Deploy

ogamma Visual Logger for OPC can be deployed either as a Docker container, or as a Windows application, or as a Linux (Ubuntu 18.04) application. Also it is possible to install it as Azure Iot Edge Module.

Tip

After deployment, web based configuration GUI will be available at the address http://localhost:4880. To login, use default user name admin and password password. If you are using ogamma Visual Logger for OPC in production, reset password immedately using menu Account/Change Password.

Note

Web GUI of the ogamma Visual Logger for OPC is optimized and tested for screen resolution 1920x1080 in full size mode, in Google Chrome and Microsoft Edge. GUI layout might be disrupted in other combinations of browse and screen resolution. If this becomes blocking issue for you, please report it at https://github.com/onewayautomation/ogamma-logger/issues.

Setup using Docker

The easiest and guaranteed to work in minutes way to start using ogamma Visual Logger for OPC is running it as a Docker container. If you never tried to use Docker before, we encourage you to try to install and use this powerful technology. You can find instructions about how to install it at its home page.

Following below console commands assume that you use bash terminal in Linux hosts, and PowerShell in Windows hosts. If you don’t want to use PowerShell in Windows, it is possible to use regular windows command console too, but in this case some commands will need to be modified. For example, instead of using PowerShell variable for current folder ${pwd}, absolute path value should be used.

Pulling docker image of ogamma Visual Logger for OPC and running it.

Linux image of ogamma Visual Logger for OPC is hosted at Docker Hub and can be pulled by command:

docker pull ogamma/logger

Then you can start the container by command:

docker run --name ogamma-logger --hostname ogamma-logger -v ${pwd}/data:/home/ogamma/logger/data -e OVL_USER_ID='admin' -e OVL_USER_PASSWORD='password' -p 4880:4880 ogamma/logger

Warning

In production setup define custom values for default login credentials using environment variables OVL_USER_ID and OVL_USER_PASSWORD!

Using docker-compose.

ogamma Visual Logger for OPC can run as stand-alone application without other dependencies, if SQLite type databases are used to store configuration settings and to store time-series data. But very often PostgreSQL is used as a configuiration database, and time-series data can be stored in other databases, like TimescaleDB, InfluxDB or Apache Kafka. While these third-party dependencies can be installed and run independently, you can also use docker-compose files from product’s GitHub repository, to install them and run in just a few minutes.

Warning

Note that docker-compose files are not intended for production use as is. At least default user credentials must be modified to more secure values.

Easiest way to get all docker-compose files is to clone the repository to local folder by running command:

git clone https://github.com/onewayautomation/ogamma-logger

Tip

If you don’t have git installed, you can download it here.

As a result, repository files will be pulled into sub-folder ogamma-logger. In sub-folder docker of this folder you will find multiple files with extension .yml. Each of them intended to start specific application in its own Docker container. You can start desired set of containers by passing names of these files in docker-compose command.

For example, if you want to use TimescaleDB to store time-series data, and also use Grafana to visualize data, you can start them together with ogamma Visual Logger for OPC by running following below command from working directory ./ogamma-logger/docker

docker-compose -f docker-compose.yml -f portainer.yml -f timescaledb.yml -f grafana.yml up -d

Short description of used files follows below.

• docker-compose.yml describes container service for ogamma Visual Logger for OPC,

• portainer.yml starts Portainer, web based configuration and management tool for docker containers. With it, you can easily see list of running containers, stop, start and restart them, upgrade or re-create them, view usage statistics, logs, connect to them via terminal, and lot of other features are available.

• timescaledb.yml starts instance of TimescaleDB database server, where you can create a database to store time-series data, and also it can used as regular PostgreSQL database to store configuration data.

• grafana.yml - starts instance of Grafana version 8.0.3.

As a result, Docker images will be downloaded from Docker Hub, containers from those images will start, and components of ogamma Visual Logger for OPC and database with web based management tool will be available at the following below URLs:

• http://localhost:4880 : ogamma Visual Logger for OPC configuration GUI, where you can setup connections to OPC UA servers and define what variables to collect data for. Default credentials are admin / password.

  
  

• http://localhost:9000 : Portainer GUI.

  
  

• localhost:5432 - PostgreSQL database with TimescaleDB extension;

  Default credentials are: ogamma/ogamma.

  
  

• http://localhost:4888: PgAdmin web GUI, using which you can analyze historical data utilizing standard SQL queries.

  Default credentials are admin@ogamma.io/admin.

  
  

• http://localhost:3000: Grafana web GUI, using which you can visualize data from OPC UA Servers;

  
  

To stop all containers, use the command:

docker-compose -f docker-compose.yml -f portainer.yml -f timescaledb.yml -f grafana.yml down

In case if you want to use other database to store time-series data, add respective yml file.

