# PagerDuty vs Grafana IRM: An Incident Management comparison for 2026
For years the reason to run PagerDuty alongside Grafana was simple: Grafana could draw the dashboard and fire the alert, but it could not reliably wake a human at 3am. So teams watched dashboards in one tool and paged from another. Grafana Cloud IRM closes that gap. It folds on-call scheduling, alert routing, and incident response into the same platform as your metrics, logs, and traces, which flips the question. It is no longer "which pager do I bolt onto Grafana," but "now that Grafana can page me from the same place as my graphs, do I still need a separate PagerDuty at all."
That reframes the whole comparison, because these two are not built on the same premise. **PagerDuty is a focused, best-in-class incident and on-call platform** that holds none of your telemetry and reaches into other tools for the data behind an alert. **Grafana IRM is the incident layer of a full observability platform**, so the alert, the dashboard that explains it, and the page to the responder can live in one product. One is deep and specialized. The other is younger at incident response but sits on top of the data.
This comparison works through architecture, on-call, incident response, AI, the observability difference that defines the whole matchup, pricing, the open-source wrinkle, and security, so you can decide whether you want the specialist pager or the on-call layer that ships inside your monitoring stack.
## Quick comparison at a glance
Read the table with the platform context in mind. PagerDuty is the deeper incident tool; Grafana IRM's advantage is that it is part of an observability platform rather than a standalone product.
| Category | PagerDuty | Grafana IRM |
|---|---|---|
| **Product type** | Standalone incident and on-call platform | Incident layer inside Grafana Cloud observability |
| **Observability** | ✘, consumes alerts only | ✔, part of Loki, Mimir, and Tempo |
| **On-call scheduling** | ✔, most configurable in the category | ✔, schedules, Terraform, iCal, swaps |
| **Escalation depth** | ✔, deepest, unlimited tiers | ✔, multi-step chains |
| **Declare from a dashboard** | ✘ | ✔, from any Grafana visualization |
| **AIOps noise reduction** | Mature ML, add-on from $699/month | Alert grouping, plus AI investigations |
| **AI assistant** | ✔, GA SRE Agent | ✔, Grafana Assistant and Sift investigations |
| **AI reaches your telemetry** | Via external tools | ✔, native to Grafana data |
| **MCP server** | ✔, GA, Professional and above | ✔, open-source Grafana MCP server |
| **Open-source on-call** | ✘ | Archived March 2026, Cloud IRM is the path |
| **Pricing model** | Per user plus add-ons | Per active user plus platform fee |
| **Compliance** | SOC 2, GDPR, FedRAMP authorized, HIPAA-eligible | SOC 2, GDPR, FedRAMP, PCI DSS, NATSEC100 |
## Platform and philosophy
The defining difference is what each product is a part of. PagerDuty is a complete tool that does one job. Grafana IRM is one capability inside a platform that also holds your telemetry.
### PagerDuty: the focused incident front end
PagerDuty's Operations Cloud centers on an event pipeline that ingests alerts from more than 700 integrations, deduplicates and groups them, and routes the result through the deepest escalation logic in the market. It is mature, reliable, and specialized: its entire surface area is getting the right person paged and coordinating the response. It holds no logs, metrics, or traces, so investigation always happens in a separate monitoring product, and its most advanced capabilities are priced as add-ons.
### Grafana IRM: on-call inside the observability platform
Grafana IRM combines what were previously two products, Grafana OnCall and Grafana Incident, into a unified incident-response layer inside Grafana Cloud. Its distinguishing move is that you can declare an incident directly from any Grafana visualization the moment a graph looks wrong, and the responder investigates in the same tool that raised the alert. On-call scheduling, alert routing, escalation chains, timelines, and post-incident reviews all live beside the dashboards, and because Grafana Cloud is a full observability platform with Loki for logs, Mimir for metrics, and Tempo for traces, the data that explains the incident is already there. The trade-off is depth and commitment: IRM's incident and on-call features are newer and less configurable than PagerDuty's, and getting the integrated experience means adopting Grafana Cloud as your observability platform.
| Platform aspect | PagerDuty | Grafana IRM |
|---|---|---|
| **What it is** | Standalone incident tool | Layer in an observability platform |
| **Holds telemetry** | ✘ | ✔, Loki, Mimir, Tempo |
| **Investigate in-product** | ✘, jump to monitoring | ✔, same platform |
| **Incident maturity** | Deep, specialized | Newer, consolidating |
| **Commitment** | Add to any stack | Adopt Grafana Cloud |
[summary]
### One warehouse, one query language
PagerDuty holds none of the data behind an alert, and Grafana holds it, but across separate backends with separate query languages: LogQL for logs, PromQL for metrics, TraceQL for traces. Better Stack keeps logs, metrics, and traces in one warehouse queried with plain SQL, so the on-call engineer pivots from a trace to the logs around it without switching stores or syntax, and there is far less to assemble and operate.
