In Kubebuilder, custom resource definitions (CRDs) are serialized using Go structs. The serialization process converts the struct into a format that can be understood by the Kubernetes API server. This allows custom resources to be easily maintained and utilized within the Kubernetes ecosystem.
To serialize CRDs, you often define your custom resource types by creating Go structs and using annotations to specify how they should be handled when serialized into the Kubernetes API.
Here is an example of how to serialize a CRD in Kubebuilder:
// +kubebuilder:object:root=true
// +kubebuilder:subresource:status
// MyCustomResource is the Schema for the mycustomresources API
type MyCustomResource struct {
metav1.TypeMeta `json:",inline"`
metav1.ObjectMeta `json:"metadata,omitempty"`
Spec MyCustomResourceSpec `json:"spec,omitempty"`
Status MyCustomResourceStatus `json:"status,omitempty"`
}
// MyCustomResourceSpec defines the desired state of MyCustomResource
type MyCustomResourceSpec struct {
// Define your spec fields here
}
// MyCustomResourceStatus defines the observed state of MyCustomResource
type MyCustomResourceStatus struct {
// Define your status fields here
}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?