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Compliance Without Complexity: Introducing Harness Rego Policy Packs | Harness Blog

Shift governance left with out-of-the-box Policy-as-Code. Simplify compliance and achieve continuous audit readiness across your entire SDLC.

In the fast-paced world of modern software delivery, compliance is often a bottleneck. While our existing OPA-based Policy as Code feature has long empowered teams to encode complex authorization checks and enforce granular governance across their DevOps workflows, we know that starting from a blank page can be daunting. Security and governance teams struggle to keep up with the volume of releases, while developers often find the initial setup of these policies to be time-consuming.

Today, we are thrilled to announce a significant leap forward in automated governance: Policy Packs.

What Are Policy Packs?

Policy Packs are a curated library of pre-written Rego policies designed to align your software delivery lifecycle (SDLC) with the most popular compliance frameworks.

By providing out-of-the-box policies, we are eliminating the primary barrier to automated governance: the need to write and maintain complex Rego code from scratch. With Policy Packs, you can adopt industry-standard guardrails by adapting our out of the box policies from the policy packs with zero to little customization. This will allow your teams to focus on shipping features rather than writing policy.

Comprehensive Framework Coverage

Our Policy Packs initiative covers the frameworks that matter most to your business and your auditors:

  • SOC 2: Focuses on trust service criteria like security, availability, and processing integrity. Our policies help enforce peer-reviewed pull requests and automated change management gates.
  • NIST: Specifically targeting SP 800-53 and 800-171, these policies cover configuration management, system integrity, and supply chain risk management via automated SBOM generation and SLSA provenance.
  • PCI DSS: Designed for organizations handling payment card data, these policies enforce secrets management, network segmentation, and mandatory vulnerability patching.
  • HIPAA & HITRUST: For those dealing with protected health information (PHI), these packs provide automated data leakage prevention and secure API monitoring.

Turning Framework Requirements into DevOps Controls

Compliance is no longer just a "point-in-time" audit; it’s a continuous process. Policy Packs map technical events directly to framework controls, providing the evidence your GRC teams and auditors need.

Compliance Framework Control Domain DevOps Implementation OPA/Rego Policy Evidence
NIST Special Publication 800-53 Configuration Management (CM) Policy checks in CI/CD pipelines, Infrastructure as Code (IaC) validation Rego policies deny infrastructure changes that do not meet approved configuration baselines, such as missing required resource tags, unapproved regions, or insecure defaults.
NIST Special Publication 800-53 Access Control (AC) Least-privilege IAM automation and Kubernetes admission controls Rego policies prevent deployments that create excessive permissions, require approved IAM roles, and block publicly accessible resources.
SOC 2 Change Management (CC8.1) Pull request reviews, protected branches, CI/CD approval gates, and deployment traceability Rego policies verify that production changes include peer approvals, linked tickets, successful pipeline checks, and required metadata before release.
SOC 2 Logical Access Controls (CC6.1) Automated identity provisioning, role-based access control (RBAC), and secrets management integration Rego policies prevent excessive privileges and block workloads using unmanaged credentials.
Health Insurance Portability and Accountability Act (HIPAA) Access Control (§164.312(a)) API authorization controls, workload identity, and protected health information (PHI) access enforcement Rego policies deny unauthenticated or unauthorized API requests, require approved FHIR resource access patterns, and enforce encryption requirements for PHI workflows.
Health Insurance Portability and Accountability Act (HIPAA) Audit Controls (§164.312(b)) Centralized logging, immutable audit trails, and security event monitoring Rego policies require audit logging configuration on services handling PHI and block deployments without required monitoring integrations.
Payment Card Industry Data Security Standard (PCI DSS) Vulnerability Management (Requirement 6) Automated dependency scanning, container image scanning, and security checks integrated into CI/CD Rego policies deny deployments containing critical or high-severity vulnerabilities, unsupported software versions, or unapproved container images.
Payment Card Industry Data Security Standard (PCI DSS) Secure Configuration (Requirement 2) Hardened container images, secure cloud configurations, and automated infrastructure checks Rego policies enforce secure baseline configurations, disable insecure services, and require approved encryption and network settings.
ISO/IEC 27001 Asset Management (A.5.9) Automated asset inventory, cloud resource discovery, and IaC governance Rego policies prevent unmanaged resources from being deployed and require ownership metadata on infrastructure assets.
CIS Critical Security Controls Secure Configuration of Enterprise Assets (Control 4) Kubernetes policy enforcement, cloud security posture management, and automated compliance checks Rego policies block insecure configurations such as privileged containers, open security groups, and missing security contexts.