Tip

If you choose to use PostgreSQL to store configuration settings, you can keep the file timescaledb.yml in the command arguments and use its corresponding service to store configuration database.

• confluent.yml - Apache Kafka distribution from Confluent, bundled with bunch of other services, as described at Confluent Platform Quick Start page.

  Once services start, Confluent Control Center will be available at http://localhost:9021

  
  

• influxdb.yml - InfluxDB version 1.8.6, will be available at localhost:8084, and management web application for InfluxDB 1.x, will be available at http://localhost:8085. For details on how to use it refer to project home page at https://timeseriesadmin.github.io/. No credentials are required to access the page.

  
  

• influxdb2.x.yml - InfluxDB version 2.0.7, web GUI will be available from the host machine at http://localhost:8086. To configure connection from ogamma Visual Logger for OPC which is running within Docker container to this instance of the Influx DB set Host field to influxdb2x and Port to 8086.

  You will need to initialize InfluxDB using its web interface at port 8086.

  Note

  InfluxDB 2 web GUI also provides tools to run queries, build dashboards with graphs, configure monitoring of data for specified conditions and generating alerts, etc. Refer to its documentation for more details at https://v2.docs.influxdata.com/v2.0/.

• mssql.yml - Micsofot SQL database server.

• mysql.yml - MySQL database server.

• mqtt.yml - MQTT Broker Eclipse Mosquitto.

• opcplc.yml - OPC UA simulation server (https://github.com/Azure-Samples/iot-edge-opc-plc). To connect to it from instance of the ogamma Visual Logger for OPC running as a Docker container you can use OPC UA enpoint URL opc.tcp//opcplc:50000.

  Note

  From the host machine it will not be available using opcplc as host name though, which might cause problems if you want to connect to it using OPC UA client running in your host PC. Refer to the Docker documentation on how to make it accessible from the host machine using host name.

• ovl-2.yml - example of running second instance of the ogamma Visual Logger for OPC.

Running all supported databases and demo OPC UA Server in Docker

To start all suported databases and demo OPC UA Server in containers, run this command:

docker-compose -f docker-compose.yml -f portainer.yml -f timescaledb.yml -f grafana.yml -f confluent.yml -f influxdb.yml -f influxdb2.x.yml -f mssql.yml -f mysql.yml -f mqtt.yml -f opcplc.yml up -d

To stop all containers run this command:

docker-compose -f docker-compose.yml -f portainer.yml -f timescaledb.yml -f grafana.yml -f confluent.yml -f influxdb.yml -f influxdb2.x.yml -f mssql.yml -f mysql.yml -f mqtt.yml -f opcplc.yml down

Note

You can also stop or start any one container independently, by passing corresponding .yml file name.

Setup in Windows

1. Install required prerequisites

a). Install Visual C++ 2019 redistributables (64 bit version)

Can be installed using installation file (vc-redist.x64.exe) included into the distribution package.

Latest downloads are available at https://support.microsoft.com/en-ca/help/2977003/the-latest-supported-visual-c-downloads

b). Install / Configure database to store time-series data.

Note

This step can be skipped if you plan to read real time and historical data from OPC UA servers directly, without storing values in database, or plan to store historical data in the SQLite database, which does not require installation.

For information on supported databases and how to install/configure them, refer to the section Time-Series Databases.

c). Install Microsoft ODBC Driver 17 for SQL Server.

If not installed already, install Microsoft ODBC Driver 17 for SQL Server from file msodbcsql.msi included into distribution package.

Note

This driver must be installed even if you are not using MS SQL Server as a time-series database.

2. Install ogamma Visual Logger for OPC

• Download zip file from https://onewayautomation.com/opcua-binaries/ogamma-logger-windows-4.0.3.zip

• Unzip.

• If required, modify settings in the configuration file, for example, http port number for Web based configuration GUI (default number is 4880), and settings to connect to the time-series database.

Note

By default ogamma Visual Logger for OPC is configured to use configuration file at location data/config.json (relative to the current working folder), althouth folder data does not exist after installation. The point is that it is recommended to use separate folder for all installation instance specific data, which is by default to be in folder data. When the application is started, it checks if configuration file exists in expected location, and if it does not exist, it copies original config.json file from original installation location. Therefore, if you want to use modify settings, create folder data, copy config.json file to it, and then modify file data/config.json.

3. Start ogamma Visual Logger for OPC.

Warning

Before starting ogamma Visual Logger for OPC first time in production setup, define custom values for default login credentials using environment variables OVL_USER_ID and OVL_USER_PASSWORD!

