TrustyAI meets Kogito: decision monitoring

by Jacopo Rota - July 1, 2020
AI Article

In this article, we introduce the metrics monitoring add-on for Kogito. This add-on is part of the TrustyAI initiative already introduced in the previous article https://blog.kie.org/2020/06/trusty-ai-introduction.html .

Like Quarkus extensions, the Kogito add-ons are modules that can be imported as dependencies and add capabilities to the application. For example, another add-on is the infinispan-persistence-addon that enables the Infinispan persistence.

The add-on we introduce in this post was already available but now with version 0.11 of Kogito new features related to decision monitoring have been added:

Export of domain specific monitoring metrics with Prometheus.
Generate operational and domain specific grafana dashboards.

In the article cited above, we introduced three personas: the devops engineer, the case worker and the compliance officer. The current version of the add-on exports one or more dashboards for each DMN and DRL resource. In particular, two types of dashboards might be generated depending on the type of the resource: one with operational metrics more oriented for the devops engineer and one with domain specific metrics, oriented to the case worker and the compliance worker needs.

Operational dashboard: this kind of dashboard is generated for each DMN and DRL endpoint and it contains useful information to monitor the status of the applications so as to have a fast reaction in case something goes wrong. The available graphs are about:

The total number of requests on the endpoint.
The average number of requests on the endpoint per minute.
The quantiles on the elapsed time to evaluate the requests.
Exception details.

Domain specific dashboard: currently this dashboard is exported only for each DMN endpoint. In particular, the domain specific dashboard contains a graph for each type of decision in the DMN model. At the moment, the types number, boolean and string are supported, all the other time-based builtin types will be covered in the next Kogito release. In particular

if the output of the decision is a number, the graph contains the quantiles for that metric (on a sliding window of 3 minutes).
If the output is a boolean or a string, the graph contains the number of occurrences for each output (10 minutes average).
if the output is time-based, a graph containing the quantiles is generated (with different scales and measurement unit depending on the type).

The plan for the next versions of the add-on is to also support complex structures and lists.

The devops engineer can directly use the dashboards that the add-on generates, or create custom ones manually based on the metrics exported by the application.

How To Use It

There are a few steps to follow to start using this add-on:

In your kogito project, assuming that you have imported the kogito bom to manage properly the versions of the kogito modules, import the monitoring-prometheus-addon in your pom.xml:

<dependency>
<groupId>org.kie.kogito</groupId>
 <artifactId>monitoring-prometheus-addon</artifactId>
</dependency>

In case you are interested about the number of requests on the endpoints and the status code of the responses, add the following class to your project

import javax.ws.rs.container.ContainerRequestContext;
import javax.ws.rs.container.ContainerResponseContext;
import javax.ws.rs.ext.Provider;
import org.kie.addons.monitoring.system.interceptor.MetricsInterceptor;
@Provider
public class MyInterceptor extends MetricsInterceptor {
    @Override
    public void filter(ContainerRequestContext requestContext, ContainerResponseContext responseContext) {
        super.filter(requestContext, responseContext);
    }
}

At this point, once the application is packaged

mvn clean package

the dashboards are generated under the path target/generated-resources/kogito/dashboards and the devops engineer can easily inject them during the deployment of the grafana container.
For the grafana provisioning, we suggest having a look at the official Grafana documentation https://grafana.com/docs/grafana/latest/administration/provisioning/ . The steps to deploy the dashboards will be integrated with Kogito Operator in a future release.

That’s it! The Kogito application is ready to export operational and domain specific metrics on the endpoint /metrics.

A complete example can be found here https://github.com/kiegroup/kogito-examples/tree/main/kogito-quarkus-examples/dmn-drools-quarkus-metrics.

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