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"There's a saying in programming: make the easy things easy and the hard things possible," Pennarun said. "There's lots of products out there that make the hard things possible. But surprisingly, there's very few products that make the easy things easy."

That might be good advice for enterprise tech entrepreneurs: Tailscale has raised $150 million in funding since it was founded in 2019 and just hit the 100-employee milestone. The dirty secret of enterprise tech is that most companies don't need infrastructure that makes hard things possible to thrive on the internet; you are not Google.

When reaching for a UDF system as a tool to solve a problem, ask yourself this: “am I modifying my own system’s behaviour, or is someone else modifying my system?”. If the answer is that you want to modify the behaviour of your own system, a database UDF may be a good option. If you want to grant someone else the ability to modify how your software behaves, then a SaaS UDF is the way to go. Permalink

Unlike I think pretty much all other professionals that don’t have it within their power to create their own tools – if you work in sales and you want better sales tools, you have to find a software engineer to do it for you – but we are software engineers and the tools that we use are themselves made out of software. So we have it in our power to fix them.

[I] went to work at Foursquare, I quickly noticed that Foursquare had the exact same problem. They had this big Scala code base and it wasn’t scaling. The solution at the time – and I am not joking – was to give all of the engineers a stick of ram, a screwdriver, and to say just upgrade your laptops.

I work on Earthly, another open-source build tool tackling similar problems. To Benjy, though, the important thing is not the potential for competition, it’s the size of the problem. I think an example of how much work there is to do in this space is the fact that Earthly and Pants are so different in their approaches, and yet both really fill in these needs.

There’s so much open space here to fill with good technology that two systems with radically different architectures and radically different approaches can both be very useful in their own right and also complimentary.

Last year's focus was on adding serverless flavors of their analytical & streaming engines, plus on expanding their data marketplace features. However, AWS's push towards "serverless" was soon criticized as only delivering auto-scaling capabilities rather than truly lifting infrastructural burdens off the customer. If it does not have on-demand pricing nor turn off fully when idle, it is not serverless by most cloud observers' definition (which is also AWS's own definition when they invented serverless functions with Lambda).

Beyond Redshift catching up to Snowflake on the separation of storage and compute, data sharing, and serverless with on-demand pricing, they have also caught up on data marketplace capabilities.