Open Windows command line console, navigate to the folder where ogamma Visual Logger for OPC files are unzipped, and start application ogamma-logger.exe. At the very first start, it might run some initialization steps in the database (for example, if PostgreSQL is used, it will create required tables in the PostgreSQL database). Before connecting to the frist OPC UA server (after adding it from GUI and attempt to browse), it will also generate OPC UA Application Instance Certificate, which might take some time.

The application has built-in web server to support web based GUI to configure it, and it will listen to http port of that configuration endpoint (port 4880). Windows operating system will pop-up dialog window asking for permission to listen on the port, you will need to allow it.

Tip

Configuration GUI will be aavailable to access from web browser at address http://localhost:4880, default user name and password are admin and password.

4. Running ogamma Visual Logger for OPC as a Windows service.

If you want to run ogamma Visual Logger for OPC as a WIndows service, you can use Server Manager available to donwload for free here.

5. Install Grafana

Note

This step can be skipped if you do not want visualize data.

To install Grafana, follow instructions at Download Grafana web page

Setup in Ubuntu 18.04 and Ubuntu 20.04

Distribution package for Ubuntu is available at https://onewayautomation.com/opcua-binaries/ogamma-logger-ubuntu1804-4.0.3.zip

To download and install it from terminal:

• Open terminal (keyboard shortcupt Ctrl+Alt+t can be used).

• Update package lists:

  sudo apt update
  

• Install tools wget and unzip:

  sudo apt install wget unzip
  

• Download distribution package:

  wget https://onewayautomation.com/opcua-binaries/ogamma-logger-ubuntu1804-4.0.3.zip
  

• Unzip it:

  unzip ogamma-logger-ubuntu1804-4.0.3.zip -d ogamma-logger
  

• Navigate to the folder where it is extracted to:

  cd ogamma-logger
  

• Unzip Python library:

  unzip ./python/python310.zip -d ./python/lib
  

• Install MS SQL ODBC libraries:

  sudo ./install-unix-odbc-11.sh
  

  Note

  This is required even if you do not plan to store data in MS SQL Server.

• Run ogamma Visual Logger for OPC:

  ./ogamma-logger
  

Warning

Before starting the application ogamma-logger first time in production setup, define custom values for default login credentials using environment variables OVL_USER_ID and OVL_USER_PASSWORD!

If application does not start, then check error messages in console. If required, adjust settings in the configuration file ./data/config.json and start application again.

Note

In default basic configuration file ./data/config.json field configDb is set to use built-in SQLite database.

• ogamma Visual Logger for OPC Configuration GUI will be accessiblie at address http://localhost:4880 Configuration GUI will be aavailable to access from web browser at address http://localhost:4880.

Setup in RedHat Enterprise Linux

Distribution package for Redhat is available at https://onewayautomation.com/opcua-binaries/ogamma-logger-rhel-2.1.15.zip.

To download and install it from terminal:

• Open terminal (keyboard shortcupt Ctrl+Alt+T can be used).

• Download distribution package:

  wget https://onewayautomation.com/opcua-binaries/ogamma-logger-rhel-2.1.15.zip
  

• Unzip it:

  unzip ogamma-logger-rhel-2.1.15.zip -d ~/ovl
  

• Navigate to the folder where it is extracted to:

  cd ~/ovl
  

• Install MS SQL ODBC libraries:

  sudo ./install-unix-odbc-11.sh
  

  Note

  This is required even if you do not plan to store data in MS SQL Server.

• Enable configuration endpoint port 4880 and run ogamma Visual Logger for OPC:

  firewall-cmd --zone=public --permanent --add-port 4880/tcp
  firewall-cmd --reload
  
  run-ovl.sh
  

Warning

Before starting the application ogamma-logger first time in production setup, define custom values for default login credentials using environment variables OVL_USER_ID and OVL_USER_PASSWORD!

If application does not start, then check error messages in console. If required, adjust settings in the configuration file ./data/config.json and start application again.

Note

In default basic configuration file ./data/config.json field configDb is set to use built-in SQLite database.

• ogamma Visual Logger for OPC Configuration GUI will be accessiblie at address http://localhost:4880 Configuration GUI will be aavailable to access from web browser at address http://localhost:4880.

Setup in Raspberry Pi.

Note

Currently, only Docker image with 32 bit OS is supported.

Prepare Micro SD card with 32 bit debian-bullseye OS.

• Using Raspberry Pi Imager, write the image to the SD card.

• Insert SD card into the Raspberry Pi device and start it.

• Configure OS: set up country, language, WiFi connection, interface preferences (SSH, VNC), etc.

