What do you like best about the product?

Gitpod allows engineers to focus as much of their time as possible on delivering business value. With Gitpod, engineers don't have to worry about installing tools and can start coding right away. Gitpod workspaces boot up in seconds, run in the cloud (right next to your data) and thus also give you the power of cloud machines. Big enterprises typically don't gave very good engineering laptops, which is also solved by using a Cloud IDE such as Gitpod.

As an internal developer platform team, it allows us to onboard new engineers much faster than before. Where in the past people had to go through 20 documentation pages with all the tools that needed to be installed, this can now be provided by the platform team as a script in the .gitpod.yml configuration file.

What do you dislike about the product?

In general you see that the market is still quite young for cloud IDEs and that you can't use all the features of Jetbrain products yet. Next to that, plugins on the marketplace sometimes don't work.

What problems is the product solving and how is that benefiting you?

- Slow enterprise laptops
- Secure connectivty to data systems (data doens't have to be on personal laptops anymore)
- Onboarding people instantly without losing time
- Helping to bridge the disconnect between the "experimentation" and "industrialization" phases of the data product lifecycle. People can now run Jupyter notebooks right next to their code in an IDE. This promotes better writing of functions and prevents copy pasting code after the machine learning model experiments are done. In the past, when people finished developed a machine learning model in a notebook, they had to go to the next step, which is industrializing the code and making sure the predictions are run everyday or in real-time. People often had to copy paste code from a notebook to an IDE.