Pros of Gatekeeper

• Uses Rego, a powerful and flexible policy language
• Supports complex policy logic and external data sources
• Integrates well with existing OPA ecosystems

Cons of Gatekeeper

• Steeper learning curve due to Rego language complexity
• Requires separate CRDs for constraints and templates
• More resource-intensive compared to Kyverno

Code Comparison

Kyverno policy example:

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-labels
spec:
  validationFailureAction: enforce
  rules:
    - name: check-for-labels
      match:
        resources:
          kinds:
            - Pod
      validate:
        message: "label 'app' is required"
        pattern:
          metadata:
            labels:
              app: "?*"

Gatekeeper constraint template example:

apiVersion: templates.gatekeeper.sh/v1beta1
kind: ConstraintTemplate
metadata:
  name: k8srequiredlabels
spec:
  crd:
    spec:
      names:
        kind: K8sRequiredLabels
  targets:
    - target: admission.k8s.gatekeeper.sh
      rego: |
        package k8srequiredlabels
        violation[{"msg": msg}] {
          provided := {label | input.review.object.metadata.labels[label]}
          required := {label | label := input.parameters.labels[_]}
          missing := required - provided
          count(missing) > 0
          msg := sprintf("you must provide labels: %v", [missing])
        }

Pros of Datree

• Simpler setup and configuration process
• Focuses on policy enforcement during CI/CD pipelines
• Provides a user-friendly web interface for policy management

Cons of Datree

• Limited to YAML validation and Kubernetes manifests
• Less flexible for complex policy scenarios
• Requires a SaaS component, which may not be suitable for all environments

Code Comparison

Kyverno policy example:

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-labels
spec:
  validationFailureAction: enforce
  rules:
    - name: check-for-labels
      match:
        resources:
          kinds:
            - Pod
      validate:
        message: "label 'app' is required"
        pattern:
          metadata:
            labels:
              app: "?*"

Datree policy example:

customRules:
  - identifier: CUSTOM_LABEL_REQUIRED
    name: Ensure 'app' label exists
    query: metadata.labels.app
    errorMessage: The 'app' label is missing
    schema:
      type: string

Both tools aim to enforce policies in Kubernetes environments, but they differ in approach and scope. Kyverno offers more flexibility and can be used for a wider range of policy enforcement scenarios, while Datree focuses on simplicity and integration with CI/CD pipelines. The choice between them depends on specific use cases and organizational requirements.

Pros of Polaris

• User-friendly web interface for visualizing and managing policy violations
• Includes a set of pre-defined best practices for Kubernetes configurations
• Supports both CLI and admission controller modes for flexible integration

Cons of Polaris

• Limited to static analysis of Kubernetes resources
• Less extensive policy customization options compared to Kyverno
• Primarily focused on configuration validation, lacking mutation capabilities

Code Comparison

Polaris configuration example:

checks:
  - name: hostNetworkSet
    exclude:
      - Deployment
  - name: hostPIDSet
    exclude:
      - DaemonSet

Kyverno policy example:

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-labels
spec:
  validationFailureAction: enforce
  rules:
    - name: check-for-labels
      match:
        resources:
          kinds:
            - Pod
      validate:
        message: "label 'app.kubernetes.io/name' is required"
        pattern:
          metadata:
            labels:
              app.kubernetes.io/name: "?*"

Both tools aim to improve Kubernetes cluster security and configuration management, but they differ in approach and capabilities. Polaris focuses on pre-defined best practices and offers a user-friendly interface, while Kyverno provides more extensive policy customization options and supports both validation and mutation of resources.

Pros of Trivy

• Broader scope: Scans containers, filesystems, git repositories, and more
• Faster scanning speed, especially for large images or repositories
• More comprehensive vulnerability database, including OS packages and language-specific dependencies

Cons of Trivy

• Limited policy enforcement capabilities compared to Kyverno
• Lacks native Kubernetes integration and admission control features
• Primarily focused on vulnerability scanning rather than configuration management

Code Comparison

Trivy CLI command:

trivy image nginx:latest

Kyverno policy example:

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-labels
spec:
  validationFailureAction: enforce
  rules:
    - name: check-for-labels
      match:
        resources:
          kinds:
            - Pod
      validate:
        message: "label 'app.kubernetes.io/name' is required"
        pattern:
          metadata:
            labels:
              app.kubernetes.io/name: "?*"

While Trivy focuses on vulnerability scanning with a simple CLI interface, Kyverno provides declarative policies for Kubernetes resource management and validation. Trivy excels in comprehensive security scanning across various artifacts, while Kyverno specializes in Kubernetes-native policy enforcement and admission control.