Introducing Control Policies

Today, we are happy to announce our latest addition to ControlMonkey’s CI/CD solution – Control Policies! Control Policies provide customers with preventive controls to help them avoid errors and misconfigurations in production, making it an essential tool for DevOps teams.

With Control Policies, DevOps teams receive instant feedback for any proposed infrastructure configuration changes before they are deployed to their live environment. DevOps members get immediate input on any misconfigurations or non-compliant changes as part of their CI (Continuous Integration) pipeline, enabling them to take corrective action quickly and efficiently. Utilizing this GitOps methodology can save a significant amount of time that would otherwise be spent on reviewing incorrect code among DevOps team members.

ControlMonkey Preventive Controls

By offering preventive controls, ControlMonkey is taking a proactive approach to infrastructure management that can help organizations avoid costly mistakes. Compared to detective controls, which identify issues after they’ve occurred, preventive controls provide an opportunity to avoid those issues altogether. This means that Control Policies can help organizations reduce the risk of errors and misconfigurations in production, which can lead to costly downtime and lost revenue.

ControlMonkey’s Control Policies are cloud-ready, parameterized policies, which means that customers don’t need to use any specific programming language or be familiar with Terraform internals. This is a major advantage for organizations that may not have dedicated DevOps members to write policies on their own.
With Control Policies, customers can provide parameters according to their needs, and ControlMonkey takes care of the rest, including supporting different versions of Terraform and various plugin versions.

Some Examples

To better illustrate the capabilities of Control Policies, let’s explore a few examples of how they can be applied in real-world scenarios:

  1. Required Tags:  A customer can define that all of their resources should have specific tag keys and tag values. If a proposed change contains a resource without those tags the build will be blocked on ControlMonkey’s CI solution. This helps maintain consistency and compliance across your infrastructure and simplifies resource management.
  1. Allowed Regions:  A customer can define allowed regions in which resources can be spun up. If someone attempts to spin up resources in a different region, they will be blocked. This is highly relevant for GDPR compliance, as it helps organizations manage and maintain data residency requirements by restricting resource allocation to specific geographical locations.

These examples demonstrate the versatility and practicality of ControlMonkey’s Control Policies in addressing common infrastructure management challenges. By implementing such preventive controls, organizations can streamline their DevOps processes, save time, reduce risks, and enhance overall efficiency.

Introducing Control Policies

Overall, Control Policies are an essential feature that can help organizations manage their infrastructure delivery more efficiently and with fewer errors. If you’re looking for a reliable and efficient platform to manage your infrastructure, check out the ControlMonkey CI/CD pipeline with Control Policies today! 

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