Both of these tools will now try to tell you why something broke. Rootly's AI SRE opens its own investigation when an incident starts and posts a likely root cause, with a confidence score, in the Slack channel. Grafana's Sift runs checks across your metrics, logs, and traces and flags error spikes, noisy neighbors, and recent changes, while Grafana Assistant can write queries and dig further on request.
The difference is where each one looks. Rootly's AI works from what integrations send it: alerts, deploys, related incidents, and whatever your monitoring tools expose. Grafana's AI reads the raw telemetry directly, because Grafana stores it. That is the clearest way to frame this comparison: one vendor owns the response process, and the other owns the data.
Everything else follows from that split. Rootly treats an incident as a team exercise run in chat, and it coordinates incidents through channels, roles, and configurable workflows, sells on-call and its AI SRE as separate products, and is independent. Grafana built its incident tooling into an observability stack. Grafana IRM is the on-call and incident layer of Grafana Cloud, where what used to be two products, OnCall and Incident, now sit beside Mimir, Loki, and Tempo, and billed by active user.
This comparison covers the AI question, declaring and running incidents, on-call, status pages and retrospectives, the telemetry itself, and costs for a 25-person team.
Start with the comparisons most teams make on day one. Several favor Grafana on data and Rootly on process.
| Category | Rootly | Grafana IRM |
|---|---|---|
| What it is | Standalone response platform | Incident and on-call layer of Grafana Cloud |
| Ownership | Independent | Grafana Labs |
| Holds your telemetry | ✘ | ✔, metrics, logs, traces, and more |
| AI root-cause work | ✔, AI SRE, priced by quote | ✔, Sift |
| AI reads raw telemetry | ✘, works through integrations | ✔ |
| AI assistant | ✔, Essentials | ✔, Grafana Assistant |
| Where incidents run | Slack or Teams channel | Grafana UI, with Slack and Teams |
| Declare from a dashboard panel | ✘ | ✔ |
| Lifecycle workflows | ✔ | Lighter automation |
| On-call | Separate license, $20 per user | Included in active-user price |
| Shadow rotations | ✔ | ✘ |
| Status pages | ✔ | ✘ |
| MCP server | ✔, GA since March 2026 | ✔, open-source Grafana MCP server |
| Free plan | ✘, trial only | Up to 3 active users |
| Paid pricing | $20 per user per product | $20 per active user plus $19 platform fee |
| Compliance highlights | Enterprise controls | SOC 2 Type II, GDPR, FedRAMP, PCI DSS |
Since both vendors lead with AI, start with how each one reasons.
Rootly's AI SRE, a separately licensed product, starts investigating as soon as an incident opens. It considers what changed recently, which other alerts fired, and how similar past incidents were resolved, then posts its best explanation in the channel with a confidence score and the reasoning behind it, so responders can accept or challenge it.
Its strength is context about the incident: who changed what, and what happened last time. Its limit is that it sees telemetry only as far as your monitoring integrations let it. On Essentials, without the AI SRE, Rootly's assistant still summarizes the incident and drafts the retrospective.
Sift runs a set of automated checks against the data in Grafana Cloud when an incident is declared, looking for error patterns in logs, latency changes in traces, resource contention, and recent deployments. Grafana Assistant goes further on request, writing PromQL, LogQL, or TraceQL, building dashboards, and carrying out multi-step investigation tasks.
Its strength is direct access to the signals. Its limit is that it works best when everything lives in Grafana Cloud, and it brings less organizational context, such as ownership and response history, than a process-focused tool.
Both vendors offer MCP servers. Rootly's, generally available since March 2026, gives assistants such as Claude read and write access to incidents, alerts, schedules, and workflows. Grafana's MCP server, which is open source, opens up its dashboards, data sources, alert rules, incidents, and Sift findings to the same kinds of assistants.
| AI and MCP | Rootly | Grafana IRM |
|---|---|---|
| Root-cause investigation | ✔, AI SRE | ✔, Sift |
| Primary evidence | Changes, alerts, past incidents | Metrics, logs, traces, deployments |
| Writes queries for you | ✘ | ✔, Grafana Assistant |
| Confidence scores | ✔ | ✘ |
| Incident summaries | ✔ | ✔, Grafana Assistant |
| MCP server | ✔, incidents and configuration | ✔, telemetry and IRM |
| AI pricing | AI SRE priced by quote | Sift included, Assistant may add cost |
Rootly's AI has incident context but reaches telemetry through integrations, and Grafana's AI reads telemetry spread across several backends. Better Stack's AI SRE queries one warehouse holding your logs, metrics, and traces, with the on-call schedules and incident history in the same platform.
The best root-cause answers come from an AI that sees both the evidence and the incident. See Better Stack AI SRE.
Rootly organizes people. Grafana organizes around the graph.
Once someone declares an incident, Rootly opens a dedicated Slack or Teams channel, assigns the incident roles, starts recording a timeline, and prompts whoever is leading. Workflows then react to changes in severity, roles, and status, paging more people, opening tickets, posting updates, and keeping the status page current. The service catalog pulls in the owning team, and teams can shape the process in great detail, at the cost of someone maintaining it.
