Hey Product Hunt 👋 Yuanlin here, founder of Zeabur and now building Nuphos.
Nuphos started from something we learned while building Zeabur.
We used to describe where Zeabur was going as “Your AI DevOps Engineer.”
But eventually we realized:
A PaaS asks you to adapt to its rules. A DevOps engineer adapts to your team’s infrastructure.
They learn the systems you already have, work within your permissions, and follow the way your team operates.
AI DevOps engineers should too.
Nuphos is an AI-native DevOps workspace that brings AI agents into the infrastructure your team already runs, without giving up control.
Our team of fewer than 10 engineers operates across 8+ clouds, 20+ Kubernetes clusters, and more than 10,000 hosts. We’d already been using coding and terminal agents in production, and they were surprisingly capable.
The hard part wasn’t getting an agent to run kubectl or inspect logs. It was everything around the action:
Whose permissions is it using?
What can it change?
Who approved it?
What exactly changed?
That’s what we built Nuphos around.
With Nuphos, you can connect your existing AWS, GCP, Kubernetes, and observability stack, keep agents read-only by default, require approval for write actions, and keep the context and audit trail shared with your team.
You can try it with your own infrastructure, or use the live demo on our homepage without signing up.
🎁 Use code PH100OFF to get your first month of Nuphos free.
👉 Got questions or want to follow what we’re building? Join our Discord: https://nuphos.ai/dc
And I’d love to hear from people running production:
What kind of experience would make an AI feel like a real DevOps engineer on your team, rather than just another AI agent?
This looks really exciting! One thing I’m curious about: how would you see Nuphos fitting into the workflow of a solo developer or a one-person team?
I build and experiment with multiple small products and AI projects, but I don’t necessarily have a large SaaS infrastructure or a dedicated DevOps team.
Would Nuphos still be useful at this stage? If so, what would be a good real-world use case for someone like me to start with?
Or is Nuphos currently more suited to larger teams that already have a fairly complex production infrastructure?
Would love to understand where a solo builder fits into the Nuphos vision.
We’ve been using @Nuphosas their design partner. This is pretty much how I want AI to work with our production infra. Congrats@yuaanlin
the read-only-by-default plus approval-for-writes model makes sense for trust. during an active incident when minutes matter, does that approval step ever become the bottleneck itself, or is there a break-glass path for that moment?
This feels like the right direction for AI in DevOps. Running commands is the easy part — understanding the infrastructure, permissions, past incidents, and how a team actually operates is much harder.
Really like the read-only-by-default + approval approach too. Agents touching prod need context and guardrails, not just more autonomy. Congrats on the launch!
This looks promising. I would be curious to see how Nuphos handles situations where the agent is unsure or finds conflicting signals. Knowing when to pause and ask a human could be just as important as knowing what action to take.
Congrats on the launch!
Really interesting to see agents operating directly against customer infrastructure.
How do you evaluate whether an agent will make the right infrastructure decision across scenarios it hasn’t encountered before, especially failures that would be expensive or risky to reproduce in a real cloud environment?
Love the idea of an AI agent that adapts to the team’s existing infrastructure. Congrats to the Nuphos team!
The point about running kubectl not being the hard part really resonated with me. Agents can already execute commands. The bigger challenge is making sure teams understand what they are doing and feel comfortable giving them access to production. Nuphos seems to be solving the right problem.
I worked on the agent experience in Nuphos. The hard part wasn’t getting an agent to propose a fix—it was designing the interface so operators can see the evidence, review a scoped plan, and hit stop the moment something doesn’t look right. In prod, trust is a UI/interaction problem as much as it is a model problem.
Part of the team here! One thing I really like about the permission admin design is how it makes the whole privilege escalation flow feel much safer. Instead of access changes being handled loosely or buried in chat, there’s a clearer approval path before anyone gets elevated permissions. That became a big part of how we thought about making admin workflows more trustworthy.
Team member here. My favorite part is actually not the AI—it’s finally having logs, cluster state, deployments, and the rest of the incident context in one place. The agent becomes a lot more useful once everyone is looking at the same thing.
