By Or Weis
Discover how leveraging a policy-as-code platform helps foster an engineering culture focused on efficient authorization and access control.
Platform engineering is rooted in a fundamental principle: cultivating a culture within development teams. This culture is not merely about saving time or streamlining development processes. Rather, it's about creating superior products through the application of standards and well-defined solutions, providing developers with clear guidelines where they might otherwise struggle to find direction.
In crucial areas like security and observability, such a culture is the difference between scalable success and inefficiency.
In this article, we will explore how we successfully implemented such a culture, specifically in the context of permissions and authorization for our product users. We believe that our approach can serve as a valuable model for creating more effective platform engineering teams.
One of the challenges developers often experience with the amount of data our applications process is the complexity of managing a vast web of policies that govern the permissions over this data. Managing the authorization of users and systems has become an increasingly challenging task.
In recent years, Policy-as-Code has emerged as a compelling solution. Tools like Rego and Cedar, which use domain-specific languages, bring the rigor of software engineering to the world of policy management, allowing teams to express rules clearly and enforce them consistently.
We've witnessed firsthand the transformative impact of integrating a Policy as Code culture within organizations, especially when it comes to navigating the complexities inherent in modern software development and data management.
Policy as code essentially involves translating organizational rules and procedures into code. This approach draws on a fundamental insight: complex logic is most effectively managed and understood when expressed as declarative code. The beauty of this approach is that it leverages best practices from software development—such as version control, CI/CD, testing, and code reviews— empowering us with the tools to handle policies with the same level of scrutiny and flexibility as our software.
By encoding policies in a declarative language, we ensure that all aspects of compliance and security are handled in a uniform, traceable way. This approach not only makes policy management more efficient but also makes auditing and troubleshooting more straightforward.
Policy as code is also one of the biggest enablers of the fine-grained authorization motion, where we can give our users the exact permissions they need without compromising on our applications’ code limitations.
While Policy-as-Code greatly simplifies policy enforcement, it’s not a silver bullet. While it significantly streamlines policy management, several challenges remain, particularly concerning its implementation. How do we ensure that Policy-as-Code is applied consistently across an organization? How can we make it accessible to those without a development background? And perhaps most importantly, how do we choose the right Software Development Life Cycle (SDLC) models that align with Policy-as-Code?
Consider the scenario of a shared database or message queue that houses sensitive data. This data, once it leaves its original source, can be transformed by various services or their consumers, often as part of Extract, Transform, Load (ETL) flows. Ensuring that our policies protect this data across different teams and services requires a unified approach that is challenging to scale across diverse teams or developers.
This difficulty stems not from technical limitations but from cultural ones. As different developers contribute to the software, a phenomenon known as 'code drift' occurs, where deviations from the initial policy intentions compromise the policy's effectiveness.
As your team grows, maintaining alignment on policy intent becomes increasingly difficult, especially as data schemas evolve and services change.