Common Compliance Challenges in DevOps

In our work with industry leaders, like those in highly regulated industries such as healthcare, finance, or insurance, we’ve seen that compliance is often a manual, high-friction process that slows down software delivery. Two of the most common challenges teams face are:

  • The "audit readiness" blind spot: Teams often struggle to prove that their pipelines are consistently secure. Without automated guardrails, compliance is only checked during point-in-time audits, leaving gaps that are hard to identify and remediate.
  • The manual approval bottleneck: Many organizations rely on manual checkpoints to satisfy framework requirements. This frustrates developers who want to move fast, leading to "compliance fatigue" where processes are bypassed or ignored.

Harness Policy Packs address these challenges by shifting governance left, embedding compliance checks directly into your CI/CD pipelines so that validation happens automatically with every commit.

Example Policy: Enforcing Separation of Duties

A classic requirement for frameworks like SOC 2 and NIST is "Separation of Duties." In a modern DevOps workflow, this means the person who writes and commits the code cannot be the same person who approves the deployment to production.

To enforce this, a compliance policy in your pipeline would verify the identity of the commit author against the identity of the deployment approver. If the system detects that the author and the approver are the same individual, the policy automatically blocks the deployment. This ensures that every production change has been independently peer-reviewed, providing auditors with a tamper-proof guarantee that your internal controls are working as intended without requiring manual intervention from your GRC team.

Why This Matters

  1. Shift governance left: Catch violations before they ever reach production by enforcing policies during the save, run, or step phases of your pipeline.
  2. Accelerate audit readiness: Move from "preventing risk" to "proving compliance" with a tamper-proof evidence vault that stores all builds, scans, and approvals.
  3. Reduce risk: Mitigate legal and audit risks by using policies that are directly mapped to specific framework controls.
  4. Universal coverage: Whether you are using CI, CD, Feature Management, or Cloud & AI Cost Management, our one framework provides cross-module coverage across the entire platform.

Get Started Today

The journey to automated compliance doesn't have to start with a blank page. Get access to our policy packs in the repository here to get started. You can leverage our native Git integration for OPA rego policies to fork the policies from the repository linked above and import them into your account.  

Get ready to stop audit delays before they start. 

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Related Resources

The AI Velocity Paradox: Why Faster Code Creation Is Breaking Software Delivery

Continuous Delivery & GitOps

The AI Velocity Paradox: Why Faster Code Creation Is Breaking Software Delivery

October 14, 2025

Eric Minick

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Time to Read

Every engineering leader I talk to is asking the same questions about AI coding assistants: How much faster can we ship? How much more productive can my developers be?

On the surface, the answers look pretty good. The 2025 "State of AI in Software Engineering" report from Harness found that 63% of organizations report shipping code to production faster since adopting AI. Developers certainly feel more productive, and who are we to argue with feelings?

Here's the thing, though: this acceleration is telling a more complicated story. While developers are spending less time typing, a study from the research nonprofit METR found that for experienced developers, the impact of AI could actually be negative, even though they felt that they were moving faster.

This highlights a growing consensus I'm seeing across the industry: we are facing an AI Velocity Paradox. AI makes generating that first draft of code easier than ever. But figuring out if that code is actually good—functional, performant, and secure—well, that still takes time.

What we’re seeing is that when you hold the quality bar high as METR did, velocity can sometimes dip with AI. More often, organizations are letting their quality bar slip, and stability issues are emerging in production. AI is supercharging the front end of the software development lifecycle (SDLC), and this flood of new code demands a serious upgrade to our feedback loops—the core promise of DevOps—to manage all this change.

