Metoro has made visibility into our Kubernetes environment effortless with on-demand event analysis and AI-driven root-cause investigations. Nothing is hidden anymore.
Powered by eBPF·Cluster state, metrics, and events in one timeline
Kubernetes infrastructure monitoring
you can rewind
See nodes, pods, workloads, events, and resource pressure exactly as they looked when an incident started. Metoro gives platform teams a time-aware view of Kubernetes without Prometheus setup or application changes.
Kubernetes resource viewer
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Porter
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Porter
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Porter
Capabilities
Infrastructure telemetry with Kubernetes context built in.
One Helm install gives you node metrics, object state, resource pressure, right-sizing, and issue detection across every connected cluster, without deploying a separate exporter stack.
Nodes & clusters
Know which node is under pressure and why.
Track CPU, memory, disk, and network by node, namespace, workload, and label. Metoro collects the signals operators need at the kernel level and ties them back to Kubernetes objects.
- ✓Node, pod, and container metrics collected without scrape configs
- ✓Automatic detection of node pressure, failures, and degradation
- ✓Multi-cluster inventory with health and resource context in one view
- ✓Filter infrastructure by Kubernetes labels, annotations, or namespace
hosts · live
workload · k8s context
Kubernetes context
Put Kubernetes object state next to infrastructure metrics.
Metoro records pod phases, replica counts, node conditions, deployment status, and Kubernetes events alongside the metrics. Rewind the timeline to see what the API server reported when the problem happened.
- ✓Pod, deployment, node, and event timelines for every cluster
- ✓Historical cluster state, not just the current object snapshot
- ✓Out-of-the-box signals for OOMs, throttling, crash loops, and image pull errors
- ✓Unified Kubernetes context across production, staging, and dev clusters
Right-sizing
Find wasted capacity and starved workloads.
Right-sizing should not require a separate spreadsheet project. Metoro compares requests and limits with real usage, then highlights workloads that are oversized, throttled, or regularly running out of memory.
- ✓Identify over-provisioned and under-utilized workloads automatically
- ✓Catch OOMs, CPU throttling, and disk pressure before users do
- ✓Compare requests and limits against real usage across deploys
- ✓Tune cost and reliability from the same operational view
issues · resource pressure
issues · cluster overview
Issues & events
Turn noisy infrastructure signals into ranked issues.
Metoro continuously evaluates each cluster for the failure modes Kubernetes operators see every day, including OOMs, restarts, image pull failures, and node pressure. Issues are grouped by affected resource so the feed stays actionable.
- ✓Pre-built detectors for common Kubernetes infrastructure failures
- ✓Issues link directly to affected pods, nodes, events, and charts
- ✓Self-configuring detectors reduce threshold tuning work
- ✓Wire issues into Slack, PagerDuty or email with one click
What changes after install
Less setup, more evidence when the cluster is under pressure.
<1m
Install to first cluster telemetry
one Helm chart, no scrape configs
<1%
Typical CPU overhead per node
kernel-level eBPF agent
All
Nodes, pods, and workloads
health, usage, and object state
0
Application code changes
works for first- and third-party workloads
Predictable cost
Scale without surprises.
Cost comparison
Infrastructure monitoring cost comparison
Estimate by cluster size and metric volume
Datadog
$3,050/monthNew Relic
$2,450/monthMetoro
$1,000/month* Approximate cost. Precise costs depend on the specific use case and any discounts.
** Estimates based on public pricing pages. Vendor pricing can change over time.
Customer feedback
What teams are saying.
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 Questions
Answers for platform teams evaluating Metoro for Kubernetes infrastructure monitoring.
What does Metoro monitor for Kubernetes infrastructure?
Metoro monitors node CPU, memory, disk, and network usage, pod and container resource consumption, Kubernetes object state, node conditions, cluster events, and infrastructure issues. You can break the data down by cluster, namespace, workload, label, or annotation.
Can I see historical Kubernetes state?
Yes. Metoro keeps Kubernetes object state tied to the same timeline as metrics and events, so you can inspect how pods, deployments, nodes, and replica counts looked when an incident started instead of only seeing the current API server snapshot.
Do I need Prometheus, exporters, or scrape configs?
No. A single Helm install starts collecting node, pod, container, and Kubernetes telemetry without Prometheus, exporters, or scrape configuration. Metoro also supports PromQL for teams that want to query with familiar syntax.
How does Metoro detect infrastructure issues?
Metoro evaluates Kubernetes failure modes such as OOMs, CPU throttling, pod restarts, image pull failures, and node pressure, then groups them into ranked issues linked to the affected resources and supporting charts.
Can I monitor multiple Kubernetes clusters together?
Yes. Metrics, events, Kubernetes state, and issues from every connected cluster appear in the same product. You can compare environments, filter to a specific cluster, or drill from a fleet view into a single node, namespace, or workload.
What is the runtime overhead?
Metoro's eBPF-based monitoring typically uses less than 1% CPU per node. The agent collects infrastructure signals from the kernel and Kubernetes API without requiring application instrumentation.