• Install OS upgrades.

Install Docker and Docker Compose

curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker pi
sudo apt-get install -y docker-compose
sudo systemctl start docker
sudo systemctl status docker

If Docker service fails to start, rebooting of the device should help:

sudo reboot

Get docker compose files for ogamma Visual Logger for OPC and start it:

git clone https://github.com/onewayautomation/ogamma-logger.git
cd ogamma-logger/docker
docker-compose -f docker-compose-pi32.yml up -d

Optionally, you can also install Portainer service to manage containers:

docker-compose -f portainer.yml up -d

Install as Azure IoT Edge module.

To install the ogamma Visual Logger for OPC as Azure IoT Edge module, refer to the section How to deploy ogamma Visual Logger for OPC as Azure IoT Edge Module.

Installing older versions.

If you need help with installing older versions, please contact support.

Upgrading from older versions.

Note

Starting from version 2.2.0 valid Annual Maintenance and Upgrades License is required. Before upgrading of the application please check if your existing license allows to run the new version to which you are considering to upgrade to. If release date of the new version is no later than the date displayed in the First Activation Date field of the License Information dialog window, then no separate AMU License is required. Otherwise, you will need to purhcase the AMU License, contacting Support.

For details about this license please refer this section: Annual Maintenance and Upgrades License.

For information about how to install the AMU License please refer section Upload Annual Maintenance and Upgrades License..

Steps before upgrade.

• Before upgrading to the new version, stop existing application and create backup of your application data folder (usually sub-folder ./data) and backup of configuration database to avoid any data loss.

• If as a time-series database either InfluxDB or Confluent/Apache Kafka or MQTT Broker is configured, where either measurement and tags or topic name / key name are used, to make sure that the same values for those fields are used after upgrade as before upgrade, before starting upgrade process, in the Logged Variables table review current values for those columns, and remember what are the current values for some rows. Later, after upgrade, verify that the same measurement/topic name and tags/keys are used as before the upgrade.

Also, review and remember configuration settings for the time-series database.

Tip

As a precaution, to eliminate writing into the time-series database records with un-desired measurement/topic name, or tags/key name, before starting of the upgrade you can change configuration of the time-series database to use host name which does not exist.

• In version 2.1.0, for the Local Storage new database engine is used. Data migration from older version of the Local Storage to the newer version is not implemented. Therefore, before starting the upgrade, make sure that the Local Storage does not have data for significant time range. If connection with the destination time-series database is normal, then the Local Storage should have still not forwarded data for very short time (around 1 second or so) and this should nto be an issue.

Upgrading Docker container.

Note

In this section it is assumed that docker-compose files from Github project https://github.com/onewayautomation/ogamma-logger used.

• Open terminal and navigate to the sub-folder ogamma-logger

• Stop ogamma-logger container:

  docker-compose -f docker-compose.yml down
  

• Open file docker-compose.yml in text editor, and modify line which defines what image to use (image: 'ogamma/logger:1.2.5', or image: 'ogamma/logger:latest') to use the latest version of the ogamma Visual Logger for OPC (as of today, it is version 4.0.3): image: 'ogamma/logger:4.0.3'.

• Start the container:

  docker-compose -f docker-compose.yml up -d
  

• Process to the section Steps after upgrade.

Upgrading Windows and Ubuntu installations.

• Install ogamma Visual Logger for OPC into new location, but do not start it.

• Stop existing instance;

• Copy folder ./data from older installation to the new installation location;

• Start new instance. If required, it will upgrade config files and configuration database.

Steps after upgrade.

• If as a time-series database either InfluxDB or Confluent/Apache Kafka or MQTT Broker is configured, in the Logged Variables table check values in the column Measurement (for InfluxDB), or Topic Name (for Confluent/Apache Kafka and MQTT), and verify that they have the same values as before the upgrade. Also, check values in the column Tags (for InfluxdB), or in the column Key Name for Confluent/Apache Kafka, and verify that the same values as before the upgrade.

  If values are not as expected, revise settings in the time-series database configuration dialog window. Note that starting from version 2.0.2, options measurement, topicTemplate, tags, keyTemplate applied only if corresponding `` … Generion Mode`` field is set to Use JSON template ....

• Verify that data is being written to the time-series database. This can be done either by reading values back from the database using corresponding tools for that database, or by viewing historical data graphs in Grafana.

  Also, open dialog window Tools/Statictics and verify that the field TSDB Status has value connected, and values in the fields of groups Collected values and Stored values are increasing.

Versions the upgrade is supported from.

Upgrading from any previous version to the newer version is supported. Downgrading is not implemented.