How AI is Reshaping a Developer’s Day

Let’s be clear: AI is absolutely changing the coding experience. The latest DORA "State of AI-assisted Software Development" report found that AI adoption now positively correlates with software delivery throughput—a complete reversal from the previous year. Developers say it's great for boilerplate, scaffolding, and getting quick options on the table.

But to get the full picture, we have to look at how the work itself is changing.

While developers feel faster, the METR study uncovered a critical nuance: the work isn't eliminated—it changes. The cognitive load moves from typing to a whole new, demanding set of tasks: specifying what’s needed, validating the AI's output, carefully reviewing its logic, hunting for subtle bugs, and trying to integrate it into a decade's worth of architectural decisions the AI knows nothing about. Think less bricklayer, more architect meets building inspector.

This shift from creation to verification is so profound that the METR study found experienced developers sometimes took 19% longer on certain tasks, even as they felt more productive. The end result is the same: a firehose of new code, pull requests, and changes aimed directly at your delivery pipeline. And frankly, that pipeline is starting to buckle.

Part 2: The Downstream Bottleneck

This is the heart of the AI Velocity Paradox. In the Harness report, a respondent put it perfectly, describing it as "squeezing a balloon - the volume of work stays the same, it's just forced from one side to another".

The data backs this up. The imbalance in automation across the SDLC is stark. While coding workflows are 51% automated on average, that number drops to just 43% for CI/build pipeline creation and continuous delivery. We're simply generating code faster than we can validate and deploy it.

The consequences are as predictable as they are severe:

  • Increased Failures: Nearly half (45%) of all deployments linked to AI-generated code lead to problems.
  • Rising Instability: The DORA report found that while throughput is up, AI adoption is still associated with a problematic increase of about 9% in “software delivery instability”. Their conclusion is blunt: our systems "have not yet evolved to safely manage AI-accelerated development".
  • Growing Risk: Almost half (48%) of teams in the Harness report are worried they will see an increase in software vulnerabilities from using AI coding assistants. I think that might be an optimistic take.

We’re driving faster on bad roads. Sometimes we get there faster. Sometimes we crash.

Part 3: The DevOps Decoupling Point - How to Win

So what does this mean? How do you tackle the paradox?

Code generation isn’t the problem. The feedback loop is. How quickly can you determine if a change is beneficial or detrimental? How fast can you fix it if it's not? Amplifying these feedback loops is DevOps 101, and it's never been more critical. The answer isn't in the code creation phase, but in everything that comes after it.

Both the DORA and Harness reports, despite their different approaches, converge on a single, powerful conclusion: mature DevOps practices are the critical mitigating factor. This is the decoupling point that separates the teams who are just creating chaos faster from those who are actually delivering value faster.

The Platform as an Amplifier

The DORA report highlights a key finding regarding the importance of having a "quality internal platform". A good platform is what operationalizes these feedback loops at scale, giving you standardized pipelines, automated governance, and developer-friendly guardrails. It’s the foundation you need to let the benefits of AI actually scale. DORA's research found that a high-quality platform literally amplifies the positive effects of AI adoption on organizational performance.

The Power of Good Continuous Delivery (CD)

The Harness report delivers a stunning statistic: organizations with moderate automation in their CD processes are more than twice as likely to see a velocity gain from their AI coding tools compared to those with low automation. A robust, automated CD pipeline gives you a tight, reliable feedback loop for that deluge of new code.

Bottom line: both reports are saying the same thing. To solve the problems created by AI at the beginning of the lifecycle, you must invest in the systems that manage the end of it—you must invest in the feedback loop.

Conclusion: From AI-Assisted Coding to an AI-Powered System

If the first chapter of AI in software development was about individual productivity, the next chapter is all about systemic health. The paradox is real: just handing developers AI assistants without upgrading your delivery infrastructure is a recipe for riskier, more chaotic releases. And let's be honest, if stability continues to slip it won’t take long for the business to tell us to slow down. 

The path forward starts with the fundamentals. The Harness report shows a huge jump in success just by moving from low to medium CD maturity. A solid foundation of basic DevOps and automated testing is the first step to handling today's AI-assisted reality.