**A single data model with one query language means less stack to run and one place to look during an incident.** [See the unified data view](https://betterstack.com).
[/summary]
## On-call scheduling and escalation
Both cover the on-call fundamentals well. PagerDuty is more configurable at the extreme; Grafana IRM is capable and improving, and it inherited a strong open-source lineage.
### PagerDuty: the most configurable escalation engine
PagerDuty's policies support unlimited tiers, multi-user escalation, time-based delays, automatic reassignment on no-acknowledgement, and iCal imports, scoped per service, team, or globally. Combined with event orchestration, it absorbs enormous alert volume without paging a human for everything. For the most complex follow-the-sun operations, it remains the reference.
### Grafana IRM: schedules, swaps, and a mobile app
Grafana IRM handles schedules with Terraform and iCal import, planned overrides, automated shift-swap requests, a Google Calendar integration, and full timezone and rotation support, with multi-step escalation chains and notifications across the iOS and Android app, Slack, Teams, Telegram, SMS, phone, and email. The mobile app overrides do-not-disturb for critical alerts and lets responders acknowledge, resolve, or escalate from anywhere. It is a solid, engineer-friendly on-call experience that grew out of the well-regarded Grafana OnCall project. PagerDuty still edges it on raw escalation configurability, but for most teams IRM covers the real needs.
| On-call feature | PagerDuty | Grafana IRM |
|---|---|---|
| **Rotations and overrides** | ✔, most configurable | ✔, planned overrides, swaps |
| **Escalation chains** | Unlimited tiers | ✔, multi-step |
| **Schedule as code** | iCal | ✔, Terraform and iCal |
| **Notification channels** | Phone, SMS, Slack, Teams, email | Adds Telegram, Google Calendar |
| **Mobile app** | ✔ | ✔, DND override |
| **Declare from a dashboard** | ✘ | ✔ |
[summary]
### Escalation that starts where the data is
Both tools escalate well, and Grafana's advantage is that its escalation sits beside its telemetry. Better Stack takes the same shape and keeps it simple: on-call schedules and escalation policies live in the same product as the logs, metrics, and traces, with one setup rather than a stack of components to wire together, and no separate observability adoption decision to make first.
**On-call is most useful attached to the data that fired the alert, without a platform migration to get there.** [See on-call in Better Stack](https://betterstack.com).
[/summary]
## Incident response
PagerDuty coordinates the response as its core job. Grafana IRM coordinates it as part of the observability workflow, with the notable ability to start from the graph.
Grafana IRM centralizes incident data in one authoritative view, tracks a full timeline of actions and decisions, and automatically converts that timeline into a structured post-incident review, integrating with Jira, ServiceNow, and GitHub for the ITSM side. Its signature is launching an incident directly from a Grafana visualization the moment you spot an anomaly, so detection and declaration happen in one place.
PagerDuty automates coordination through incident workflows from the Business tier, opening tickets, notifying stakeholders, posting to Slack, and assigning roles, with conditional branching on the Digital Operations tier. It is the more mature and more automated incident engine of the two, refined over years, but its coordination happens without the telemetry in the same window. The split is familiar by now: PagerDuty does incident response deeper, Grafana IRM does it closer to the data.
| Incident response | PagerDuty | Grafana IRM |
|---|---|---|
| **Timeline capture** | ✔ | ✔ |
| **Auto post-incident review** | ✔ | ✔, from timeline |
| **Declare from visualization** | ✘ | ✔ |
| **Workflow automation** | ✔, mature, conditional | Growing |
| **ITSM integration** | ✔ | ✔, Jira, ServiceNow, GitHub |
| **Data in the same view** | ✘ | ✔ |
## AI and MCP
Both have shipped real AI, and here Grafana has an unusual advantage for a PagerDuty alternative: its AI can reason over its own telemetry, because it holds the telemetry.
### Grafana IRM: Assistant, Sift, and AI investigations
Grafana's AI spans the platform. Grafana Assistant powers agentic workflows, prebuilt dashboards, intelligent filters, and customized alerts, and Sift, its AI investigation engine, automatically runs checks against your metrics, logs, and traces during an incident to surface likely causes. Because these run over Grafana's own observability data, the AI investigates the actual telemetry rather than a summary handed across an integration. Grafana also maintains an open-source MCP server that exposes dashboards, queries, and IRM data to assistants like Claude and Cursor.
