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Orca's API documentation is a mess. Am I missing something?

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(@charlotte1)
Estimable Member
Joined: 3 months ago
Posts: 94
Topic starter   [#25009]

Hi everyone, I hope this is the right place for this. I’ve been quietly reading for a while, but this is my first real post, so please bear with me.

I’ve been tasked with looking into cloud security tools for our small business, and we’re currently evaluating Orca Security. Everyone talks about their agentless approach and the dashboard, which seems great, but I keep hitting a wall when I try to do anything programmatic. My background is more in the bookkeeping and operations side of SaaS tools, so maybe I’m just not looking in the right spot?

Specifically, I’ve been trying to use the API to pull some basic asset inventory data into our own internal reports. The documentation I’ve found feels… scattered? Like, some endpoints are documented in one portal, but then I find references to others only in old community posts. The examples often skip over the authentication setup, which I finally pieced together from three different pages. I spent a whole afternoon just trying to get a simple list of our cloud accounts to return correctly, and I’m still not sure I’m doing it the most efficient way.

I guess my question is: am I missing some central, well-maintained hub for their API docs? Or is the experience really this fragmented? Coming from tools like QuickBooks Online or Gusto, where the API documentation is very structured (even if it’s complex), I’m finding this surprisingly difficult to navigate. I really want to like Orca, but if this is a core part of their offering, it feels a bit discouraging.

Has anyone else gone through this and found a good workflow or a hidden gem of a resource? Any pointers would be so, so appreciated. I’m trying to build a solid case for our tooling stack, and thorough API support is becoming a bigger factor than I initially thought.



   
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(@danielm)
Honorable Member
Joined: 2 months ago
Posts: 453
 

No, you're not missing anything. Their API docs are exactly that scattered. It's a classic vendor move: the dashboard is the shiny product for the execs who sign the checks, while the API is an afterthought for the engineers who actually have to live with it.

Pulling asset data was a headache for us too. We found the real 'documentation' was often in their support portal, buried in replies to tickets from two years ago. The official examples tend to assume you're already authenticated and have the perfect, non-rate-limited test environment.

If you're still evaluating, make this a contractual point. Get specific about which API endpoints you need documented and maintained. Otherwise, you'll be paying for a 'programmatic' interface that your team has to reverse-engineer.


— skeptical but fair


   
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(@ashp99)
Honorable Member
Joined: 2 months ago
Posts: 377
 

Yeah, the docs are definitely fragmented. I had a similar experience trying to set up automated reports for cloud compliance last quarter.

Two things that helped me:
* Their Postman collection (if you can find the link) actually has more working examples than the written docs.
* For asset inventory specifically, the `/assets` endpoint is your friend, but the pagination parameters are key for pulling it into reports efficiently. The default limit is easy to miss.

Hope that saves you another afternoon


data over opinions


   
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(@davidn3)
Reputable Member
Joined: 2 months ago
Posts: 277
 

The scattered documentation is unfortunately common. Based on my work integrating their data into a warehouse, the problem is structural; they seem to update the API spec and the dashboard independently.

You're right to focus on authentication. The examples often omit that you need to generate an API key in the dashboard first, then pass it as a bearer token. For the `/assets` endpoint mentioned earlier, the critical detail for reporting is the `limit` and `next_token` parameters for pagination. Without them, you're only getting the first page.

If you're pulling for internal reports, structure your calls to handle that pagination and rate limiting from the start. The API's inconsistency becomes a major data quality issue downstream.


Data is the only truth.


   
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(@charliep)
Prominent Member
Joined: 3 months ago
Posts: 803
 

> Get specific about which API endpoints you need documented and maintained.

Good luck with that. You'll find they'll happily put that in the contract, and then the engineering team will still deprecate those endpoints with a 30-day notice because "the new dashboard uses a different data model." The contract covers documentation, not API stability.

The real cost isn't the reverse-engineering, it's the maintenance when their undocumented changes break your reports.


Your stack is too complicated.


   
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(@adrianm)
Estimable Member
Joined: 3 months ago
Posts: 146
 

That's such a crucial point, thank you. The hidden maintenance cost is what kills you. A "working" integration can turn into a silent failure if their changes affect a field your reports depend on.

My follow-up question would be: has anyone had success getting them to commit to a deprecation policy in the contract, like a six-month notice for breaking changes? Or is that something they just won't do?


still learning


   
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 annt
(@annt)
Reputable Member
Joined: 3 months ago
Posts: 339
 

> has anyone had success getting them to commit to a deprecation policy in the contract, like a six-month notice for breaking changes?

In my experience, they will not contractually commit to a deprecation policy for their API. The standard line is that the API is considered a feature of the core platform, which is subject to continuous improvement and change without such formal notice. We attempted to negotiate this last year, and the most we could secure was a clause stating they would "endeavor to provide reasonable notice" of deprecated functionality via their standard release notes, which is practically unenforceable.

The more viable, albeit labor-intensive, path is to build monitoring around the specific data fields your reports consume. Implement checks that alert you to schema changes, such as a missing expected field or a change in data type, as part of your ingestion pipeline. This shifts the burden to you, but it turns a silent failure into a managed event.


—at


   
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