Idako: Industrial Data Collector

Contents:

  • Introduction
  • Features
    • Deploy
    • Activate
    • Configure
    • Collect
    • Store and Forward
    • Visualize
    • Analyze
    • High Availability
    • Troubleshoot
    • Target Platforms
    • More features are coming
  • Licensing
    • Licence for Industrial Data Collector.
    • Annual Maintenance and Upgrades License.
    • Licenses of open source dependencies.
  • Deploy
    • Setup using Docker / Podman
      • Pulling docker image of Industrial Data Collector and running it.
      • Using docker-compose.
        • Short description of docker compose configuration files.
        • Starting multiple containers using multiple docker compose files.
      • Breaking change in Docker container version 4.2.0
    • Setup in Windows using the installer
    • Portable Setup in Windows
      • 1. Download portable distribution package
      • 2. Install required prerequisites
        • a). Install Visual C++ 2019 redistributables (64 bit version)
        • b). Install Microsoft ODBC Driver 18 for SQL Server.
        • c). Install / Configure database to store time-series data.
      • 3. Start Industrial Data Collector.
      • 4. Running Industrial Data Collector as a Windows service.
      • 5. Install Grafana
    • Setup in Linux
    • Setup in 64-bit Raspberry Pi.
    • Setup in Raspberry 32-bit Pi.
      • Prepare Micro SD card with 32 bit debian-bullseye OS.
      • Install Docker and Docker Compose
      • Get docker compose files for Industrial Data Collector and start it:
    • Installing as Kafka Source Connector on Confluent and Redpanda platforms.
      • Installing as Confluent / Kafka Source Connector
      • Installing as Redpanda / Kafka Source Connector
    • How to deploy Industrial Data Collector as Azure IoT Edge Module
      • Install Azure IoT Edge runtime in the device.
        • Install prerequisites.
        • Install Azure IoT Edge runtime
        • Provision IoT Edge device with its cloud identity (using symmetric key).
        • Restart IoT Edge runtime.
      • Deploy Industrial Data Collector
    • Installing older versions.
    • Upgrading from older versions.
    • Upgrading older Windows installations to version 4.2.0 or later.
      • Steps before upgrade.
      • Upgrading Docker container.
      • Upgrading Windows and Ubuntu portable installations.
      • Versions the upgrade is supported from.
  • Activate
    • Initial Activation
      • 1. Obtain activation key.
      • 2. Activate Industrial Data Collector
        • 2.1. Online activation.
        • 2.2. Offlie activation.
    • Upload Annual Maintenance and Upgrades License
    • Reactivate.
    • Upgrade with a key for different edition.
  • Configure
    • Application Instances.
    • Configuration settings: Introduction
      • Configuration files
      • Environment variables.
      • Configuration web GUI
    • Configuration steps.
      • 1. Connecting to the Configuration database.
      • 2. User authentication and authorization.
        • Built-in identity provider
        • 2.2. Authentication with JWT tokens
      • 3. Collector Configurations.
      • 4. Time-Series database connection settings.
      • 5. Configuration of the application instance.
      • 6. Configuration of the instances as High Availability Cluster Nodes.
  • Collect
    • Connections to OPC UA Servers.
    • Advanced connection settings.
      • Periodical reading and logging of variable values.
      • Enabling support for complex type values.
      • Browsing OPC UA Server nodes with large number of child nodes.
    • Connecting in secured mode and certificates.
      • Configuring Idako: Industrial Data Collector to trust to server instance certificates.
      • Configure OPC UA servers to trust Industrial Data Collector instance certificate.
    • Connections from Docker container.
    • Connecting to OPC UA Servers running in Docker container, accessed over VPN or NAT or using port forwarding.
    • Connecting to classic OPC DA Servers.
    • Browsing OPC UA Server address space and selecting variables to log.
      • Browsing and selecting of variables manually using web GUI.
      • Auto-discovery and selection of variables
        • Auto-discovery workflow
        • Python scripts that define auto-discovery logic
        • Debugging of Python scripts
    • Logged Variables table.
      • Columns.
        • Column Chooser
      • Grouping of logged variables
      • Filtering by OPC UA Server.
      • How to set default values for logging options.
      • Display real time data.
      • Other options.
      • Client-side deadbands.
      • Logging values of complex data type.
  • Write values to OPC UA Variables
  • Time-Series Databases
    • Common settings
      • Store and Forward options in the Instance Settings dialog
      • Options in the Time-series database connection settings dialog.
      • How to check data forwarding status.
      • Settings for OPC UA to TSDB mapping.
      • Handling of invalid UTF-8 strings.
    • SQLite
    • Snowflake
    • TimescaleDB/PostgreSQL.
