I have a process with max flow limit enabled. The value being set at 10. Its a Asyn process and used to get thousands of messages daily. We noticed that at peak time, with the increase in messages in queue in EMS server, the performance of the tibco process decline. Is there is any dependency between slowness in Tibco with increased inflow of EMS messages. How to calculate the exact flow limit for a process ? do we have any standard procedure ?
The FlowLimit configuration setting is a BusinessWorks setting, so I am assuming that you have BusinessWorks engines that are consuming messages from an EMS queue.
The concept of flow control exists in order to ensure that the number of incoming evens to a BusinessWorks engine does not cause the JVM to exceed its available memory resources. BusinessWorks implements the flow control by temporarily disabling the process starter until the number of jobs in memory falls below a threshold. In the case of EMS-based process starters this entains closing the MessageConsumer, which causes EMS to stop delivering messages to the process. In high-volume messaging scenarios this will cause a backlog of messages on the EMS server. Additionally it will cause any message in the prefetch cache on the client-side to be re-prioritzed for re-delivery on the EMS server side. When this happens you will notice that your outbound message count is greater than you inbound message count in your EMS statistics.
You are best off avoiding getting into flow-controlled scenarios. Is your current FlowLimit parameter realistic for the heap size you are allotting your JVM and the message payload sizes you are working with? Can you increase your JVM heap size and also your FlowLimit? Are you able to run multiple instances of the BusinessWorks application dispatching off the same queue in order to increase scalability? The approaches may help you scale and avoid message backlogs.