[jtagliabuetooso]

Thanks a lot for the feedback, point taken!

Wrt deployment: the system has a control plane (on Bauplan AWS, never see any data, just auth and metadata), and data planes for customers (single tenant, private link, Soc2 compliant and all that).

If by hosting you mean "move the data plane to my cloud", that is entirely possible but not as recommended as the managed offering: in the end, the only dependency we have are off-the-shelf VMs in which we install our binary - and your bucket of course, but that is yours.

If you mean "installing the control plane on my cloud", that is not in the cards at the moment, unless a very special deployment is needed.

My suggestion - before complex deployment discussion - is always super simple: try it for free on public datasets and decide if you like it; running the quick start takes three minutes, just send over your email for access.

If you do like it, we can have a discussion on deployment, which has never been a blocker before.

[anentropic]

so like the Lambda funcs in the examples - do I deploy those myself to my own infra? or they have to be defined using Serverless framework and get deployed to Bauplan-controlled infra? are they in the control plane or the data plane?

Just trying to understand how it all fits together

[jtagliabuetooso]

Sorry for the confusing example.

So, the AWS lambda in the data product example is a bit of a red herring, and it's used as the outer process to create branches and launch bauplan pipelines through the Python client (https://github.com/BauplanLabs/data-products-with-bauplan/bl...).

It can be your laptop, an Airflow task, a prefect flow or a step function or a cron job on a VM - it's the "host" process (for the data product we picked lambda because it's the easiest way for people to "run small Python stuff every 5 minutes" - this is a prefect example: https://www.prefect.io/blog/prefect-on-the-lakehouse-write-a...).

When you interact with the Bauplan lakehouse, all the compute happen on bauplan, nothing happens in the lambda: think of launching a Snowflake query from a lambda - the client is in the lambda but all the work is done in the SF cloud. Unlike many (all?) other lakehouses, Bauplan is code-first, so you can program the entire branching and merging patterns with a few lines of code, offloading the runtime to the platform.

The platform itself runs on standard EC2, which contains the dockerized functions needed for execution - typically we manage Ec2 in single tenant, private link, soc2 compliant account we own for simplicity, but nothing prevents the VMs to be somewhere else (given connectivity is ok etc.). It is our philosophy that you should not worry about the infra part of it, so even in case of BYOC we will be in charge of managing that.

Does it help clarify the mental model?

[anentropic]

Totally - got it now, thanks