### PagerDuty: mature AIOps and the SRE Agent
PagerDuty's AIOps engine brings mature ML grouping, outlier detection, and probable-origin tracing in an add-on from $699 per month metered per accepted event, and its GA SRE Agent recommends and executes diagnostics, with a virtual-responder mode in early access as of the August 2026 drop. Its MCP server is GA to Professional customers and above. The capability is strong, and at extreme event volume its ML is formidable, but its AI reaches into monitoring data it does not own, where Grafana's works on data it holds. Both ship MCP servers; the difference is what sits behind them.
| AI and MCP | PagerDuty | Grafana IRM |
|---|---|---|
| **ML noise reduction** | ✔, AIOps add-on | ✔, alert grouping |
| **AI investigations** | SRE Agent, external data | ✔, Sift, over own telemetry |
| **AI assistant** | ✔, SRE Agent | ✔, Grafana Assistant |
| **AI reasons over your data** | Via integrations | ✔, native |
| **MCP server** | ✔, GA | ✔, open-source |
## The observability difference
Every other comparison in this category ends with the same caveat, that the incident tool leaves the telemetry to a separate product. This one is different, and it is the crux of the whole decision. PagerDuty holds no observability data and never has. Grafana IRM is part of a platform that is a recognized leader in observability, with logs, metrics, traces, profiling, synthetic monitoring, real user monitoring, and Kubernetes and application observability all in Grafana Cloud.
That single fact is Grafana IRM's biggest advantage over PagerDuty. With PagerDuty you are paying for the response layer and buying observability elsewhere. With Grafana IRM the response layer and the observability are the same platform, so the alert, the dashboard, the query, and the page are one product. The cost of that advantage is commitment: you get it by standardizing on Grafana Cloud, and if you already run a different observability stack, IRM's appeal narrows to its on-call and incident features on their own, where PagerDuty is deeper.
| Observability | PagerDuty | Grafana IRM |
|---|---|---|
| **Logs, metrics, traces** | ✘ | ✔, Loki, Mimir, Tempo |
| **Profiling and RUM** | ✘ | ✔ |
| **Synthetic monitoring** | ✘ | ✔ |
| **Same platform as incidents** | ✘ | ✔ |
| **Requires adopting the platform** | No | Yes, Grafana Cloud |
[summary]
### The incident and the data, without the assembly
Grafana proves the point that incident response belongs with the telemetry, and getting there means running Loki, Mimir, Tempo, alerting, and IRM as assembled components. PagerDuty skips the data entirely. Better Stack lands in between by design: incident management, on-call, status pages, and full observability in one product with one data model, so you get the unified experience without operating a multi-service stack to assemble it.
**The same platform for the page and the data, delivered as one product rather than a set of parts to run.** [See the unified platform](https://betterstack.com).
[/summary]
## Pricing
The pricing models reflect the products. PagerDuty is per user with add-ons. Grafana IRM bills per active user and only when engineers actually use it, which is a real structural difference.
### Grafana IRM: pay for active users
Grafana IRM's free tier covers up to 3 active IRM users a month with access to everything. The Pro plan is $20 per active IRM user per month plus a $19 monthly platform fee, with automatic volume discounts, and the key phrase is active user: your bill only grows when an engineer actually uses IRM in a given month, so a large roster of occasional responders does not cost the same as a full team on rotation. Enterprise is custom with a $25,000 annual minimum and deployment flexibility across public cloud, federal cloud, and bring-your-own-cloud. Because IRM is part of Grafana Cloud, the observability data it sits beside is billed by usage separately.
### PagerDuty: per user, plus add-ons
PagerDuty's tiers, on annual billing, are Free for up to 5 users, Professional at $21 per user per month, Business at $41 per user per month, and a custom Digital Operations tier, with AIOps from $699 per month, PagerDuty Advance around $415 per month, and status pages from $89 per 1,000 subscribers as add-ons. Every licensed seat is billed whether or not that person is paged in a given month, which is the opposite of Grafana's active-user model.
### Cost comparison
For a team with many occasional responders, Grafana IRM's active-user billing is usually cheaper, and its included AI and observability adjacency reduce what you buy separately. PagerDuty costs more once add-ons load, but it buys the deeper incident engine and does not require adopting a particular observability platform. The honest comparison depends on whether you are also buying observability: if you want Grafana Cloud anyway, IRM is close to free-riding on that decision; if you are not, you are weighing IRM's on-call against PagerDuty's on its own merits.
| Pricing aspect | PagerDuty | Grafana IRM |
|---|---|---|
| **Free tier** | Up to 5 users | Up to 3 active users, full features |
| **Entry paid price** | $21 per user per month | $20 per active user plus $19 platform fee |
| **Billing model** | Every seat | Active users only |
| **AI and noise reduction** | Add-ons | Included, plus platform AI |
| **Enterprise** | Custom | Custom, $25,000 per year minimum |
## The open-source wrinkle
One factor belongs in any Grafana IRM decision because it recently changed. Grafana OnCall, the popular open-source, self-hostable on-call project, entered maintenance mode in March 2025 and was archived on March 24, 2026. The grafana/oncall repository is now read-only, and the Cloud Connection features that OSS users relied on for mobile push, SMS, and phone notifications were switched off on that date. Active development moved entirely to Grafana Cloud IRM.