But we have to look ahead, too. Today, developers use AI chat interfaces and in IDE based assistants. Tomorrow, they might be acting as "first-line managers" for teams of autonomous coding agents. In that future, the sheer volume of change will be unimaginable, and "basic" DevOps won't cut it. The feedback loops will need to be instantaneous and intelligent. We'll need AI woven into the very fabric of DevOps—AI-powered verification, AI-driven testing, and intelligent pipeline orchestration, just to keep our heads above water.

Start building that foundation now. The paradox is a warning, sure, but it's also a massive opportunity to build the resilient, high-performing systems that will define the next era of software development.

Learn more: Best DevOps Automation Tools to Streamline Software Delivery

Introducing Harness Policy as Code, Powered by OPA

Harness Platform

Introducing Harness Policy as Code, Powered by OPA

May 11, 2022

Avantika Mathur

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We’re excited to announce Harness Policy as Code, powered by Open Policy Agent (OPA), a centralized policy management and rules service that empowers enterprises to centrally define and monitor policies that are enforced across all delivery pipelines and processes. Harness Policy as Code helps organizations create and enforce policies on deployments, infrastructure, and more, providing developer velocity without sacrificing compliance and standards.

Harness Policy as Code is based on OPA, an easy-to-use, extensible solution for creating and enforcing policies across the entire stack. OPA is an open source project accepted by the Cloud Native Computing Foundation (CNCF) with wide adoption across numerous software delivery use cases. Policies are written as declarative code, so they are easy to understand and modify—from simple to complex use cases.

Harness Policy as Code integrates with CI, CD, and Feature Flags enforcing automated approvals, denials, and other advanced pipeline functionality. Check out our technical documentation to learn more.

Why We Need Policy Management in Software Delivery

As DevOps is adopted within an enterprise, typically one team creates and maintains software delivery and processes. That team has full control and visibility, as they are the ‘creator’ of DevOps processes within the company. As more business units adopt DevOps within the company, that originating team’s manual processes can create a bottleneck, which hampers innovation by limiting team autonomy and slowing down software delivery.

 In an effort to remove the bottleneck and increase velocity, companies can give development teams more autonomy by allowing them to drive their own DevOps processes. That decentralization of process control can lead to more risks for the company.

When governance is decentralized, development teams can miss quality checks or approvals, introduce vulnerabilities, or break compliance. Organizations need to balance autonomy and governance, so they can empower teams with the confidence that they are adhering to all compliance standards and security policies – all without slowing down innovation.

Compliance becomes even more critical in regulated industries, such as financial services and healthcare—not only with enterprise standards, but with third-party regulations, like SOC2, PCI, and FedRamp. It is imperative that all software delivery pipelines meet compliance standards with full auditability; otherwise, the organization is at risk of failed audits, heavy fines, and reputational damage. 

Centralized management and governance of policies across DevOps processes allow enterprises to define standards for the entire organization while enforcing compliance with regulations. Policies enable individual teams to have autonomy over their processes with oversight and guardrails in place to prevent them from straying from standards, ensuring secure and compliant software delivery. 

Harness Policy as Code Features

Harness Policy as Code is a centralized policy management and rules service that leverages OPA to meet compliance requirements across software delivery. HPE enables organizations to centrally define and monitor policies that are enforced across all delivery pipelines and processes. 

Policy as Code features for writing and enforcing policies include:

  • A Policy Editor that enables developers to start writing policies-as-code quickly. With a library of policies to start from and a testing terminal, developers can try out policies on real inputs during development before enabling them.
  • Policies that are configured to be automatically enforced on Harness processes (e.g. on Pipeline Run, on Feature Flag save).
  • The ability to set severity, so a policy violation can issue a warning or throw an error to stop processes from continuing.
  • An audit trail that can maintain a full history of policy evaluations with detailed outputs for audit and compliance.
Harness Edit Policy screen showing Rego code for pipeline approvals alongside a library of sample policies
Sample policies that can be customized.

With the release of Policy as Code, policies can now be enforced on CI and CD pipelines and Feature Flags.

