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Interesting benchmarks. I'm surprised vLLM is performing so poorly given all the corporate investment/attention it's getting. Is it because the contributions are more distributed than the average LLM team?
Having worked on pricing strategy, this is not what I've seen as the norm in B2B. If you're talking to an early company that is still working on product market fit, maybe, and definitely if you ask for your own features.
If you're talking to larger companies, thing FAANG, then they have a list price and discount levels that can act as incentives, levers or there are other options for inducement. Otherwise, you give the sales team the authority on go-to-market strategy while they are executing individual deals (tactics). Senior sales leaders can authorize some of those discounts and any special inducements or incentives have to be custom written into contracts by legal + deal desk, making them more time intensive and less desirable.
A sponsorship / bounty program is an interesting train-of-thought. It certainly 'fits' into an open source ethos and might give the company the added benefit of positive marketing.
I just looked at the Github sponsors program and AFAICT, they only offer a recurring monthly plan which is probably not what either myself or the company are looking for. I'd be curious about more options though.
Generally speaking, I have found Atlassian’s tools don’t scale well to megacorp usage. When there are thousands to tens of thousands of users connecting at peak times, stuff just gets extremely slow. Noticeably slower than when we all put up our own team-level Phabricator instances, although I’m obviously not adjusting for Phabricator downtime when inevitably the unofficial team sysadmin went on vacation and the server fell over.
I’m sure people involved in infrastructure are working on making this better, but I don’t have any visibility into that layer.
From a speed standpoint, I'll say the obvious thing, "it's architecture dependent".
For thousands to tens of thousands of users, most folks need data center with 1+n nodes (w/ larger diminishing returns at 8 nodes). There's a few tips and tricks with that, like pointing CI/CD tools to a smart mirror instead of the primary instance and only mirroring specific build projects. Putting smart mirrors in the same physical location as a primary instance could also help reduce the impact of CPU-intensive requests like git fetch or clone.
Another common issue is apps/plugins. Bitbucket 5.9 added a way to get app diagnostics so infra folks can see if there's a long-running process or other weirdness. Vanilla Bitbucket needs about a 1gb heap (java) and with apps, you want around 4gb (give or take).
In a past life as a solutions engineer at a SaaS company, I'll address a couple points specific to a unified solution.
Problem 1: Not every SaaS platform has a company with an API to manage user accounts. Even then, I would be skeptical of a company that offered it and didn't offer it via oauth tokens.
Problem 2: Automating the task within the browser also fails when it comes to uniformity. Any company that lacks an API endpoint for user management means you need to interact with a browser or some other hacky nonsense. With that solution comes the problem of understanding the site structure, login forms, and action menus.
Problem 3: Even if you did the above 2, you now have additional points of failure within your offboarding. If a failure occurs in the automation process, is it silent? What if the API changes (not that it should) or the UI?
The best solution is to look for companies that offer the API option or that support SAML.
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