Explore use cases for alerts on the Digibee Integration Platform
This documentation describes use cases that show how the metrics available in the Digibee Integration Platform can be applied in real-world scenarios. These use cases will help you understand how to interpret the data and make decisions to improve your operational results.
Pipeline executions and Pipeline Executions per instance
Fixing a pipeline execution or a Pipeline Executions per instance issue
If the number of executions per second of a pipeline is outside the expected range, it could be due to the following:
Your pipeline is not being triggered as expected
For example, if your pipeline has a REST trigger that is activated by a third-party application, a failure in that application will cause that pipeline not to activate. Consequently, the execution rates of your pipeline would take a value lower than the expected one. If this is the case, fixing the issue in the third-party application will return your pipeline execution rate to the expected level.
If, on the other hand, the execution rate of a pipeline is higher than expected, this may be due to an incorrect trigger configuration, such as a cron expression in the settings of a scheduler trigger that was entered incorrectly.
Your pipeline architecture is inappropriate
An improper pipeline architecture can lead to unexpected execution rates. For example, if you build a pipeline that reprocesses failed executions and forget to set a limit on reprocessing, that pipeline might try to execute an infinite number of times.
An inefficient architecture may also cause pipelines to take longer than expected to execute, decreasing their execution rate. If this is the case, review your pipeline architecture. Consider using an event-driven architecture and/or pagination.
When the deployment size of a pipeline is too small to support the frequency in which it's triggered, execution requests stack up instead of executing immediately. This can cause the execution rate to take on a value that is lower than expected. If this is the case, consider increasing the deployment size of your pipeline. Read the article about deployment sizes to learn more.
If the period that the pipeline inflight execution is outside the expected range, it could be due to the following:
Increase the number of replicas of a pipeline in Run
When many messages are executed at the same time, we can check if it is necessary to increase the number of replicas of a given pipeline in order to distribute the execution load among all of them.
If the memory usage of a pipeline is outside the expected range, it could be due to the following:
Your pipeline deployment size is too small
When the deployment size of a pipeline is too small to support the size of the request and the memory usage may become larger than is available to the pipeline, there is not enough memory to execute the given request. This can cause the pipeline to display an “out of memory” error. If this is the case, you should increase the size of the pipeline deployment size. Learn more in the deployment sizes documentation.
If the pipeline message size is outside the expected range, it could be due to the following:
Your pipeline deployment size is too small
When the deployment size of a pipeline is too small to support the size of the request and the memory usage may become larger than is available to the pipeline, there is not enough memory to execute the given request. This can cause the pipeline to display an “out of memory” error. If this is the case, you should increase the size of the pipeline deployment size. Learn more in the deployment sizes documentation.
Pipeline Messages on Queue
Fixing an MOQ issue
If the number of messages on queue for a pipeline is out of the expected range, it could be due to the following factors:
Redeploy your pipeline
Increase the number of replicas on the Run tab and check the number of concurrent executions.
Move your pipeline to a larger size
If you have available licenses, consider scaling your pipelines to a larger number to allow for more concurrent executions.
Pipeline Response Time
Fixing a pipeline response time issue
If the period that the pipeline response time is outside the expected range, it could be due to the following:
Increase the number of replicas of a pipeline in Run
By increasing the number of replicas, the number of messages on queue decreases because there is a higher throughput and processing is accelerated. Learn more in deployment sizes documentation.