Pipeline policies govern the requirements of delivery pipelines, and they can be automatically enforced when the pipeline is saved or triggered, or even in the middle of pipeline execution. Policies can enforce specific pipeline configuration, advanced access control use cases, runtime validation, and more. Here are some examples of what the Policy as Code can do: 

  • Require an approval step before deployment to production.
  • Forbid use of Shell scripts in the pipeline.
  • Only allow deployment to approved namespace.
  • Only allow deployments from approved container registries.
  • Validate test step outcome meets minimum threshold before allowing the pipeline to continue.
Harness Policy Engine
A pipeline that could not be deployed due to policy noncompliance. 

Policies for Feature Flags are enforced when the flag is updated or toggled on/off, enabling policies for adhering to standards, flag process, and hygiene. This includes:

  • Only allowing creation of boolean flags.
  • Enforcing flag naming conventions.
  • Enforcing when creating a flag the default on and off values must both be false.
  • Requiring a Feature Flag be enabled in QA before it can be turned on in Production.

Policy as Code centralizes and standardizes policy management across software delivery, allowing engineering leaders to empower dev teams to own their tools and practices while ensuring that everyone is following company standards for compliance and security. With guardrails in place, security vulnerabilities won’t be introduced as development teams are writing their pipelines. Leaders can rest assured that compliance standards are being met, with full auditability of policies and failures, and they can find and report breaches as early as possible with shift-left governance.

Get Started

Check out our platform governance page to learn more about how Harness' modern approach to software delivery governance empowers teams with stable processes that don’t slow down delivery, or request your personalized demo today.

Announcing OPA Policy Evaluation on Your Own Infrastructure

Continuous Delivery & GitOps

Announcing OPA Policy Evaluation on Your Own Infrastructure

June 9, 2026

Abhijit Pujare

+ more
Time to Read

Let's face it: "move fast and break things" is a great way to end up sitting in a war room at 3:00 AM. Engineer burnout is at record highs, we don’t need sloppiness to hurt us further.

Look. Here’s the reality: thanks to AI code generation tools, we are writing more code than ever before. Delivering that with pipelines built for human-speed development? That’s become the chokepoint. Everything in delivery needs to get faster and better. That includes governance. 

We’ve long used Open Policy Agent (OPA) to embed automated governance directly into delivery pipelines to stop teams from cutting corners. OPA is Policy as Code and by default evaluates on our secure cloud infrastructure. But for large, highly regulated enterprises, corporate firewalls and strict data residency rules present a classic dilemma: 

What happens when a policy needs to access data that resides within a corporate firewall? How do we run these policies so that they connect to internal systems securely and access that data within the corporate trust boundary?

We’re tackling that challenge now. New to Harness is the ability to evaluate OPA Policies on Local Infrastructure.

The Architectural Hurdle: Firewalls & Local Secrets

Platform and security engineering teams love OPA because it allows them to gate pipelines based on real-time business logic. For example, you may want to implement a waiver or exceptions workflow that grants a one-time exception to a specific Policy from being broken. And you may want to track that a waiver was issued in a ticketing system like ServiceNow.

However, executing this evaluation in a standard SaaS model breaks down when:

  1. The Target System you are querying is Inbound-Protected: Your internal ticketing system, database schema verifier, or proprietary security scanner lives deep behind your corporate firewall.
  2. Secrets Must Stay Local: To query that internal system, OPA needs an API token, certificate, or password. Sending that credential to an external cloud environment—even one as secure as Harness—is often an immediate veto from Chief Information Security Officers (CISOs).

Historically, teams had to choose between drilling holes in their firewall, duplicating infrastructure, or reverting to manual spreadsheets and agonizing verification meetings.

Enter Local OPA Evaluation on Kubernetes

With this new capability, Harness lets you direct the OPA evaluation engine to run in your own environment (specifically on your local Kubernetes clusters).

