u/Feeling-Maybe-3443

You can use it to run notebooks, build dashboards, and manage workflows without worrying about setup issues or system limitations during your projects.

We’re also providing free credits to help you get started and actually run your workloads.

We’re currently looking for a few users to try it out and share honest feedback on how it fits into your project work. If you’re working on something and would like to explore it, feel free to reach out.

Currently we're at a stage where we want genuine users to try it and share their insights.
Whether you live in Jupyter notebooks, Airflow or use other tools like VS Code or anything else in your data science workflow, I'd love to hear from you. The more variety of use cases, the better. To make it worth your time, we're offering free credits so you can run real workloads on the platform.

If you're regularly doing data work and want to try something new, feel free to reach out here or send me a message

Hey everyone, I’ve been working on a side project to simplify data workflows. I often faced issues managing different tools separately — notebooks, scripts, dashboards, and scheduling along with setup and environment conflicts.

So I built a cloud platform that brings Jupyter, VS Code, Streamlit, and Airflow together in one place.

It’s still early, and I’m mainly looking for honest feedback, what feels useful and what could be improved.

Happy to share access if anyone’s interested in trying it out.

Hey everyone,

I’ve been working with Jupyter notebooks recently and started facing some issues with performance when handling larger datasets. My system slows down quite a bit during heavier tasks.

Just wanted to ask — how do you usually deal with this? Do you upgrade your setup or follow some different approach?

We’ve been working on a cloud platform with Jupyter, VS Code, Streamlit, and Airflow in one place to solve exactly this, and recently opened it up.

Looking for a few genuine users to try it and share honest feedback. We’re also offering some credits so you can test real workloads.

Happy to discuss in comments or DMs.

Hey everyone,

While working on data science projects, one recurring issue we faced was managing environments, setups, and tool conflicts across Jupyter, Airflow, VS Code, etc.

So we built a cloud-based setup where these tools run without local configuration; mainly to make workflows smoother and less time-consuming.

This isn’t open-source, but since many here actively use open tools, I’d really value your perspective on whether something like this actually helps or not.

We’re at a stage where we’re looking for genuine feedback and real use cases. Happy to offer free credits if anyone wants to test it with actual workloads.

Would appreciate any thoughts, even just how you currently manage your workflow.

Since many of you actively use and build with open-source tools, we’d really value your perspective — this isn’t open-source, but it’s designed to fit into those kinds of workflows and hopefully make things smoother.

Currently we’re at a stage where we want genuine users to try it and share their insights. Whether you live in Jupyter notebooks, Airflow or use other tools like VS Code or anything else in your data science workflow — we’d love to hear from you. The more variety of use cases, the better.

To make it worth your time, we’re offering free credits so you can run real workloads on the platform. If you’re regularly doing data work and want to try something new, feel free to reach out here or send me a message — would really appreciate it.