      • Installation.
      • Configuration.
      • Mapping from OPC UA to SQL database, table and columns.
        • Schema of the values table.
        • Accessing Display Name or OPC UA Node Id of variables from time-series database of SQL type.
        • Writing time-series data to the table with name different than default name values.
      • Connection in secured mode
      • Using PostgreSQL instance hosted at Microsoft Azure
      • Using instance of TimescaleDB hosted by Timescale
      • Configuring retention policy in TimescaleDB.
    • InfluxDB version 1.7.
      • Installation.
      • Configuration.
        • Example file for automatic deployments.
        • Configuration using web GUI.
      • Mapping OPC UA to InfluxDb.
        • The measurement part.
        • The tags part
        • Placeholders
        • Spaces in measurement and tag keys.
        • The InfluxDB fields part.
        • Timestamp precision.
      • Logging application status
    • InfluxDB version 2.0.
      • Installation.
      • Configuration.
        • Example configuration file used in case of automatic deployment.
        • Steps to configure InfluxDb2 running in Docker container.
        • Grafana data source plugin for InfluxDB 2.0
      • Mapping OPC UA to InfluxDb.
    • Confluent Platform: Cloud and Enterprise
      • Configuration.
        • Configuration using web GUI.
        • Example file for automatic deployments.
      • Mapping from OPC UA to Confluent Topic, Key names and Partitions. Payload format.
        • Payload
    • Apache Kafka
      • Configuration.
        • Configuration using web GUI.
        • Example file for automatic deployments.
      • Mapping from OPC UA to Kafka Topic, Key names and Partitions. Payload format.
    • Microsoft SQL
    • MySQL
    • MemSQL
    • MQTT
      • Publish Topic Name composing
      • MQTT payload
      • Eclipse Mosquitto
      • Microsoft Azure IoT Hub
      • AWS IoT Broker
      • Google Cloud IoT Core MQTT Bridge.
      • IBM Watson IoT Platform
    • TSDB database access optimization.
  • Store
  • Visualize
    • InfluxDB 2.0 built-in visualization tools.
    • Visualization with Grafana.
    • Install Grafana
    • Setup Grafana data source plugins to get data via Industrial Data Collector REST API endpoint
      • Installing of the Infinity plugin.
      • Installing of the SimpleJson data source plugin.
    • Using Grafana data sources to read data from databases directly.
    • Setup Grafana dashboards.
      • Create new dashboard.
      • Reading values from Infinity data source plugin.
      • Reading values from SimpleJson data source plugin.
      • Reading values stored in PostgreSQL database.
  • Analyze
    • Test use case
    • Step 1: Add server node into Address Space.
    • Step 2. Start logging of values for OPC UA variable node.
    • Step 3. Configure Grafana panel to view data values
    • Step 4. Analyze data visually.
    • Step 5. Open PgAdmin page and connect to the TSDB database.
    • Step 6. Run SQL queries.
    • Step 7. Look at log files for additional information.
    • Step 8. Conclusion.
  • Roadmap
  • Support
  • How to:
    • Configure the application using Basic Configuration file.
    • How to setup configuration GUI endpoint to use https.
      • How to generate and install SSL certificate issued by Let’s Encrypt.
      • Configuring of the instance to use https.
    • Modify minimal refresh rate for Grafana
    • How to enable SQL Server Authentication and TCP in Microsoft SQL Server Express
      • Enabling SQL authentication Mode.
      • Enabling TCP connections.
    • Enable horizontal scrolling in the Logged Variables table.
    • Upgrade time-series database from InfluxDB 2.0 Beta version to InfluxDB 2.0.3 released version.
    • How to solve issue with duplicate records in SQLite or PostgreSQL/TimescaleDB.
    • How to install and run InfluxDB.
      • Windows 10
      • Linux (Ubuntu 18.04)
      • Installing SSL certificates from letsencrypt for InfluxDB (Ubuntu)
      • Running InfluxDB as Azure IoT Edge Module
    • How to quickly setup test configuration with 100K variables.
    • How to modify configuration options for large number of variables.
    • Import variables from CSV file
      • Import into SQLite configuration database.
      • Import into PostgreSQL configuration database.
    • How to add OPC UA Server connection settings and logged variables using Python scripts
    • How to create and use self-signed OPC UA application instance certificate.
    • How to monitor state of connection with OPC UA Servers
    • How to configure Industrial Data Collector and monitor its state using REST API.
    • How to connect to Ignition OPC UA Server in secured mode.
    • Connecting when Industrial Data Collector and OPC UA Server run in different network environments.
    • Network issues on Siemens Simatic IoT2050
Idako: Industrial Data Collector
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