Run LLM Agents as Microservices with One-Click Deployment
agentainer.ioI guess you get a pass because it's not formally a Show HN but I detest launches that are "join our mailing list" because (a) seems like fishing for interest in vaporware (b) a spam risk when you sell my details if the product doesn't materialize
> Made with for developers
If that were true, you wouldn't have a template website that used the GitHub icon to point to just github.com instead of your repo or org. The whole site just seems autogenerated. I'm aware that's the popular accusation of late, but I don't mean it in the AI wrote it way, I mean the $(npx create-generic-business-site) way
Thank you for your feedback — I can see where the concerns are coming from. We did use Claude Code to help build the landing page, which I believe is why it has that “template-ish” feel. We’ve been mostly heads-down on the backend and infrastructure, and yeah… design isn’t really our strength yet.
The GitHub (and other) icons linking to github.com was just a miss — they were on our checklist, but we somehow let them slip through. We’ll get that fixed right away.
I know a lot of startups fall into the vaporware category, but I’m confident that’s not the case here. We’re building this to solve our own problems, and we’re committed to shipping it. We really appreciate the skepticism — it's the kind of feedback we might have missed if you hadn’t pointed it out.
If you're confident, then link to the documentation for how I could get started with your non-vaporware product
The "waiting list" should gate load upon your platform, it should not gate confidence in it
For sure! We’re planning to release a demo version later this week once we clean up the codebase (it’s a bit messy since we hadn’t originally planned to open it up publicly). This is our first time putting something like this out, so definitely a learning opportunity. I’ll follow up with a repo link once it’s ready — appreciate the push and feedback!
You said demo, and I said documentation. I don't need to run it, I need to understand how I would run it, and more importantly it's an opportunity for you to drive down the skepticism in your target audience since they, too, can see that you have something real
This will be the last time I reply to this thread, since you are clearly in a vastly different place in your journey, but I thought I'd take one more parting shot at getting you to treat your potential customers seriously
I apologize for misunderstood, English isn't my first language but I totally get what you mean now. We have updated our web page with Github repo to a demo version and documentation page is available now as well. Although we don't know what would be valuable to put in documentation page but if there is something you are interesting to learn, please let me know! Thanks again for your time
We are working on Agentainer, a platform to make deploying and managing LLM-based agents as microservices feel effortless — especially for developers who don’t want to wrestle with infrastructure. This isn’t a pitch. we're sharing a pain we’ve run into hard, and we want to know if others are feeling it too. We’ve built agents using AutoGen, LangChain, and custom setups to monitor APIs, automate tasks, or manage systems autonomously. But running these in production? It’s a mess.
Most cloud platforms are designed for stateless apps or short-lived functions — not long-running agents that need to:
- Stay alive for hours or days
- Recover from crashes without losing context
- Expose secure APIs for integrations
- Scale up when demand spikes
- Persist state across redeploys
Dealing with Dockerfiles, Kubernetes, and manually wiring Redis/PostgreSQL eats up too much time — time we'd rather spend improving the agent’s logic.
Agentainer is our attempt to fix this. It’s a platform that gives agents the runtime treatment they deserve. Highlights:
- One-click deployment: Upload your code or Docker image, no YAML or infra scripts. (oh, and we designed it in a way where other AI agent can do it as well!)
- Lifecycle management: Start, stop, pause, resume, and auto-recover — via UI or API.
- Persistent state: Redis (runtime), Postgres (config), with automatic rehydration.
- Per-agent secure APIs: Each agent gets its own REST/gRPC endpoint with token auth and usage logging.
- Scaling and cloning: Horizontal scaling with optional memory cloning.
- Logs and metrics: Real-time logs, crash history, uptime, Prometheus-backed metrics.
What makes Agentainer uniquely flexible is that we expose the entire platform through APIs. This means not just you, the developer, but also your own developer agent can programmatically deploy, monitor, or retire other agents. Want a planning agent that spins up task-specific agents on demand? That’s a first-class use case. We’re building toward a world where autonomous agents can coordinate and manage infrastructure without human input — and Agentainer is designed with that architecture in mind.
We are applying to YC and would love unfiltered feedback from anyone who’s run agents in production:
1. What’s the hardest part of deploying or scaling agents for you?
2. What infrastructure or tooling would actually make your life easier?
3. What debugging/monitoring features would save your sanity?
Honest takes are super welcome. If this idea feels useful — or totally off-base — we’d love to hear why.
Note: Agentainer doesn’t provide any LLM models or reasoning frameworks. We’re infra-only — you bring your own agent code, and we handle the deployment, state, scaling, and API exposure.
> We’re building toward a world where autonomous agents can coordinate and manage infrastructure without human input — and Agentainer is designed with that architecture in mind.
While it can manage infrastructure, how would it know what to manage toward? And would it know how to adapt when the business or other context changes?
That’s a great point — and you’re absolutely right.
Agentainer isn’t responsible for determining what to manage or why — it's not an orchestration brain or planner itself. It’s designed to enable that level of automation by giving agents the tools to act. Think of it more like the runtime and control plane that an intelligent planning agent (built by the developer) can use to execute its decisions.
So for example, if you’ve built a supervisor agent that analyzes workloads and spins up child agents to handle different tasks — Agentainer provides the infrastructure APIs to make that possible (create, monitor, terminate, etc.), but it’s up to you (or your planner agent) to define the logic based on business rules, goals, and evolving context.
We’re not building AGI — we’re just trying to remove the DevOps wall for people building toward that vision.
This is a cool idea that is not ready to share yet. Please consider writing your own comments on HN in the future.
Totally fair, appreciate the honesty. we’re still building and not quite ready yet, but wanted to start getting feedback early so we can build something people actually need while we fix our own pain point.
Also, yes — I did use AI to help clean up my comment because English isn’t my first language, and I didn’t want it to come across sloppy. I get how it might’ve made it sound kinda off. thanks for pointing it out.
If you are looking for feedback:
The website invites users to sign up to get notified of the pre-beta release. Some people might refer to this as an "alpha release".
Your social buttons don't go anywhere. It really seems like you just asked Claude Code to build a website and then posted it to HN and then had a robot respond to all the comments.
Now I feel like I just spent 5 minutes looking at someone's AI slop. It feels fake.
I prefer bad English from a real person over "That’s a great point — and you’re absolutely right."
You are not wrong, the website was actually built with help of Claude Code (like I mentioned in other reply) and we missed to update the social link of it. We will be releasing our demo version repo later this week once we get our codebase cleaned up and then we will post it here again so we can get actual feedback on the product itself. I appreciate you don't roast on my English tho lol
Your English is great! I'll keep an eye out for your demo version. It's a cool idea.
Great news! We have released our demo version in the Github with updated home page. Please feel free to give us some feedback after you try!