OPA (Open Policy Agent) VS spicedb

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)

Have you taken a look at SpiceDB? The Authzed blog has a few posts that are useful to improving your understanding -- I can think of two: New Enemies and Writing relationships to SpiceDB.

Things I can't live without in a new Go project in no particular order:

- https://github.com/golangci/golangci-lint - meta-linter

- https://goreleaser.com - automate release workflows

- https://magefile.org - build tool that can version your tools

- https://github.com/ory/dockertest/v3 - run containers for e2e testing

- https://github.com/ecordell/optgen - generate functional options

- https://golang.org/x/tools/cmd/stringer - generate String()

- https://mvdan.cc/gofumpt - stricter gofmt

- https://github.com/stretchr/testify - test assertion library

- https://github.com/rs/zerolog - logging

- https://github.com/spf13/cobra - CLI framework

FWIW, I just lifted all the tools we use for https://github.com/authzed/spicedb

We've also written some custom linters that might be useful for other folks: https://github.com/authzed/spicedb/tree/main/tools/analyzers

At AuthZed, we think about this topic regularly while developing SpiceDB[0], except we believe feature flags are a subset of authorization. I'd disagree with the author that permissions are always long-lived -- authorization can also be ephemeral (and often that's how it's most secure) or dependent on run-time context[1]. What's more, using SpiceDB, we can often collapse checking for authorization and feature-flags into a single round-trip by defining a permission that can additionally require a feature flag (e.g. permission = admin & has_feature_flag).

It's a little silly, but lots of folks ask for the moon when it comes to performance for authorization because it's critical to every request, but then go on and sprinkle a dozen feature flag RPCs each adding more and more latency. We think you should be able to have both.

What we're excited about is use cases beyond feature flags and authorization: we've also seen some folks use SpiceDB as an update graph or others as a dependency graph.

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

[1]: https://authzed.com/blog/caveats/

It scaled well compared to a naive graph abstraction implemented outside the database, but when performance wasn't great, it REALLY wasn't great. We ended up throwing it out in later versions to try and get more consistent performance.

I've since worked on SpiceDB[1] which takes the traditional design approach for graph databases and simply treating Postgres as triple-store and that scales far better. IME, if you need a graph, you probably want to use a database optimized for graph access patterns. Most general-purpose graph databases are just bags of optimizations for common traversals.

[0]: https://github.com/quay/clair

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

I get the sentiment. We held off on building an operator until we felt there was actually value in doing so (for the most part, Deployments cover the operational needs pretty well).

Migrations can be run in containers (and they are, even with the operator), but it's actually a lot of work to run them at the right time, only once, with the right flags, in the right order, waiting for SpiceDB to reach a specific spot in a phased migrations, etc.

Moving from v1.13.0 to v1.14.0 of SpiceDB requires a multi-phase migration to avoid downtime[0], as could any phased migration for any stateful workload. The operator will walk you through them correctly, without intervention. Users who aren't running on Kubernetes or aren't using the operator often have problems running these steps correctly.

The value is in this automation, but also in the API interface itself. RDS is just some automation and an API on top of EC2, and I think RDS has value over running postgres on EC2 myself directly.

As for helm charts, this is just my opinion, but I don't think they're a good way to distribute software to end users. The interface for a helm chart becomes polluted over time in the same way that most operator APIs become polluted over time, as more and more configuration is pulled up to the top. I think helm is better suited to managing configuration you write yourself to deploy on your own clusters (I realize I'm in the minority here).

[0]: https://github.com/authzed/spicedb/releases/tag/v1.14.0

To my understanding, the only ReBAC system that supports dynamic attributes is SpiceDB.

If you're curious to see a Postgres-based implementation, SpiceDB has a Postgres driver: https://github.com/authzed/spicedb/tree/main/internal/datast...

Interesting, for SpiceDB[0], one place we've struggled with MySQL is preemptively establishing connections in the pool so that it's always full. PGX[1] has been fantastic for Postgres and CockroachDB, but I haven't found something with enough control for MySQL.

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