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Best Practice

This section compiles rules that have proven effective in projects. They help prevent two types of errors: lost or duplicated data records, and engineering that fails under load or as the volume of data increases. Read the guidelines before you build the flows—once they’re in place, changing the table structure and flow design requires significant effort.

The pages in this chapter​

  • Project Development – how to customize flows and when to use templates or functions instead of many individual flows. Impact: maintainability and debugging.
  • OPC Transfers – which trigger to use for which purpose, and why a bit trigger requires a response bit. Effect: Data consistency.
  • Databases – Filters, Transfer Flag Columns, and Indexing When Reading from Tables. Impact: Data Consistency and Performance.
  • Cloud and IoT – QoS, connection pool, caching, and credentials for MQTT and cloud connections. Impact: Throughput and data loss during disruptions.

Examples and Concepts​

Detailed implementation examples are available in the plug-ins, along with sample configurations and images:

  • Performance Analysis – Test suites detailing the setup, hardware, and achieved throughputs on which the performance guidelines are based.
  • Architecture Recommendations – Design and scaling of the installation itself, from a single instance to a high-availability solution.