma Visual Logger can connect to OPC UA Servers and collect data for configured variables using subscriptions and monitored items mechanizm. To serve SimpleJson requests coming from Grafana, it can also retrieve real time data using Read requests, and historical data using HistoryRead requests.

Some highlithgs of OPC UA connectivity features are listed below:

  • opc.tcp protocol with binary encoding
  • None-secure and secure connections.
  • Collection parameters are configurable through Web GUI.


Once collected, data can be stored in persistent data storage. For list of suported databases and on information how to installa and configure them refer the section Time-Series Databases.


To visualize real time or historical data, open source visualization tool Grafana is used.


Once stored in persistent storage, data can be analized by using standard SQL queries.


  • Connection errors reported in detail with popup messages on GUI.
  • Application level and OPC UA SDK level log files are available via Web GUI.