In the dynamic world of container orchestration, Kubernetes has emerged as the de facto standard for managing containerized applications as we discussed in a previous article. However, with great power comes great responsibility. As organizations scale their Kubernetes deployments, the need for robust policy enforcement becomes increasingly critical. In this article, we'll explore the challenges of Kubernetes cluster policy enforcement and examine two popular solutions: Kyverno and Gatekeeper.

Challenges

Imagine running a large-scale Kubernetes cluster where dozens of teams deploy hundreds of applications. Without proper controls, you might face several challenges:

1. 1. Resource Overconsumption: Stands as one of the most pressing challenges in Kubernetes environments. When pods operate without properly defined resource limits, they can create a "noisy neighbor" problem within your cluster. Consider a scenario where a single memory-intensive application, perhaps a Java service with an unbounded heap size, gradually consumes increasing amounts of node resources. Without proper limits, this application could potentially consume all available memory, leading to pod evictions and failed scheduling attempts for other critical workloads. Organizations often discover this issue too late, usually during peak traffic periods when resource contention becomes most apparent.
2. 2. Security Vulnerabilities: The practice of running privileged containers introduces significant security risks to your Kubernetes infrastructure. While granting privileged access might seem like a convenient solution for certain operational challenges, it fundamentally violates the principle of least privilege. When containers run as privileged, they gain the ability to potentially escape their isolation boundaries, access sensitive host system resources, and modify critical system files. This becomes particularly dangerous in compromised container scenarios, where an attacker could leverage these elevated privileges to gain access to the underlying host system or adjacent containers. Modern security best practices strongly advocate for running containers as non-root users with carefully scoped permissions through security contexts and pod security policies.
3. 3. Compliance Violations: The absence of required metadata labels and annotations might appear trivial at first glance, but it can lead to serious operational and compliance challenges. Proper metadata management serves as the foundation for resource tracking, cost allocation, and regulatory compliance in Kubernetes environments. Without consistent labeling, organizations struggle to identify resource ownership, track application dependencies, or implement effective security policies. For instance, in regulated industries, specific labels might be required to indicate data sensitivity levels or distinguish between production and non-production workloads. The lack of proper metadata can complicate audit processes and make it difficult to demonstrate compliance with regulatory requirements.
4. 4. Inconsistency in Team Standards: As organizations scale their Kubernetes deployments across multiple teams, maintaining unified standards becomes increasingly challenging. When different teams apply varying standards to their Kubernetes resources, it creates a fractured environment where deployment patterns, security configurations, and operational practices lack coherence. This inconsistency manifests in various ways - from divergent naming conventions and labeling schemes to contrasting approaches in security controls and resource configurations. For instance, while one development team might implement comprehensive pod security policies and strict resource quotas, another team could rely primarily on default configurations, creating potential vulnerabilities and resource management challenges. These divergent practices not only complicate cluster management but also make it difficult to implement organization-wide policies and maintain compliance standards. The impact of inconsistent standards becomes particularly apparent during incident response scenarios, where troubleshooting becomes more complex due to the varied approaches across different parts of the infrastructure.

Core Aspects

Policy enforcement in Kubernetes operates as a comprehensive control system, creating guardrails that directly contribute to your organization's operational excellence and risk management. Think of it as an intelligent traffic management system for your cluster – actively directing traffic, ensuring safety, and maintaining order while reducing operational overhead and potential costly incidents. This system continuously monitors and governs how resources are created, modified, and maintained within your Kubernetes environment. It validates that all operations align with your organization's established standards, from basic resource configurations to complex security protocols, ultimately leading to more reliable services, reduced downtime, and improved compliance posture. By preventing misconfigurations and security issues before they impact production, organizations can focus on innovation and business growth rather than incident response and remediation.

Resource Creation Control

Policy enforcement begins at the resource creation phase. This includes validating:

• Resource requests and limits
• Container image sources and tags
• Network policies
• Service account usage
• Volume mount configurations

Modification Governance

Beyond creation, policies must govern how resources can be modified:

• Preventing changes to critical labels
• Enforcing immutable fields
• Controlling scale operations
• Managing configuration updates

Automated Remediation

Modern policy enforcement doesn't just block non-compliant actions—it can automatically fix issues:

• Adding missing labels
• Injecting sidecars
• Updating resource configurations
• Applying default settings

Policy Enforcement Solutions: Kyverno vs. Gatekeeper

Let's examine two leading solutions in the Kubernetes policy enforcement space.

