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PI System Connector

Best Practices

  • Last UpdatedFeb 20, 2024
  • 2 minute read

Do not put connector and relay on the same machine.

The Relay and the Connector should be on dedicated machines with no other applications (such as a SQL Server, PI Server, AF Server, etc.).

Verify that the PI System Connector and Relay are not competing with Source and Destination clients. If you have an application (PI Vision, Datalink, or something custom) that makes expensive queries to your source or destination PI Server this can impact performance of the PI System Connector and Relay.

If you have a PI Server collective, set the affinity for PI System Connector and Relay to a node that is less overloaded/used.

System Sizing Best Practices

Category

Guideline

General

PI System Connector and Relay should each have at least four virtual processors at minimum. For best results, we recommend using eight virtual processors.

Peak loads (startup, restarts, bulks edits, etc.)

Although you may not need this much for normal operation, your system will struggle to process large amounts of data if you have less RAM.

PI System Connector - 16GB RAM (recommended: 32GB)

Relay - 16GB RAM (recommended: 32GB)

Event Frames

Additional 4GB RAM for every 4 million Event Frames.

Large AF Database

Additional 2 GB Ram for every 100,000 elements.

Large PI Point Count

Additional 2 GB Ram for every 1.5 million PI Points.

Note: For each 500K points, add a virtual processor.

Snapshot Rate

Multiples of 15,000 events/sec - Add another virtual processor.

Example: if you have 50,000 events/sec, you should have three additional virtual processors.

Make Health AF Element, pointing to customer created health tags.

You will need a watchdog tag on the Source PI Data Archive– one that updates very frequently – to monitor updates are being replicated. We recommend a tag is added to the source PI Data Archive that updates once per second (or customer preference).

Create an element with a reference to the newly created tag bound to an attribute so the custom element is replicated and can be monitored on the destination(s).

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