When Policy as Code Implementation Fails

Author

Govardhana M K
November 22, 2024

TechOps Examples

Hey — It's Govardhana MK 👋

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IN TODAY'S EDITION

🧠 Use Case

  • When Policy as Code Implementation Fails

🚀 Top News

👀 Remote Jobs

📚️ Resources

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🧠 USE CASE

When Policy as Code Implementation Fails

If you've seen someone stopped for overspeeding, you already understand 'Policy as Code' in action!

In this analogy 👇️ 

Overspeeding vehicle = Your build

Speed Limit = Policies (set of rules defined by a governing body)

Traffic Police = Continuous Integration enforcing the rules

In short, Policy as Code is the practice of defining rules and compliance policies in a machine-readable format, enabling automated enforcement during every step of the development and deployment process.

In a technical sense, implementing Policy as Code involves integrating tools and practices to enforce rules automatically for the validation.

Popular Tools for Policy as Code:

  • Kyverno: Kubernetes-native policy engine to validate, mutate, and generate configurations.

  • OPA (Open Policy Agent): A general-purpose policy engine that works across various environments like Kubernetes, Terraform, and CI/CD pipelines.

  • Checkov: Focused on scanning Infrastructure as Code (IaC) for policy violations.

Who is Responsible?

  • Security/Compliance Teams: Define the policies, making sure they align with organizational and regulatory standards.

  • DevOps Engineers: Implement and integrate these policies into CI/CD pipelines, enabling seamless enforcement during development.

How It Works?

  • Policy Engine: Tools like Kyverno or OPA serve as the policy engine, comparing builds against defined rules.

  • Ruleset Definition: Policies are defined in code (YAML, Rego for OPA), specifying what is allowed or disallowed.

  • Automated Enforcement: Integrated into CI/CD pipelines, ensuring that every change is validated against the policies before merging or deployment.

Policy as Code (PaC) is definitely a game-changer for sure, but it’s not foolproof.

Here are real-world scenarios where PaC falls short.

1. Inadequate Policy Coverage

Teams deploy PaC tools but only write policies for obvious cases (e.g., enforcing tag usage) while neglecting less visible issues like resource over-provisioning or data encryption.

Mitigation Steps:

  • Conduct regular audits of existing policies.

  • Use threat modeling sessions to identify coverage gaps.

  • Implement policies iteratively, starting with critical risks.

2. Performance Bottlenecks in CI/CD Pipelines

Policy checks added to pipelines slow down deployments significantly, especially when applied to large infrastructure changes.

Mitigation Steps:

  • Categorize policies into critical (blocking) and non-critical (warnings).

  • Run non-critical policies asynchronously.

  • Use parallel execution for policy evaluations.

3. Blind Spots in Runtime Enforcement

Policies are enforced during CI/CD but not monitored at runtime, allowing post-deployment drift.

Mitigation Steps:

  • Integrate runtime checks using tools like OPA Gatekeeper or Cloud Custodian.

  • Implement drift detection workflows to monitor policy violations in real-time.

4. Human Error in Writing Policies

A poorly written policy inadvertently allows misconfigured resources to pass checks (e.g., wide-open S3 bucket policies).

Mitigation Steps:

  • Use linting tools like Regal to validate policy syntax and structure.

  • Test policies against a set of misconfiguration scenarios.

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