Most devs I talk to are quietly overpaying AWS or GCP. Not by a little but by a lot.

We've been building Huddle01 Cloud for a while now and honestly, the pricing difference is wild. Same bare-metal performance, global edge infrastructure with sub-100ms latency, no egress fees, no hidden markups.

What's everyone paying for cloud compute right now? Curious if others have found good alternatives.

Hey everyone!

I love the concept of "vibecoding", getting into the flow, using AI to build fast, and focusing purely on the product. But for a lot of developers (especially in emerging markets like Indonesia), that vibe instantly dies when it's time to deploy.

Suddenly, you are dealing with complex server setups, fighting DevOps configurations, or getting blocked because you don't have an international credit card to spin up a basic server.

Deployment shouldn't ruin the vibe. It should be just as seamless as writing the code.

I'm building Clarity Cloud AI, an AI Native analytics platform for technical and non-technical folks alike. As a first time builder, the journey has been challenging yet fun. I'm planning to launch soon!

I just started solo dev last year and have been trying to keep all early prototype projects low budget. I personally build in a serverless way on @AWS and pay only for what I use (<$1 per month). I'm curious what do you all use for low-budget development? Maybe I can find even cheaper build stack from you guys lol :)

I have made a list of platforms where you can create your community and share your knowledge in a closed circle (and in some cases sell memberships).

The list is according to my preferences, so the platforms I use the most are at the top.

I ve been working on some AI projects recently things like scheduled agents, API responders, and multi-agent systems that need to run continuously. One of the biggest headaches I ve run into is deployment.

Most cloud platforms (AWS, GCP, etc.) are built for stateless apps or short-lived functions. But for long-running, stateful agents, the kind that need to persist data, auto-recover from crashes, and expose custom endpoints it gets surprisingly messy. I ve spent so much time setting up VMs, Docker configs, and recovery logic than actually writing agent behavior logic.

Thanks to supabase I was able to get my project up and running in record time. I use oauth, edge functions, storage, database ofcourse, queues:pgmq and pgvector.

Please check out the project at https://github.com/vpuna/vpuna-a...

It's a semantic search platform for structured and unstructured data , with MCP support and more

Curious what you re actually shipping with right now. Which stack are you using day-to-day, and why did you choose it over the alternatives? A bit of context (product type + team size) helps a ton.

If you ve switched stacks recently, what did you move from/to and what pushed the change? Cost, speed, hiring, DX, vendor limits, something else?