OPA (Open Policy Agent) VS gatekeeper-library

How can we handle this? Are there any mechanisms to prevent or at least to some extent safeguard this kind of issues without falling back to a manual workflow? There is. One huge advantage of sticking to (de-facto) standards like Terraform is that first we are probably not the first ones to come up with this question and second there is a huge ecosystem around Terraform that might help us with such challenges. And for this specific scenario the solution is the Open Policy Agent. Let us take a closer look how the solution could look like.

A popular Policy-as-Code tool for Terraform is OPA, everyone's favorite versatile open-source policy engine that enforces security and compliance policies across your cloud-native stack, making it easier to manage and maintain consistent policy enforcement in complex, multi-service environments.

Harness Policy As Code uses Open Policy Agent (OPA) as the central service to store and enforce policies for the different entities and processes across the Harness platform. In this section, you will define a policy that will deny a pipeline execution if there is no approval step defined in a deployment stage.

OPA: While OPA is an open-source, general-purpose policy engine capable of enforcing unified and context-aware policies throughout the stack, it can also accept and output data in formats such as JSON, effectively functioning as a tool for generating or modifying configurations. Although it does not provide out-of-the-box schema definition support, it allows the integration of JsonSchema definitions.

In essence, container image signing involves adding a digital stamp to an image, affirming its authenticity. This digital assurance guarantees that the image is unchanged from creation to deployment. In this blog, I'll explain how to sign container images for Kubernetes using Cosign and the Open Policy Agent. I will also share a tutorial that demonstrates these concepts.

In this post we will explores two powerful solutions for addressing this issue: the Open Policy Language (OPA) and Google’s Zanzibar.

Now there are more subdivided practice: * Policy as Code: Sentinel, OPA * Database as Code: bytebase * AppConfiguration as Code: KusionStack, Acorn * ...... (Welcome to add more)

CIAM is not nearly as popular of a term as it needs to be. When most developers build apps today, they still look at their cloud provider's IAM or Active Directory for inspiration in design of their customer-facing systems. I think this article is actually understating the complexity. Conway's Law rules all and sometimes your systems and users won't even necessarily be in your control. I urge folks to look into policy engines like OPA[0] and ReBAC systems like SpiceDB[1] rather than reinventing the wrong wheel.

[0]: https://www.openpolicyagent.org

[1]: https://github.com/authzed/spicedb

Here is a library or rules for the Open Policy Agent.

Many more examples are available in the OPA Gatekeeper library project!

by default and exposes metrics on path ```/metrics``` . It can run locally on your development box as long as you have a valid Kubernetes configuration in your home folder (i.e. if you can run kubectl and have the right permissions). When running on the cluster a ```incluster``` parameter is passed in so that it knows where to look up for the cluster credentials. Exporter program connects to Kubernetes API every 10 seconds to scrape data from Kubernetes API. We've used [this](https://medium.com/teamzerolabs/15-steps-to-write-an-application-prometheus-exporter-in-go-9746b4520e26) blog post as the base for the code. ## Demo Let's go ahead and prepare our components so that we have a Grafana dashboard to show us which constraints have been violated and how the number of violations evolve over time. ### 0) Required tools - [Git](https://git-scm.com/downloads): A git cli is required to checkout the repo and - [Kubectl](https://kubernetes.io/docs/tasks/tools/) and a working K8S cluster - [Ytt](https://carvel.dev/ytt/): This is a very powerful yaml templating tool, in our setup it's used for dynamically overlaying a key/value pair in all constraints. It's similar to Kustomize, it's more flexibel than Kustomize and heavily used in some [Tanzu](https://tanzu.vmware.com/tanzu) products. - [Kustomize](https://kustomize.io/): Gatekeeper-library relies on Kustomize, so we need it too. - [Helm](https://helm.sh/): We will install Prometheus and Grafana using helm - Optional: [Docker](https://www.docker.com/products/docker-desktop): Docker is only optional as we already publish the required image on dockerhub. ### 1) Git submodule update Run ```git submodule update --init``` to download gatekeeper-library dependency. This command will download the [gatekeeper-library](https://github.com/open-policy-agent/gatekeeper-library) dependency into folder ```gatekeeper-library/library``` . ### 2) Install OPA/Gatekeeper If your K8S cluster does not come with Gatekeeper preinstalled, you can use install it as explained [here](https://open-policy-agent.github.io/gatekeeper/website/docs/install/). If you are familiar with helm, the easiest way to install is as follows: ```bash helm repo add gatekeeper https://open-policy-agent.github.io/gatekeeper/charts helm install gatekeeper/gatekeeper --generate-name

Gatekeeper library has example policies for restricting image repositories: https://github.com/open-policy-agent/gatekeeper-library/tree/master/library/general

You should check out the Gatekeeper project. There's plenty of templates available for use without having to write a single line of rego for most use cases (e.g https://github.com/open-policy-agent/gatekeeper-library)