Features¶
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.
Deploy¶
There are 2 options to install and run ogamma Visual Logger for OPC: using Docker image, and using distribution package.
Docker.¶
Docker image of the ogamma Visual Logger for OPC 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 Setup using Docker.
Distribution packages for various target platforms.¶
ogamma Visual Logger for OPC 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.
Activate¶
Starting from version 0.7.0, ogamma Visual Logger for OPC requires activation using software license key (free for Community and Academic Editions). For instructions on how easily this can be done, please refer to section Activate.
Configure¶
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.
Only authenticated and authorized users can view and change configuration settings.
Communication with configuration backend server can be established over secured connection (https protocol is supported).
Bulk configuration.
Import and export of configuration settings from/to CSV files using SQL server tools is possible.
Collect¶
ogamma Visual Logger for OPC can connect to OPC UA Servers and collect data for configured variables using subscriptions and monitored items mechanizm. Variable values can also be of complex data type. 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.
OPC UA Session’s user authentication (identity token types
UserName/Password
andAnonymous
are supported).Collection parameters are configurable through Web GUI.
Note
If you need to collect data from classic OPC DA Servers, it is possible too, using third party protocol converter applications, like Matrikon OPC UA Tunneller.
Store and Forward¶
Once collected, data is temporarily stored in the persistent file-based Local Storage, and then forwarded to the destination time-series database. This provides guaranteed delivery of data even in cases of long connection interruptions with the time-series database.
For the list of supported time-series databases and on information how to install and configure them refer the section Time-Series Databases.
Visualize¶
To visualize real time or historical data, open source visualization tool Grafana
is used.
Analyze¶
Once stored in persistent storage, data can be analized by using queries. Query language depends on type of selected time-series database: for PostgreSQL/TimescaleDB it is standard SQL, for InfluxDb and Apache Kafka - their own query languages.
Troubleshoot¶
Connection errors reported in detail with popup messages on GUI.
Application level and OPC UA SDK level log files are available via Web GUI.
Latest values, timestamps and status codes returned for monitored variables by OPC UA Servers are displayed in Web GUI.
Status of the connection with the time-series database and metrics on number of collected values, number of stored in the Local Storage and forwarded to the destination database values, and other useful information can be viewed in the
Statistics
dialog window.