The Camel Dashboard Operator is a project created to simplify the management of any Camel application on a Kubernetes cluster. The tool is in charge to monitor any Camel application and provide a set of basic information, useful to learn how your fleet of Camel (a caravan!?) is behaving.
The project is designed to be as simple and low resource consumption as possible. It only collects the most important Camel application KPI in order to quickly identify what's going on across your Camel applications.
NOTE: as the project is still in an experimental phase, the metrics collected can be changed at each development iteration.
The operator uses a simple custom resource known as app or capp (as Camel App) which stores certain metrics around your running applications. The operator detects the Camel applications you're deploying to the cluster, identifying them in a given namespace or a given metadata label that need to be included when deploying your applications (all configurable on the operator side).
You can use Helm to install the operator resources. You can install it in any namespace (we conventially use camel-dashboard namespace, which, has to be created previously). The default configuration is for a cluster scoped operator (use --set operator.global=\"false\" for a namespace scoped operator).
helm install camel-dashboard https://github.com/camel-tooling/camel-dashboard-operator/raw/refs/heads/main/docs/charts/camel-dashboard-0.0.1-SNAPSHOT.tgz -n camel-dashboard
NOTE: the installation procedure is still in experimental phase and uses a snapshot artifacts. It could change in future stable releases.
You can check if the operator is running:
kubectl get pods -n camel-dashboard
NAME READY STATUS RESTARTS AGE
camel-dashboard-operator-7c6bcf5576-fwn7s 1/1 Running 0 4m18s
The operator is instructed to watch Deployment and verify if they are marked as Camel application. You will likely need to update your deployment process and include automatically a camel.apache.org/app label for all the applications you want to monitor.
NOTE: you can configure the operator to watch for a different label setting the environment variable LABEL_SELECTOR in the operator Pod.
The operator is designed to consume the services exposed by Camel Observability Services component.
It will works also when no services are exposed, but it won't be able to collect any meaningful metrics (likely only the status and the number of replicas).
Let's run some sample Camel application. We have prepared a few available to run some quick demo:
- A Camel main application available at
docker.io/squakez/db-app-main:1.0 - A Camel Quarkus application available at
docker.io/squakez/db-app-quarkus:1.0 - A Camel Spring Boot application available at
docker.io/squakez/db-app-sb:1.0
These applications were created, exported and "containerized" via Camel JBang, which includes by default the aforementioned camel-observability-services dependency.
Let's run them in a Kubernetes cluster (it also works in a local cluster such as Minikube):
kubectl create deployment camel-app-main --image=docker.io/squakez/db-app-main:1.0
The application should start, but, since there is no label for the operator, this one cannot discover it.
NOTE: ideally your pipeline process should be the one in charge to include this and any other label to the applications.
Let's include the label via CLI:
kubectl label deployment camel-app-main camel.apache.org/app=camel-app-main
NOTE: you can test it straight away with any of your existing Camel application by adding the label as well.
The application is immediately imported by the operator. Its metrics are also scraped and available to be monitored:
kubectl get apps
NAME PHASE LAST EXCHANGE EXCHANGE SLI IMAGE REPLICAS INFO
camel-app-413 Running 8m32s OK squakez/cdb:4.13 1 Main - 4.13.0-SNAPSHOT (4.13.0-SNAPSHOT)
NOTE: more information are available inspecting the custom resource (i.e. via -o yaml).
As you will discover in the chapters below, you can provide specific configuration for each App. In order to keep the operator in synch with any deployment tool, you should therefore annotate the backing deployment object (ie, the Deployment) with such specific configuration. The operator will automatically synchronize any annotation prefixed with camel.apache.org.
You can watch the metrics evolving as long as the application is running, for example via -w parameter:
kubectl get apps -w
NAME PHASE LAST EXCHANGE EXCHANGE SLI IMAGE REPLICAS INFO
...
camel-app-413 Running 8m32s OK squakez/cdb:4.13 1 Main - 4.13.0-SNAPSHOT (4.13.0-SNAPSHOT)
camel-app-main Running OK docker.io/squakez/db-app-main:1.0 1 Main - 4.11.0 (4.11.0)
camel-app-quarkus Running Warning docker.io/squakez/db-app-quarkus:1.0 1
camel-app-sb Running Error docker.io/squakez/db-app-sb:1.0 1 Spring-Boot - 3.4.3 (4.11.0)
The App are polled every minute by default. It should be enough in most cases, as the project is really a dashboard and not a proper monitoring tool. However, you can change this configuration if you want a more or less reactive polling. You can configure this value both at operator level (which would affect all the applications) or at single application level.
You can setup the environment variables POLL_INTERVAL_SECONDS with the number of seconds between each metrics polling.
NOTE: this will affect all your applications. Setting it a low value can reduce the performances of both the operator and the same Camel applications which will need to use compute resources to read from the HTTP service.
You can add an annotation to the Deployment resource, camel.apache.org/polling-interval-seconds with the value you want.
NOTE: although this configuration will only affect the single application, consider the right balance to avoid affecting the application performances.
The operator is in charge to automatically calculate the success rate percentage of exchanges in the last polling interval time. It has some default configuration and will return a Success, Warning or Error status if it detects that the failure of exchanges during the interval exceeds the thresholds. It returns an Error when the failure exceed the 5% of exchanges failed, Warning if the failure is above 10%, Success. However, these values can be configured.
You can setup the environment variables SLI_ERR_PERCENTAGE and SLI_WARN_PERCENTAGE. It requires an int value.
You can add an annotation to the Deployment resource, camel.apache.org/sli-exchange-error-percentage and camel.apache.org/sli-exchange-warning-percentage with the value expected for that specific application only.
The operator is able to discover applications thanks to the presence of the camel-observability-services component. By default this component exposes the metrics on port 9876 (which is also the operator default if you don't configure it). However this value can be changed by the user to any other port (including the regular business service port). You can configure is both at Operator or Application level.
You can setup the environment variables OBSERVABILITY_PORT with the number of the port where the operator has to get the metrics.
You can add an annotation to the Deployment resource, camel.apache.org/observability-services-port with the value expected for that specific application only.
This operator can work standalone and you can use the data exposed in the App custom resource accordingly. However it has a great fit with the Camel Openshift Console Plugin, which is a visual representation of the services exposed by the operator.