01
Reduce MTTR during production incidents
An AI SRE gathers logs, traces, metrics, Kubernetes events, deployments, and code context automatically, so responders can move from alert to root cause faster.
DemoTry Playground→
AI SRE Agent
for teams on Kubernetes
Metoro's AI SRE agents detect production issues, investigate alerts, verify deployments, identify root causes, and generate pull requests to fix them.
Metoro Overview
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01Install
Run one command.
Install a single daemonset into your Kubernetes cluster. No code changes, no sidecars, no SDKs.
~/cluster · bash
$helm install metoro metoro/agent --namespace metoro --create-namespace --set apiKey=$METORO_KEY
And you're done.
02Detect · No alert rules required
Metoro detects issues automatically.
Metoro watches all your clusters for issues, then investigates using its collected telemetry to find the root cause.
01 · Service-level regressions
- ▸HTTP 5XX spikes
- ▸Latency spikes
- ▸Database error-rate & latency spikes
02 · Dependencies
- ▸External dependency errors
- ▸External dependency latency regressions
- ▸Deployment-related service regressions
03 · Pods & workloads
- ▸CrashLoopBackOff
- ▸ImagePullBackOff / ErrImagePull
- ▸OOMKilled
- ▸Init:Error
04 · Nodes & cluster
- ▸Kubernetes warning event spikes
- ▸Node network anomalies
- ▸CPU, memory, request, limit & throttling issues
03Root causes · Delivered to your team
Wake up to root causes, not alerts.
Metoro turns detected issues into clear, investigation-backed notifications with the root cause, supporting evidence, and suggested fixes.
AI Anomaly Detection
Metoro finds the regression. Down to the line of code.
Metoro autonomously monitors all your services and infrastructure to detect issues. Once an issue is detected, Metoro automatically root causes it and opens a pull request with a fix.
- ✓Anomaly detection over RED and USE metrics, infrastructure utlization and kubernetes events
- ✓Each anomaly detection event is investigated and validated before being sent to your team, cutting out the noise
AI REMEDIATION
Then Metoro generates the fix PR.
Metoro turns root cause analysis into proposed code fixes. When it identifies the offending change, it drafts a pull request with the fix, evidence, telemetry links, and an RCA summary - ready for your team to review and merge.
- ✓Generates fix PRs from root cause analysis
- ✓Includes RCA summary, evidence, and telemetry links
- ✓Keeps engineers in control with review-before-merge workflows
Deployment Verification
Every rollout, verified against production.
Metoro compares each deployment's behavior against the baseline. Regressions surface in Slack with a pre-drafted rollback PR - before a customer notices.
- ✓Per-service, per-endpoint comparison
- ✓Flags regressions in under 60 seconds
- ✓Rollback PR pre-drafted on failed verification
Reduce MTTR with AI Alert Investigation
Every alert, auto-investigated.
Metoro investigates every firing alert, separates noise from real production issues, and sends your team the likely root cause, evidence, and next steps in Slack.
- ✓Investigates alerts from your existing tools
- ✓Filters noisy pages from actionable incidents
- ✓Delivers root cause, evidence, and proposed fix
Why Metoro
Most AI SREs inherit your telemetry gaps. Metoro doesn't.
Metoro brings its own eBPF telemetry layer for Kubernetes and combines runtime signals, Kubernetes state, deployments, and code changes into one reliable investigation context.
Try PlaygroundPain points
What problems does an AI SRE Agent solve?
AI SRE platforms help Kubernetes teams reduce MTTR, lower alert fatigue, catch deployment regressions, and turn incident evidence into remediation steps.
02
Cut alert fatigue for on-call teams
Instead of handing engineers another page with no context, an AI SRE investigates the alert, separates noise from real issues, and summarizes what changed.
03
Catch deployment regressions earlier
AI SRE deployment verification compares new rollouts against live production baselines and flags regressions before customers report them.
04
Close observability gaps
When telemetry is incomplete, investigations stall. Metoro uses eBPF telemetry for Kubernetes so the AI starts with runtime evidence, not only pre-existing dashboards.
05
Reduce repetitive incident toil
The same investigation steps happen during every incident: query telemetry, inspect Kubernetes state, compare changes, and test hypotheses. An AI SRE automates that loop.
06
Turn root cause into action
Finding the likely cause is only part of the workflow. Metoro can generate suggested fixes and pull requests so teams can review a concrete next step.
Customer feedback
What teams are saying.
Metoro has made visibility into our Kubernetes environment effortless with on-demand event analysis and AI-driven root-cause investigations. Nothing is hidden anymore.
Metoro absolutely slaps, so good ❤️
Detection, investigation, and the fix PR - all before I finished reading the page. It's the first AI SRE that's actually earned its name.
Metoro has been a huge boon to our observability ecosystem; saving us time and effort getting the information we care about most out of our clusters. The only thing cooler than the tool has been the people behind it.
It found exactly what I was looking for in the logs. Amazing.
We used to spend an hour digging through dashboards when something broke. Now Metoro figures it out in minutes - our on-call engineers love it.
AI root cause analysis is just amazing. Helps us save a ton of time.
We installed Metoro, and it just worked.
I'm literally able to look up at a Slack notification from Metoro whilst having noodles, tap the link, access the Metoro dashboard, see what customers on Porter Cloud are doing and take a call in real-time. For me, that's the best thing ever.
In the last week, we've detected and blocked 10 malicious agents running on our infrastructure. Without Metoro, they would still likely be running.
Metoro made it incredibly simple for us to not just observe and trace logs, but also to dive into AI-driven investigations effortlessly - turning complex Kubernetes monitoring into a smooth, intuitive experience.
Anyone running user agents on their infrastructure needs a solution like Metoro. It's just a case of when, not if a malicious agent will be running.
FAQ
Frequently asked
Common questions about Metoro's AI SRE for Kubernetes.
What is an AI SRE?
An AI Site Reliability Engineer is an autonomous agent that performs the work of a human SRE: it watches production, detects anomalies, investigates root causes across code and infrastructure, and remediates the issue - often by opening a pull request. Metoro is an AI SRE built specifically for Kubernetes.
How is Metoro different from a traditional APM or AIOps tool?
APMs tell you something is wrong. AIOps correlates alerts. Metoro does the next step: it investigates the anomaly across code, logs, traces, and profiles, produces a root cause with evidence, and opens the pull request that fixes it.
How does Metoro install?
One Helm chart. eBPF at the kernel level means no code changes, no sidecars, and no SDKs. You have full observability - metrics, logs, traces, and profiles - in under five minutes.
Does Metoro replace my on-call rotation?
No. Metoro handles the triage, investigation, and remediation work that typically wakes engineers up. Your on-call is still on-call - they just review PRs instead of grepping logs at 3am.
Where does our telemetry live?
Three deployment options: Metoro Cloud (managed), Metoro BYOC (runs entirely inside your VPC), and Metoro On-Prem (fully air-gapped). Data never leaves boundaries you set.
What does the AI actually do end-to-end?
It detects regressions from live traffic without predefined alerts, correlates telemetry with source code, identifies the root cause, drafts a fix as a pull request, and attaches the evidence. You review and merge.
Is Metoro SOC 2 compliant?
Yes. Metoro is SOC 2 Type II and a CNCF Silver member. Security posture is audited continuously.
What Kubernetes distributions are supported?
Any CNCF-conformant distribution: EKS, GKE, AKS, OpenShift, Rancher, k3s, kind, and self-managed. eBPF requires a reasonably modern Linux kernel (4.18+). ARM and x86 are both supported.
Get Started
Give your on-call team the night off.
Detection to remediation. Automated. One-minute install. No code changes.