AI SRE that detects, root causes & auto-fixes K8s incidents
Metoro is an AI SRE for systems running in Kubernetes. Metoro autonomously monitors your environment, detecting incidents in real time. After it detects an incident it root causes the issue and opens a pull request to fix it. You just get pinged with the fix. Metoro brings its own telemetry with eBPF at the kernel level, that means no code changes or configuration required. Just a single helm install and you're up and running in less than 5 minutes.
Hey PH! We're Chris & @ece_kayan , the founders of Metoro.
We built Metoro because dealing with production issues is still far too manual.
Teams are shipping faster than ever with AI, but when something breaks, engineers still end up jumping between dashboards, logs, traces, infra state, and code changes just to figure out what happened and how to fix it.
We started working on this back in 2023 during YC’s S23 batch, and learned a hard lesson from customers early on: generalized AI SRE doesn't work reliably for two reasons.
Every system is different. The architecture is different. Some teams run on VMs, some on Lambdas, some on managed services, some on Kubernetes, others on mixtures of all of them.
On top of that, telemetry is usually inconsistent. Some services have traces, some don’t. Some have structured logs, some barely log at all. Metrics are named differently everywhere.
This means that teams need to spend weeks or even months generating system docs, adding runbooks, producing documentation and instrumenting services before the AI SRE can be useful. That wasn't workable.
So we took a different approach.
With Metoro, we generate telemetry ourselves at the kernel level using eBPF. That gives us consistent telemetry out of the box with zero code changes required. No waiting around for teams to instrument services. No huge observability blind spots.
And because Metoro is built specifically for Kubernetes, the agent already understands the environment it’s operating in. It doesn’t need to learn a brand new architecture every time.
The result is an AI SRE that works out of the box in under 5 minutes.
We automatically monitor your infrastucture and applications, when we detect an issue we investigate and root cause it. When we have the root cause, we automatically generate a pull request to fix it, whether that's application code or infrastructure configuration. Detect, root cause, fix.
We’re really excited to be launching on Product Hunt today 🚀
We’d love for you to check it out, try it, and ask us anything. Whether that’s about Metoro, Kubernetes observability, or AI in the SRE space.
Hey PH! We're Chris & @ece_kayan , the founders of Metoro.
We built Metoro because dealing with production issues is still far too manual.
Teams are shipping faster than ever with AI, but when something breaks, engineers still end up jumping between dashboards, logs, traces, infra state, and code changes just to figure out what happened and how to fix it.
We started working on this back in 2023 during YC’s S23 batch, and learned a hard lesson from customers early on: generalized AI SRE doesn't work reliably for two reasons.
Every system is different. The architecture is different. Some teams run on VMs, some on Lambdas, some on managed services, some on Kubernetes, others on mixtures of all of them.
On top of that, telemetry is usually inconsistent. Some services have traces, some don’t. Some have structured logs, some barely log at all. Metrics are named differently everywhere.
This means that teams need to spend weeks or even months generating system docs, adding runbooks, producing documentation and instrumenting services before the AI SRE can be useful. That wasn't workable.
So we took a different approach.
With Metoro, we generate telemetry ourselves at the kernel level using eBPF. That gives us consistent telemetry out of the box with zero code changes required. No waiting around for teams to instrument services. No huge observability blind spots.
And because Metoro is built specifically for Kubernetes, the agent already understands the environment it’s operating in. It doesn’t need to learn a brand new architecture every time.
The result is an AI SRE that works out of the box in under 5 minutes.
We automatically monitor your infrastucture and applications, when we detect an issue we investigate and root cause it. When we have the root cause, we automatically generate a pull request to fix it, whether that's application code or infrastructure configuration. Detect, root cause, fix.
We’re really excited to be launching on Product Hunt today 🚀
We’d love for you to check it out, try it, and ask us anything. Whether that’s about Metoro, Kubernetes observability, or AI in the SRE space.