warrant VS Caddy

Warrant — Hosted enterprise-grade authorization and access control service for your apps. The free tier includes 1 million monthly API requests and 1,000 authz rules.

The specific challenge with authz in the app layer is that different apps can have different access models with varying complexity, especially the more granular you get (e.g. implementing fine grained access to specific objects/resources - like Google Docs).

Personally, I think a rebac (relationship/graph based) approach works best for apps because permissions in applications are mostly relational and/or hierarchical (levels of groups). There are authz systems out there such as Warrant https://warrant.dev/ (I'm a founder) in which you can define a custom access model as a schema and enforce it in your app.

Let's use warrant.dev as an example. The system provides a set of REST APIs for you to define object types and access policies (called warrants). The general process is first to create object types using HTTP POST:

https://warrant.dev/ (Provider) Relatively new authZ provider, they have a dashboard where you can manage your rules in a central location and then use them from multiple languages via their SDKs, even on the client to perform UI checks. Rules can also be managed programmatically via SDK.

I would describe this debate more as Policy-as-Data (Zanzibar) vs Policy-as-Code (OPA et al).

In Zanzibar, all of the information required to make an authorization decision (namespaces, relationship tuples, etc.) is stored in Zanzibar, and the decision engine resolves access checks based on this data. This data can be scaled horizontally (and consistently) as needed for an application’s needs. This makes Zanzibar a centralized, unified solution for all of an application’s authorization needs. I’ve found this approach more purpose built / well suited for application authorization.

With OPA and other policy engines, the data required for performing access checks lives somewhere else (maybe the application’s database) and must be separately queried and included as part of the authorization check because OPA et al. are stateless decision engines. This makes it such that you need to piece together data from different sources in order to get your final decision, which IMO is something most developers don’t want to deal with.

On the flip side, Zanzibar’s “namespaces” are a very simple policy layer not well suited to querying against data outside of Zanzibar’s scope (e.g. geolocation, time, etc). For scenarios like this, a full fledged policy-as-code solution is great. However, it should be noted that some open source Zanzibar implementations like Warrant[1] and SpiceDB[2] (mentioned in the article) also offer a policy-as-code layer on top of Zanzibar’s graph-based/ReBAC approach to tackle these scenarios.

Disclaimer, I’m one of the founders of Warrant.

[1] https://github.com/warrant-dev/warrant

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

Hey HN, I recently shared my thoughts on why Google Zanzibar is a great solution for implementing authorization[1] and why we decided to build Warrant’s core authz service using key concepts from the Zanzibar paper. As I mentioned in the post, we recently open sourced the authz service powering our managed cloud service, Warrant Cloud[2], so I thought I’d share it with everyone here. Cheers!

[1] https://news.ycombinator.com/item?id=36470943

[2] https://warrant.dev/

More than two years after choosing to build Warrant atop Zanzibar’s core principles, we’re extremely happy with our decision. Doing so gave us a solid technical foundation on which to tackle the various complex authorization challenges companies face today. As we continue to encounter new scenarios and use cases, we’ll keep iterating on Warrant to ensure it’s the most capable authorization service. To share what we learn and what we build with the developer community, we recently open-sourced the core authorization engine that powers our fully managed authorization platform, Warrant Cloud. If you’re interested in authorization (or Zanzibar), check it out and give it a star!

These projects use Caddy as my local development server, Dart Sass for converting my Sass files to CSS, elm, elm-format, elm-optimize-level-2, elm-review, elm-test (only in Calculator), ShellCheck to find bugs in my shell scripts, and Terser to mangle and compress JavaScript code.

No, look at the associated unit test: https://github.com/caddyserver/caddy/blob/c6eb186064091c79f4...

If that test fails we could serve PHP source code instead of having it be evaluated, a major security flaw.

However, it's very unlikely that .NET developers will directly expose their Kestrel-based web apps to the internet. Typically, we use other popular web servers like Nginx, Traefik, and Caddy to act as a reverse-proxy in front of Kestrel for various reasons:

I think that recompiling with upgraded Go will not solve the issue. It seems Caddy imports `golang.org/x/net/http2` and pins it to v0.22.0 which is vulnerable: https://github.com/caddyserver/caddy/issues/6219#issuecommen....

Caddy [1] is a single binary. It is not minimal, but the size difference is barely noticeable.

serve also comes to mind. If you have node installed, `npx serve .` does exactly that.

There are a few go projects that fit your description, none of them very popular, probably because they end up being a 20-line wrapper around http frameworks just like this one.

[1] https://caddyserver.com/

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

So I dug a little deeper and came across this gem: Caddy. Caddy is this fantastic, extensible, cross-platform, open-source web server that's written in Go. The best part? It comes with automatic HTTPS. It basically condenses all the work our scripts and manual maintenance were doing into just 4-5 lines of config. So, stick around and I'll walk you through how to set up an automatic SSL solution with Caddy, Docker and a Node.js server.

Let's use Caddy which can act as reverse-proxy with automatic HTTPS coverage.

Even if it may be simple, it doesn't handle edge cases such as https://github.com/caddyserver/caddy/issues/1632

I personally would make the trade off of taking on more complexity so that I can have extra compatibility.

One of the most heavily used Russian software projects on the internet https://www.nginx.com/blog/do-svidaniya-igor-thank-you-for-n... but it's only marginally more modern than Apache httpd.

In light of recently announced nginx memory-safety vulnerabilities I'd suggest migrating to Caddy https://caddyserver.com/