Grafana visualizes it. Paxis heals it.
If you’re comparing Paxis vs Grafana, the gap isn’t which dashboard renders prettier panels — it’s what happens after the alert surface. Grafana visualizes Prom/Loki/Influx signals and pages on-call; Paxis ingests the same signals, picks a pre-approved playbook, runs it, and posts the outcome. Same telemetry, closed loop instead of an open page.
The gap Grafana leaves
A great dashboard doesn’t run the fix.
Grafana is the de facto standard for time-series visualization — PromQL/Loki panels, alerting, and a deep datasource ecosystem are exactly what you want for visibility. But Grafana’s loop ends at the panel and the alert: there is no playbook execution layer, no rollback trigger, no Kubernetes drain command waiting on the other side of the threshold. Paxis sits there. When a Grafana alert fires, Paxis receives the signal, diagnoses it against your service topology, runs the approved action, and closes the loop without waking on-call.
Side by side
Paxis vs Grafana, on the dimensions that matter
| Dimension | Grafana | Paxis |
|---|---|---|
| Coverage | Visualization and alerting — render Prom/Loki/Influx panels and surface thresholds. | Visualization + auto-remediation — ingest your Grafana signals and act on them with pre-approved playbooks. |
| Anomaly detection | Threshold rules, PromQL expressions and basic ML — fires when a metric crosses a line someone drew. | Playbook-driven detection — the same signal triggers pattern match against your service topology and selects the right remediation. |
| Auto-remediation | None — Grafana renders the panel and fires the alert; the fix is entirely manual. | Closed-loop — rollback, pod restart, horizontal scale, drain — runs and reports the outcome automatically. |
| Alert fatigue | High panel volume — many thresholds, many channels, many false positives. | Fatigue elimination — only actionable incidents surface, because the system already acted on the noisy ones. |
| Alerting model | Channel routing — alert → PagerDuty, Slack, email, webhook. | Closed-loop with approval pause — page only when a playbook can’t resolve, or when an action needs human sign-off. |
| Getting started | Configure a datasource, dashboard, alert rule and contact point before an alert can reach your team. | Connect Paxis to existing Grafana signals, then select a curated playbook for the response. |
| Pricing model | Per-active-series or panel-count; cost grows with cardinality and panel density. | Per-workspace tiers with hard pod caps — predictable bill, independent of series count or panel count. |
| Integrations | Prom/Loki/Influx/Tempo ecosystem — read the metric, render the panel. | Reads the same signals and acts on them — no rip-and-replace, runs alongside your existing Grafana stack. |
| MTTR | Detection fast via panels; resolution waits on the on-call engineer reading the alert. | Page-to-resolved in seconds — playbook runs and posts the outcome before a human reads the page. |
| On-call | Still pages — Grafana paints a great picture, then hands it to a human. | Pages only when the playbook can’t resolve — everything else returns the loop to idle automatically. |
Grafana is the leading open-source dashboarding platform. Paxis isn't a swap — it's the remediation layer that runs alongside the visualization you already trust, including Grafana itself. PromQL/Loki alert signals in, closed-loop playbook executions out.
Wire Paxis into your Grafana data today.
Pick a plan and start today — Starter ($49/mo) or Team ($199/mo) ships the full self-healing loop end-to-end. Point it at your existing Grafana alert source and watch the first playbook run before your first billing period ends.
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