Metoro has made visibility into our Kubernetes environment effortless with on-demand event analysis and AI-driven root-cause investigations. Nothing is hidden anymore.
Dashboards & Metrics·Templates, MetoroQL & Grafana imports
Custom Dashboards
built for Kubernetes.
Pre-built and custom dashboards for every workload. Import any Grafana dashboard in one click and query everything with a single PromQL-compatible language.
dashboards · live
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Capabilities
Dashboards that cover every layer of your cluster.
One Helm install gets you the metrics - and the dashboards on top. Mix eBPF, Prometheus and OpenTelemetry data on the same canvas, with a single PromQL-compatible query language.
Custom dashboards
Drag-and-drop dashboards, ready in minutes.
Build a dashboard with the chart wizard or start from a pre-built Kubernetes template. Group widgets, swap chart types, and share the result with a single URL.
- ✓Pre-made templates for every Kubernetes workload
- ✓Line charts, bar charts, single stats and grouped widgets
- ✓Per-dashboard variables that filter every chart at once
- ✓Share dashboards by URL - no extra setup, no extra cost
dashboards · canvas
dashboards · release workflow
01
Application release
service, manifests, dashboards
same pull request
02
Environment rollout
staging, preview, production
same operational view
03
Metoro dashboard
ready when the workload lands
owned by the service team
ConfigMap-managed dashboards
Dashboards as configmaps.
Keep operational views next to the service manifests they explain. Dashboard updates can move through the same review, release, and rollback process as the workload itself, so every deployment brings the right context with it.
- ✓Bundle service dashboards with application deployments
- ✓Review dashboard changes in the same pull request as code and manifests
- ✓Keep staging, production, and preview environments aligned
- ✓Give service owners a reliable default view from day one
Every signal, every source
One backend for metrics, logs, traces and K8s state.
eBPF baseline metrics, Prometheus scrapes, OpenTelemetry pushes - all flow into the same store and can be charted side-by-side with no extra exporters.
- ✓Container-level network, disk, CPU and memory from eBPF
- ✓Scrape any existing Prometheus endpoint - zero config drift
- ✓Push custom metrics over OTel HTTP from any service
- ✓Visualise logs, traces and K8s objects on the same canvas
metric · sources
eBPF metrics
kernel · always-on
baseline · per-container
Prometheus
scraped · /metrics
auto-discovered
OpenTelemetry
pushed · OTLP/HTTP
custom metrics
Logs
tailed · indexed
full-text + structured
Traces
eBPF + OTel spans
100% · no sampling
K8s resources
pods · deploys · nodes
live · queryable
grafana · http_server
Grafana import
Bring 5,000+ Grafana dashboards over in one click.
Paste a Grafana dashboard JSON or pick from the public library - Metoro translates it to MetoroQL, wires up the same variables, and renders it natively. No proxies, no parallel stacks.
- ✓One-click import from the public 5,000+ dashboard library
- ✓Translates PromQL queries to MetoroQL automatically
- ✓Reuses Grafana variables and templating
- ✓Layout, panels and links carry over so muscle memory works
MetoroQL + variables
PromQL you already know, across every signal.
MetoroQL is PromQL-compatible and works across metrics, logs, traces and Kubernetes resources. Variables make a single dashboard reusable for every service in your cluster.
- ✓PromQL-compatible - copy-paste your existing queries
- ✓Query logs, traces and K8s state with the same syntax
- ✓Dashboard variables with default values + per-user overrides
- ✓Build one generic dashboard, reuse it for every service
metoroql · query editor
$service=currency-service$cluster=prod-eu-west-1$env=production$range=1h
1# request rate, grouped by status class
2sum(rate(http_requests_total{service="$service"}[5m])) by (status_class)
3# same query, but for logs - across the same service
4count_over_time({service="$service", level="error"}[5m])
5# live K8s state on the same canvas
6k8s(kind="Pod", labels.app="$service") | status()
PromQL compatibility100%
Signals on one query languagemetrics · logs · traces · k8s
Variable defaults + overridesper-dashboard, per-user
Why teams pick Metoro for dashboarding
Built for the way Kubernetes actually runs.
5,000+
Grafana dashboards importable
one-click migration to MetoroQL
90×
Custom-metric compression
at-rest, lossless aggregation
4
Signals on the same canvas
metrics · logs · traces · k8s
0
Code changes required
works on third-party services too
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
Everything about Metoro Kubernetes dashboards and metrics.
What types of metrics does Metoro collect?
Two kinds. First, eBPF metrics from the in-cluster agents - detailed container-level network, disk, CPU, memory and node telemetry, captured automatically. Second, Prometheus metrics scraped directly from your services, so anything already exposing /metrics shows up alongside everything else.
Can I send custom metrics to Metoro?
Yes. The Metoro exporter running in each cluster speaks the OpenTelemetry HTTP specification. Send your metrics there and they become first-class - chartable, queryable with MetoroQL, and usable in dashboards and alerts like any built-in metric.
How do I create a custom dashboard?
Open the dashboards view, click Create Dashboard, and use the chart wizard to add widgets. Search for metrics, pick aggregations and filters, and drag widgets onto the canvas. Dashboards get a unique URL you can share with your team.
Can I manage dashboards with my Kubernetes deployments?
Yes. ConfigMap-managed dashboards let application teams ship operational views alongside the workloads they describe, so dashboard changes can be reviewed, versioned, and promoted through environments with the rest of the release. Setup details are in the ConfigMap-managed dashboards docs.
Can I import my Grafana dashboards?
Yes. Paste a Grafana dashboard JSON or pick from the public 5,000+ dashboard library and Metoro renders it natively. PromQL queries are translated to MetoroQL automatically and Grafana variables and templating carry over.
What is MetoroQL?
MetoroQL is a PromQL-compatible query language that works across metrics, logs, traces and Kubernetes resources. Existing PromQL queries work unchanged, and the same syntax extends to log filters, span aggregations and live K8s state.
How do dashboard variables work?
Variables let you parameterise charts at the dashboard level. Set a default - a service name, an environment, a namespace - and let users override it for their session. One generic dashboard becomes a personalised view for every service in your cluster.
What chart types are available?
Line and bar charts for timeseries, single stats for KPIs, and grouped widgets for related panels. Every chart can mix metrics, log counts, trace aggregations and K8s state in the same view.