pluto VS OPA (Open Policy Agent)

You can get all the code for this example from here. This link provides an online IDE for this sample application. Click the Fork button in the upper right corner to create your own development environment, and then you can directly modify the code and deploy it to AWS in the browser.

Big Data Scenario: Word Count

Plutolang - Pluto is a new open-source programming language designed to help developers write cloud applications, making it easier to utilize cloud services. Developers can directly use required resources such as KV databases and message queues in their code based on business needs. Pluto uses static code analysis to obtain the infrastructure resource topology the application depends on and deploys the corresponding resource instances and applications on the specified cloud platform or Kubernetes.

Developers define variables in their code, and Pluto takes care of automatically creating and managing the required cloud resource components based on those variables. This simplifies the process of deploying and managing cloud infrastructure, enabling developers to make better use of the cloud. Read more

I'm currently working on a project with a similar concept. However, at the moment, I am using static program analysis technology to infer infrastructure dependencies. But I am considering using AI to deduce the dependencies and generate the final Infrastructure as Code. So, in the architecture, we can replace the deducer and generator with an implementation using AI, as shown in the diagram.

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.

Rego is a declarative query language from the makers of the Open Policy Agent (OPA) framework. The Cloud Native Computing Foundation (CNCF) accepted OPA as an incubation-level hosted project in April 2019, and OPA graduated from incubating status in 2021.

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