I worked on the approval gate feature. There were a lot of internal debates around how much context to show, when to ask for approval, and what happens if someone interrupts halfway through. Would love feedback from people who deal with production systems every day.
This is a strong step toward practical AI-native DevOps. Giving agents real infrastructure context—while keeping humans in control of investigation and production actions—could save engineering teams a huge amount of time. Excited to see where Nuphos goes!
Really interesting approach. How does Nuphos learn the context of a team’s infrastructure over time? For example, can it pick up internal runbooks, past incidents, and team-specific operational conventions?
Been using early builds internally for a while, so today feels pretty special. It still makes mistakes (of course), but having it collect the clues before I jump into an incident has already saved me a lot of tab-hopping.
I’m one of the platform engineers building Nuphos, what concerns me the most is how each infra team adopt our product. I'd love to see the most brutal, realistic way on how every other SREs would use Nuphos. 🙂
Interrupt the agent mid-run, change direction, reject its plan, don't go easy on us. This is exactly how we dogfood and use Nuphos on our infra from day to day. We'd appreciate feedback, apart from just a simple "looks good".
Nuphos team here! 👋
My favorite part is the exact moment when monitoring FIREs, Nuphos agent starts investigating, and the context lands in our Slack channel. The agent gets to work automatically, with prod access under-watched, human approved. Being platform engineer myself, the collaborative workspace is what empowers me the most.
Coming from the marketing side of the team, I’ve been preparing for this launch for a long time. I’ve watched Nuphos take shape through every piece of copy, every image, and every video we created.
The living runbook is probably the feature I’m most excited about. Too much valuable incident knowledge gets buried in Slack, only to be rediscovered at 2 a.m. months later.
So happy to finally see Nuphos live 🎉 Give it a try! We’d genuinely love to hear any feedback, especially what feels wrong or where it breaks.
About Nuphos on Product Hunt
“The AI-Native DevOps Workspace.”
Nuphos launched on Product Hunt on August 13th, 2026 and earned 277 upvotes and 65 comments, earning #3 Product of the Day. Nuphos gives engineering teams a shared environment where AI agents can learn your infrastructure, investigate issues, and operate production systems.
Nuphos was featured in API (98.5k followers), SaaS (43.6k followers) and Developer Tools (517.5k followers) on Product Hunt. Together, these topics include over 143.3k products, making this a competitive space to launch in.
Who hunted Nuphos?
Nuphos was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Nuphos stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Hey Product Hunt 👋 Yuanlin here, founder of Zeabur and now building Nuphos.
Nuphos started from something we learned while building Zeabur.
We used to describe where Zeabur was going as “Your AI DevOps Engineer.”
But eventually we realized:
A PaaS asks you to adapt to its rules. A DevOps engineer adapts to your team’s infrastructure.
They learn the systems you already have, work within your permissions, and follow the way your team operates.
AI DevOps engineers should too.
Nuphos is an AI-native DevOps workspace that brings AI agents into the infrastructure your team already runs, without giving up control.
Our team of fewer than 10 engineers operates across 8+ clouds, 20+ Kubernetes clusters, and more than 10,000 hosts. We’d already been using coding and terminal agents in production, and they were surprisingly capable.
The hard part wasn’t getting an agent to run kubectl or inspect logs. It was everything around the action:
Whose permissions is it using?
What can it change?
Who approved it?
What exactly changed?
That’s what we built Nuphos around.
With Nuphos, you can connect your existing AWS, GCP, Kubernetes, and observability stack, keep agents read-only by default, require approval for write actions, and keep the context and audit trail shared with your team.
You can try it with your own infrastructure, or use the live demo on our homepage without signing up.
🎁 Use code PH100OFF to get your first month of Nuphos free.
👉 Got questions or want to follow what we’re building? Join our Discord: https://nuphos.ai/dc
And I’d love to hear from people running production:
What kind of experience would make an AI feel like a real DevOps engineer on your team, rather than just another AI agent?