The practical meaning is clear. If part of Grafana's appeal to you was a free, self-hosted, open-source pager, that path has closed, and Grafana provides migration tooling to move OnCall OSS configurations into Cloud IRM. Grafana IRM is a Grafana Cloud product, with self-managed deployment available only at the Enterprise tier through bring-your-own-cloud. For teams committed to fully self-hosted, open-source on-call, this is a real consideration, and it is one reason some OnCall OSS users are evaluating alternatives rather than migrating to Cloud.
## Security and compliance
Both are enterprise-grade with strong credentials. PagerDuty carries SOC 2, GDPR, a FedRAMP-authorized offering, and HIPAA eligibility. Grafana Cloud carries SOC 2 Type II, GDPR, FedRAMP, PCI DSS, and NATSEC100 certifications, with federal and bring-your-own-cloud deployment options at the Enterprise tier. Both cover the common enterprise procurement requirements; Grafana's public-sector and PCI footprint is notably broad, while PagerDuty's HIPAA eligibility is the clearer fit for healthcare-specific mandates. Confirm current scope for your specific regulatory needs directly with each vendor.
| Security and compliance | PagerDuty | Grafana IRM |
|---|---|---|
| **SOC 2 Type II** | ✔ | ✔ |
| **GDPR** | ✔ | ✔ |
| **FedRAMP** | ✔, authorized | ✔ |
| **PCI DSS** | Via platform | ✔ |
| **HIPAA** | ✔, HIPAA-eligible | Confirm scope |
| **Self-managed option** | ✘ | Enterprise BYOC |
## Where each platform fits
Reach for PagerDuty when incident response is the priority and you want the deepest, most mature tool for it, independent of your observability choice. If you need the most configurable escalation, the strongest AIOps at high event volume, and a pager you can add to any stack without changing your monitoring, PagerDuty is the specialist, provided you can absorb the add-on pricing.
Reach for Grafana IRM when you are on Grafana Cloud, or want to be. If your dashboards, metrics, logs, and traces already live in Grafana, then having on-call, alert routing, and incident response in the same platform, with AI that reasons over your own telemetry and active-user pricing, is a strong and cost-effective fit. If you are not on Grafana and do not plan to be, IRM's advantage shrinks to its on-call features alone, where PagerDuty is deeper.
The deciding factor is really the observability question underneath. PagerDuty assumes your monitoring lives elsewhere and does its one job well. Grafana IRM assumes your monitoring lives in Grafana and makes incident response an extension of it.
## Final thoughts
This is one of the few comparisons in the category where **observability is already part of one side of the equation**. PagerDuty remains the stronger standalone incident response platform, with deeper escalation, automation, and AIOps capabilities, and it can slot into almost any existing stack. Grafana IRM takes a different approach. **It brings incident response directly into an observability platform**, so the alert, dashboard, telemetry, and investigation can stay much closer together.
That integration comes with a trade-off. To get the most from Grafana IRM, you are effectively buying further into Grafana Cloud and relying on an incident management layer that is still younger than PagerDuty. The decision therefore comes down to **whether you want a dedicated incident platform or an incident workflow built into the observability platform you already use**.
The more interesting part of Grafana IRM is what its existence says about the direction of the market. **Incident response is moving closer to the telemetry needed to resolve the incident**, rather than remaining a separate layer that simply receives alerts from somewhere else. Better Stack follows the same model.
So the broader choice is not just PagerDuty versus Grafana IRM. It is whether you want **observability and incident response assembled from separate tools, integrated through a common platform, or delivered together as one product from the start**.
[summary]
### One assistant, the whole stack
PagerDuty and Grafana both offer MCP servers, but PagerDuty's reaches only its incident data and Grafana's spans an assembled stack of components. Better Stack's MCP server sits over one unified platform, so Claude or Cursor can query your logs with SQL, check who is on call, acknowledge an incident, and build a dashboard chart in one conversation, because the observability and the incident workflow are the same product.
**One MCP endpoint over one platform lets the assistant read the evidence and run the response from the same place.** [Try Better Stack](https://betterstack.com).
[/summary]