The runtime statistics can provide an initial indication of client-server interaction problems. Use the statistics to identify the general problem and then use the OPC Connection Trace Logging to identify the specific problem.
Client Groups and Client Items
Client groups and Client items provide a rudimentary indication of how an OPC client organizes the group and item object resources supplied by the GagePort Mitutoyo OPC Server. Some OPC client applications initially create a large number of OPC groups and disable the subscription updates until needed. While this will not cause CPU loading problems, it could cause the initial connection and setup time with the GagePort Mitutoyo OPC Server to be slow or for a large amount of memory to be used by the OPC Server.
Reads Transactions Per Period, Write Transactions Per Period
Reads transactions per period and write transactions per period provide information on the OPC Server loading. For example, a high Read Transactions Per Period or Write Transactions Per Period value may coincide with abnormally high CPU loading. The client may be continuously performing a large number of device read or device write requests. (Note that cache reads are very efficient and do not typically cause significant CPU loading problems.)
Subscriptions updates (e.g. unsolicited updates of changed values and/or quality information by an OPC server to an OPC client) may cause high CPU loading when the OPC client requested OPC group update rates are small for groups with rapidly changing values. If subscription updates are not occurring when OPC items are known to be changing, then there may be a DCOM security authentication problem on the computer hosting the OPC client application. The security on this node may not be configured to allow the GagePort Mitutoyo OPC Server to post subscription updates (via. callbacks).
GagePort Mitutoyo OPC Server runtime statistics.
About the GagePort Mitutoyo OPC Server troubleshooting tools.