Infrastructure Pods and Resource Management

During the installation procedure you will be able to provide information on how to best "operationalize" your infrastructure. Here we give you some Kubernetes best practices you can use in order to configure a production ready environment.

The usage of these advanced configuration assumes you’re familiar with the Kubernetes Scheduling concepts and configurations.

Depending on the installation methodology (ie, Helm) provided you may have certain configuration parameters out of the box. Otherwise you should be able to fine tune those parameters altering directly the Camel K operator Deployment.

Scheduling

Node Selectors and tolerations

We suggest to edit the Deployment to configure the NodeSelector Kubernetes feature and the Taint and Toleration Kubernetes feature.

Resources

While installing the Camel K operator, you can also specify the resources requests and limits to assign to the operator Pod. This configuration will expect the setting as required by Kubernetes Resource Management.

if you specify a limit, but does not specify a request, Kubernetes automatically assigns a request that matches the limit.

Default Operator Pod configuration

The main Camel K Operator Pod contributor resources consumption is likely to be the number of parallel builds that are performed in the operator Pod. So the resource requirements should be defined accordingly. The following requirements are sensible defaults that should work in most cases:

resources:
  requests:
    memory: "2Gi"
    cpu: "500m"
  limits:
    memory: "8Gi"
    cpu: "2"

Note that if you plan to perform native builds, then the memory requirements may be increased significantly. Also, the CPU requirements are rather "soft", in the sense that it won’t break the operator, but it’ll perform slower in general.

Default Integration Pod configuration

The resource set on the container here is highly dependant on what your application is doing. You can control this behavior by setting opportunely the resources on the Integration via container trait.

Be aware that the default are actually the following:

resources:
  requests:
    memory: "256Mi"
    cpu: "125m"
  limits:
    memory: "1Gi"
    cpu: "500m"