Kyverno takes a Kubernetes-native approach to policy management, offering several distinctive advantages:

Strengths:

• Uses standard Kubernetes resource formats
• No domain-specific language to learn
• Built-in mutation capabilities
• Excellent CLI tools for policy testing
• Straightforward policy debugging
• Generate policies from existing resources
• Native JUnit test support

Challenges:

• Limited to Kubernetes use cases
• Fewer advanced policy composition features
• Community size still growing
• UI is not very fleshed out (can change in the future)

Example Kyverno Policy:

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: registry-credential-sync
  annotations:
    policies.kyverno.io/title: Sync Secrets
    policies.kyverno.io/subject: Secret
    policies.kyverno.io/description: >-
      This policy will copy a Secret called `registry-creds` which exists in the `gitlab-runner` Namespace to new Namespaces with the component label ci when they are created.
      It will also push updates to the copied Secrets should the source Secret be changed.
spec:
  rules:
  - name: sync-secret
    match:
      resources:
        kinds:
        - Namespace
        selector:
          matchLabels:
            app.kubernetes.io/component: "ci"
    generate:
      apiVersion: v1
      generateExisting: true
      kind: Secret
      name: registry-creds
      namespace: {{`"{{request.object.metadata.name}}"`}}
      synchronize: true
      clone:
        namespace: gitlab-runner
        name: registry-creds

Gatekeeper, built on Open Policy Agent (OPA), provides a more comprehensive policy framework:

Strengths:

• Mature and battle-tested
• Powerful Rego policy language
• Extensive policy library available
• Strong community support
• Can be used beyond Kubernetes
• Advanced constraint templating
• Robust audit capabilities

Challenges:

• Steeper learning curve (Rego)
• More complex setup and maintenance
• Limited mutation capabilities
• Higher resource consumption
• More verbose policy definitions

Example Gatekeeper Policy equivalent to kyvernos clusterpolicy:

apiVersion: templates.gatekeeper.sh/v1beta1
kind: ConstraintTemplate
metadata:
  name: secretsync
spec:
  crd:
    spec:
      names:
        kind: SecretSync
      validation:
        openAPIV3Schema:
          type: object
          properties:
            sourceNamespace:
              type: string
            sourceSecretName:
              type: string
  targets:
    - target: admission.k8s.gatekeeper.sh
      rego: |
        package secretsync

        violation[{"msg": msg}] {
          # Check if the resource is a namespace
          input.review.object.kind == "Namespace"
          
          # Check if the namespace has the required label
          input.review.object.metadata.labels["app.kubernetes.io/component"] == "ci"
          
          # Get the target namespace name
          namespace := input.review.object.metadata.name
          
          # Check if the secret exists in the target namespace
          not data.inventory.cluster["v1"]["Secret"][namespace][input.parameters.sourceSecretName]
          
          msg := sprintf("Secret %v needs to be synced to namespace %v", [input.parameters.sourceSecretName, namespace])
        }

Making the Right Choice

The decision between Kyverno and Gatekeeper often depends on several factors:

1. 1. Team Experience: If your team is already familiar with Rego and OPA, Gatekeeper might be the natural choice. For teams seeking a pure Kubernetes approach, Kyverno's familiar YAML format could be more appropriate.
2. 2. Use Case Complexity: For straightforward Kubernetes policies, Kyverno's simplicity shines. For complex, cross-service policies, Gatekeeper's flexibility might be necessary.
3. 3. Scaling Requirements: Consider your cluster size and policy complexity. Gatekeeper generally handles complex policy combinations better, while Kyverno excels in straightforward Kubernetes scenarios.
4. 4. Future Growth: Think about potential non-Kubernetes policy requirements. Gatekeeper's OPA foundation makes it more versatile for broader policy enforcement needs.

Best Practices

Regardless of your chosen solution, consider these best practices:

1. 1. Start Small: Begin with basic policies and gradually expand. Focus on critical security and compliance requirements first.
2. 2. Test Thoroughly: Use dry-run modes and policy testing tools to validate policies before enforcement.
3. 3. Document Everything: Maintain clear documentation about policy intentions, exceptions, and processes.
4. 4. Monitor Impact: Track policy violations and their impact on deployments to refine your approach.
5. 5. Plan for Exceptions: Implement a clear process for handling legitimate policy exceptions.

Kubernetes Policy Enforcement with BridgePhase

In the complex landscape of Kubernetes governance, experience matters. For over a decade, BridgePhase has been at the forefront of designing and implementing sophisticated policy enforcement solutions that protect and streamline Kubernetes environments. Our deep expertise with both Gatekeeper and Kyverno have enabled us to architect robust security frameworks that address the unique challenges faced by government agencies and enterprise organizations. Our technical solutions extend beyond basic policy implementation. We've developed sophisticated integrations that weave policy enforcement throughout the entire technology stack, creating seamless governance frameworks that scale with our clients' needs. Whether it's implementing Zero Trust architectures, enforcing FedRAMP compliance, or establishing automated security controls, our solutions are built on real-world experience and battle-tested implementations.

Closing Remarks

Kubernetes policy enforcement is crucial for maintaining secure and well-governed clusters. While both Kyverno and Gatekeeper offer robust solutions, their different approaches cater to different needs. Kyverno excels in pure Kubernetes environments with its native approach, while Gatekeeper provides a more extensive policy framework suitable for complex, multi-service environments.

Consider your team's expertise, use cases, and future requirements when choosing between them. Remember that successful policy enforcement is not just about the tool—it's about implementing a comprehensive governance strategy that evolves with your organization's needs.

Start small, test thoroughly, and continuously refine your policies based on real-world usage and feedback. With either solution, you're on the path to better cluster governance and security.