vopono VS data_engineering_on_gcp_book

Vopono (https://github.com/jamesmcm/vopono):

"vopono is a tool to run applications through VPN tunnels via temporary network namespaces. This allows you to run only a handful of applications through different VPNs simultaneously, whilst keeping your main connection as normal.

vopono includes built-in killswitches for both Wireguard and OpenVPN."

I think for now on Linux you (still!) have to use external application to do the splitting. Such is vopono

I use vopono to manage it for me with Mullvad though.

you might want to check out vopono, i've gotten it working with firefox and its nice

https://github.com/jamesmcm/vopono

I highly recommend using something like vopono with this on Linux that runs only the target application (e.g. Transmission) in a network namespace in the VPN and only forwards the specified ports and only allows traffic via the VPN.

This is why I use vopono - you can run just the torrent client in the VPN on its own and the killswitch keeps it safe.

You can find the option in the settings of windows and android apps. Unfortunately, it's Still not available for Linux. As a workaround for Linux, you can use vopono, which has OpenVPN support for Proton. Or just manually add routing table entries :)

I wrote vopono, I use it all the time for quickly spinning up browsers through different VPNs for checking geographical restrictions, etc.

This book will walk you through setting up a complete data engineering stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book

As for resources, this book goes over a lot of these: https://github.com/Nunie123/data_engineering_on_gcp_book. However, this goes over the 'how', not the 'why'. The only method I know for understanding the 'why' is experience. Whether at work or personal projects.

Here's a good book to follow along to introduce you to common tooling and design patterns: https://github.com/Nunie123/data_engineering_on_gcp_book

I'm not sure if this is exactly what you're looking for, but here's a book on GitHub that talks about the tools and steps for building data pipelines into a data warehouse: https://github.com/Nunie123/data_engineering_on_gcp_book

Check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you're interested in example of how to build a complete data engineering infrastructure, you should check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want to try Airflow without the setup headache, you can try Composer on GCP, which is a hosted version of Airflow. I wrote some info on how to do that here: https://github.com/Nunie123/data_engineering_on_gcp_book/blob/master/ch_2_orchestration.md

This book might be a good resource for you: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want a place to start on personal projects you can check out this book, https://github.com/Nunie123/data_engineering_on_gcp_book, which will walk you through the basics of setting up a full data engineering stack.

If you are interested in tooling, here's a free book on setting up a basic data engineering tech stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book