How It Works

Instead of pulling your secure internal metrics out to the cloud for policy validation, Harness sends the evaluation intent down to your local cluster. The evaluation triggers locally, pulls secrets natively from your secure environment, queries your private behind-the-firewall tools, and passes a simple, immutable Pass/Fail status back to the Harness pipeline

Screenshot illustrating: How It Works

This approach delivers the best of both worlds: the ease and scalability of a unified platform control plane, backed by the absolute security of local execution

See It: Gating Pipelines on Secure Ticket States

Consider a classic enterprise scenario: gating a production deployment based on an internal ticketing system.

If the ticket is approved, the sync proceeds automatically. If the ticket is canceled, pending, or in an unexpected state, the pipeline halts or triggers an automated rollback strategy before any risk is introduced to production. Because the execution stays within your perimeter, your ticketing credentials remain entirely untouched by external systems.

Check out this quick demo video to see exactly how to configure your Kubernetes cluster to handle OPA evaluations locally:

Use Cases 

Use Case 1- Allowing for OPA waivers/exceptions

A common pattern we saw amongst our customers was they wanted an “exceptions” or  “waiver” workflow where customers, for certain use cases, could waive a failed OPA policy for a particular scenario. Let’s take the following example:

  1. You have a pipeline that has an OPA policy mandating that there’s >95% test coverage before a deployment is done
  2. A hotfix comes in at the last minute that fails the 95% test coverage
  3. Given the urgency of the situation, you want to bypass the OPA policy 

In these kinds of situations, teams often want some kind of mechanism to allow a waiver where they allow the pipeline to run this one specific time due to special circumstances. Additionally, customers want to keep track that a waiver was issued in a third-party ticketing system (like JIRA or ServiceNow). With the Local OPA evaluations capability, you can now write policies that query the internal ticketing system as shown above.

Use Case 2 - Using OPA to check for Pipeline Tampering

Another common authorization workflow we saw was customers trying to ensure that their pipeline YAMLs hadn’t been tampered with. For example, customers often want to ensure that the pipeline they have authored and stored in Harness SaaS is exactly the one that runs at the time of deployment. They want to ensure that no third party tampers with the pipeline YAML before it is actually being run. The approach we saw customers take was the following:

  1. They would author a pipeline in Harness SaaS
  2. They would take the pipeline YAML and take a hash of the pipeline
  3. They would store the hash of the pipeline within their internal database/system
  4. At the time of the pipeline actually running, they compare the hash of the “correct pipeline” with the hash of the pipeline being run to check for equivalence

The steps outlined above allow for ensuring that nobody has tampered with the pipeline’s yaml before it is run. However, to write a rego policy that can actually do a hash code equivalence check (step 4) you need to make a call to the internal database system where the hash code of the correct pipeline lives. This again necessitated having the rego policy read credentials and connect to a 3rd party system. Again, one way to solve this problem was to allow customers to run these OPA policies on their own K8s clusters.

Use Case 3 - Very Large or Sensitive Payloads

Finally, some customers use our custom policy step action to perform an authorization check midway through a pipeline. For several of these situations, customers want to send data for the OPA policy to check that is sensitive in nature. For such use cases, they don’t want the sensitive payload to be sent to the OPA service running in Harness SaaS. Instead they want the payload to be sent to the OPA rego policy running in their own infrastructure.

Zero Friction, Maximum Compliance

So, what does this mean for your daily operations?

The beauty of local OPA evaluation is that your developers won't notice a single change in their daily workflow. They continue to leverage the fastest builds and automated continuous delivery pipelines they love.

Meanwhile, Platform Leaders gain a comprehensive, immutable audit trail of every single evaluation, ensuring painless compliance reviews without hampering developer velocity.

Ready to eliminate toolchain chaos and secure your deployment guardrails? Get started with Harness Continuous Delivery & GitOps today.

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Abhijit Pujare
Senior Product Manager
Abhijit Pujare is a Senior Product Manager at Harness, where he leads product strategy and execution for developer productivity and software delivery solutions.
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Abhijit Pujare
https://www.linkedin.com/in/abhijit-pujare/
Vishal Vishwaroop
Senior Developer Relations Engineer
Vishal Vishwaroop is a senior Developer Relations Engineer.
vishal-vishwaroop
Vishal Vishwaroop