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issue-465 Create a documentation section to use Grafana DataSource with SonataFlow Prometheus metrics #693
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@jianrongzhang89 can you please take a look on CI? |
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🎊 PR Preview f1a88df has been successfully built and deployed. See the documentation preview: https://sonataflow-docs-preview-pr-693.surge.sh |
@ricardozanini fixed CI errors. |
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serverlessworkflow/modules/ROOT/pages/cloud/operator/monitoring-workflows.adoc
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Would you mind check the procedure for regular Kubernetes clusters? @domhanak |
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serverlessworkflow/modules/ROOT/pages/_common-content/sonataflow-metrics.adoc
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Many thanks, @jianrongzhang89. This documentation seems good. Thanks, @wmedvede, for verifying the steps in the cluster!
@kaldesai mind taking a look too? |
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Hi @jianrongzhang89 , I couldn't evict adding some more nitpicks when re-reading 😄
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In {product_name}, you can check the following metrics: | ||
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* `kogito_process_instance_started_total`: Number of started workflows (a workflow that has started might be running or completed) |
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* `kogito_process_instance_started_total`: Number of started workflows (a workflow that has started might be running or completed) | |
* `kogito_process_instance_started_total`: Number of started workflows. |
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* `kogito_process_instance_started_total`: Number of started workflows (a workflow that has started might be running or completed) | ||
* `kogito_process_instance_running_total`: Number of running workflows | ||
* `kogito_process_instance_completed_total`: Number of completed workflows |
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* `kogito_process_instance_completed_total`: Number of completed workflows | |
* `kogito_process_instance_completed_total`: Number of completed workflows. |
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ok
* `kogito_process_instance_started_total`: Number of started workflows (a workflow that has started might be running or completed) | ||
* `kogito_process_instance_running_total`: Number of running workflows | ||
* `kogito_process_instance_completed_total`: Number of completed workflows | ||
* `kogito_process_instance_error`: Number of workflows that report an error ( a workflow with an error might be still running or have been completed) |
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* `kogito_process_instance_error`: Number of workflows that report an error ( a workflow with an error might be still running or have been completed) | |
* `kogito_process_instance_error`: Number of workflows that report an error. |
* `kogito_process_instance_running_total`: Number of running workflows | ||
* `kogito_process_instance_completed_total`: Number of completed workflows | ||
* `kogito_process_instance_error`: Number of workflows that report an error ( a workflow with an error might be still running or have been completed) | ||
* `kogito_process_instance_duration_seconds`: Duration of a process instance in seconds |
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* `kogito_process_instance_duration_seconds`: Duration of a process instance in seconds | |
* `kogito_process_instance_duration_seconds`: Duration of a workflow instance in seconds. |
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done
* `kogito_process_instance_completed_total`: Number of completed workflows | ||
* `kogito_process_instance_error`: Number of workflows that report an error ( a workflow with an error might be still running or have been completed) | ||
* `kogito_process_instance_duration_seconds`: Duration of a process instance in seconds | ||
* `kogito_node_instance_duration_milliseconds`: Duration of relevant nodes in milliseconds (a workflow is composed by nodes, user might be interested on the time consumed by an specific node type) |
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* `kogito_node_instance_duration_milliseconds`: Duration of relevant nodes in milliseconds (a workflow is composed by nodes, user might be interested on the time consumed by an specific node type) | |
* `kogito_node_instance_duration_milliseconds`: Duration of relevant nodes in milliseconds. |
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[NOTE] | ||
==== | ||
Internally, workflows are referred as processes. Therefore, the `processId` and `processName` is workflow ID and name respectively. |
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Internally, workflows are referred as processes. Therefore, the `processId` and `processName` is workflow ID and name respectively. | |
Internally, workflows are referred as processes. Therefore, the `processId` and `processName` are workflow id and name respectively. |
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ok
Internally, workflows are referred as processes. Therefore, the `processId` and `processName` is workflow ID and name respectively. | ||
==== | ||
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Each of the metrics mentioned previously contains a label for a specific workflow ID. For example, the `kogito_process_instance_completed_total` metric below contains the labels for `callbackstatetimeouts` workflow: |
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Each of the metrics mentioned previously contains a label for a specific workflow ID. For example, the `kogito_process_instance_completed_total` metric below contains the labels for `callbackstatetimeouts` workflow: | |
Each of the metrics mentioned previously contains a label for a specific workflow id. For example, the `kogito_process_instance_completed_total` metric below contains the labels for `callbackstatetimeouts` workflow: |
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ok
---- | ||
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=== kogito_process_instance_duration_seconds | ||
Calculates duration of a workflow instance that has reached a terminal state,, i.e. `Aborted` or `Completed`. This metric is registered when the process reaches the terminal state. |
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Calculates duration of a workflow instance that has reached a terminal state,, i.e. `Aborted` or `Completed`. This metric is registered when the process reaches the terminal state. | |
Calculates duration of a workflow instance that has reached a terminal state, i.e. `Aborted` or `Completed`. This metric is registered when the process reaches the terminal state. |
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ok
* `kogito_process_instance_error`: Number of workflows that report an error ( a workflow with an error might be still running or have been completed) | ||
* `kogito_process_instance_duration_seconds`: Duration of a process instance in seconds | ||
* `kogito_node_instance_duration_milliseconds`: Duration of relevant nodes in milliseconds (a workflow is composed by nodes, user might be interested on the time consumed by an specific node type) | ||
* `sonataflow_input_parameters_counter`: Records input parameters, the occurrences of <"param_name","param_value"> per `processId`. |
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* `sonataflow_input_parameters_counter`: Records input parameters, the occurrences of <"param_name","param_value"> per `processId`. | |
* `sonataflow_input_parameters_counter_total`: Records input parameters, the occurrences of <"param_name","param_value"> per `processId`. |
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Hi @RichardW98 a few nitpicks, and I have also re-installed the grafana dahsboard after these last modification.
Is working good, great work!
Just an observation regarding the dashboard, see screenshots please:
In my tests, I have these workflows: callbackstatetimeouts
and callbackstatetimeouts-gitops
.
The dashboard works fine:
However, in the filters a "greeting" value is shown.
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@wmedvede I updated PR based on your above comments. Thanks. |
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LGTM, thanks!
@domhanak mind taking a look so we can close this one? |
…ith SonataFlow Prometheus metrics
…ith SonataFlow Prometheus metrics: address review comments
…ow-metrics.adoc Co-authored-by: Walter Medvedeo <[email protected]>
…ow-metrics.adoc Co-authored-by: Walter Medvedeo <[email protected]>
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…ith SonataFlow Prometheus metrics: address review comments
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Fix apache/incubator-kie-kogito-serverless-operator#465
Update the document to include Prometheus and Grafana installation, and Grafana Data Source congfiguration and import the default dashboard.
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[0.9.x] Issue-XYZ Subject