Pipeline metrics
Keep track of pipeline performance
On the Pipeline Metrics page you can analyze graphs concerning the performance of deployed pipelines.
Select the desired environment in the upper left corner. When you select an environment, the whole page is updated.
Then, choose a pipeline from the search bar and select the desired report period. The predetermined options are the last : 15 minutes, 1 hour, 6 hours, 1 day or 7 days. You can also choose a specific time interval.
This graph shows the average number of pipeline executions per second for many time intervals in the selected time period for all replicas.
This graph shows the average time (in miliseconds) the pipeline took to generate a response for many time intervals over the selected period for all replicas.
The response time is given by the elapsed time between the message leaving the execution queue and the pipeline generating a response. Containments in the execution queue do not affect this metric.
You can learn more about execution queues in the “Pipeline messages in queue (messages)” section below.
This graph shows the total number of concurrent requests to the pipeline - for all replicas - for many intervals in the selected time period.
This information is useful to determine if the number of replicas and concurrent executions chosen during the deployment were appropriate.
The lines in this graph show the average request and response message size in bytes for all pipeline replicas, for many intervals in the selected time period. You can see the line's label by hovering the cursor over it.
This information is useful for determining wheter the pipeline size selected during deployment was appropriate.
This graph shows the average percentage of memory usage for each replica of the pipeline for many intervals in the selected time period. The amount of memory allocated to the pipeline depends on the selected deployment size.
Deployment size | Memory |
|---|---|
Small | 64MB |
Medium | 128MB |
Large | 256MB |
This information is useful for determining whether the pipeline size selected during deployment was appropriate, as exhaustion of available memory will result in an "Out of Memory" error.
This graph shows the total number of messages in the execution queue, that is, the number of messages waiting to be processed, for all pipeline replicas, for many intervals in the selected time period.
All replicas consume messages from the same queue. A high number of messages in the queue indicates that the number of pipeline replicas or concurrent executions needs to be increased during deployment.
This graph shows the average percentage of CPU usage for each pipeline replica. The y-axis is limited by the CPU processing power, which depends on the selected deployment size.
Deployment size | CPU |
|---|---|
Small | 20% |
Medium | 40% |
Large | 80% |
This information is useful for determining whether the pipeline size selected during deployment was adequate, as exhaustion of available memory will result in an “Out of Memory” error.
Last modified 2mo ago