In Grafana IRM, an engineer looking at a spike on a dashboard can declare an incident from that panel, and the visualization comes along. The incident view keeps a timeline of actions that becomes the post-incident review, and investigation happens in the same product, with Loki logs and Tempo traces a click away. Integrations with chat, ticketing, and GitHub handle the conversation and paperwork around it.
The price of that convenience is less process: Grafana gives the incident lead fewer automated steps and fewer prompts than a chat-first tool does. incident.io makes the same bet as Rootly, and our incident.io vs Grafana IRM comparison shows how that trade-off plays out in practice.
| Running the incident | Rootly | Grafana IRM |
|---|---|---|
| Starting point | Slash command or alert in chat | Dashboard panel or alert |
| Incident channel | ✔, automatic | ✔, via Slack integration |
| Role assignment and prompts | ✔ | Roles, lighter guidance |
| Lifecycle workflows | ✔, detailed | Lighter |
| Service ownership | ✔, catalog | Grafana teams and service context |
| Evidence in the same tool | ✘ | ✔ |
Grafana lets you declare an incident from a panel, and Rootly organizes the people who respond to it, but building the right chart in Grafana usually means writing PromQL or LogQL. Better Stack lets responders drag fields onto a chart to see errors, latency, and traffic together, from the same platform that runs the incident.
During an outage, the chart you need should take seconds to build, not a query language. Build a Better Stack dashboard.
Grafana's on-call has more history. Rootly's has more features for the people on the rotation.
Grafana IRM inherits OnCall's scheduling: rotations, planned overrides, automatic shift-swap requests, Google Calendar sync, and schedules defined in Terraform or imported from iCal. Escalation chains can reach people through Grafana's mobile apps, chat tools including Telegram, SMS, voice calls, and email, and critical pages can ring through silent mode. You pay for on-call only through IRM's active-user count, which includes a person in any month they sit on a schedule or escalation chain or act on an incident. Teams that would rather keep a dedicated pager in front of Grafana usually compare it with PagerDuty, which our PagerDuty vs Grafana IRM comparison does.
Rootly prices its pager separately, at $20 per user. Besides schedules, escalation policies, and overrides, it supports shadow rotations for engineers learning the rotation, warns about gaps in coverage, and routes incoming phone calls to whoever is on duty.
| On-call | Rootly | Grafana IRM |
|---|---|---|
| Rotations and overrides | ✔ | ✔, plus automatic shift swaps |
| Schedules as code | API | ✔, Terraform and iCal |
| Shadow rotations | ✔ | ✘ |
| Coverage gap detection | ✔ | ✘ |
| Live call routing | ✔ | ✘ |
| Notification channels | Push, SMS, voice, Slack, Teams | Adds Telegram and Google Calendar |
| Pricing | Separate license | Included in active-user price |
Grafana IRM pages from Grafana Alerting rules you write and maintain, and Rootly On-Call pages from whatever other tools send. Better Stack runs uptime checks, heartbeats, and log-based alerts itself, confirms failures from multiple regions, and pages through on-call schedules with unlimited phone calls and SMS at $29 per responder.
Every alert rule you do not have to write is one less false page at 3am. See Better Stack uptime monitoring.
Rootly includes status pages on Essentials, controlled by workflows so customers hear about a severity change without anyone typing an update. Grafana IRM has no customer-facing status pages, so Grafana teams typically buy one elsewhere.
Both turn the incident timeline into a retrospective. Grafana IRM assembles the review from its own record of the incident, and Grafana Assistant can polish the write-up. Rootly's AI drafts the retrospective from the channel history and sends follow-up actions to your tracker.
| Status and review | Rootly | Grafana IRM |
|---|---|---|
| Customer status pages | ✔ | ✘ |
| Retrospectives | ✔, AI-drafted | ✔, generated from the timeline |
| Follow-up tracking | ✔, synced to trackers | Via integrations |
| Graphs in the review | Linked | ✔, native |
Here Grafana wins outright, as it does against every standalone response tool.
Behind IRM sits a full observability platform: Mimir for metrics, Loki for logs, Tempo for traces, plus continuous profiling, synthetic and real-user monitoring, and Kubernetes views. Gartner rated Grafana Labs a Leader for observability platforms in 2026. Picking IRM keeps incidents and telemetry in one product, which is why Sift can read the raw data.
Rootly stores none of it. Choosing Rootly means paying for observability elsewhere, possibly Grafana itself, and switching tabs during most investigations.
What you trade for that is complexity. Every signal has a separate backend, query language, and pricing dimension, so teams often run Grafana with several syntaxes and several meters. If that complexity is why you are looking around, our list of Grafana alternatives covers platforms that take a different approach.
| Observability | Rootly | Grafana IRM |
|---|---|---|
| Metrics | ✘ | ✔, Mimir |
| Logs | ✘ | ✔, Loki |
| Traces | ✘ | ✔, Tempo |
| Profiling, RUM, synthetics | ✘ | ✔ |
| Query languages | Not applicable | PromQL, LogQL, TraceQL |
Grafana splits OpenTelemetry data across Mimir, Loki, and Tempo, each with its own query language, and Rootly stores none of it. Better Stack accepts OpenTelemetry natively into one warehouse you query with SQL, with on-call, incidents, and status pages built on top of it.
One store and one query language make the data easier to use when it matters most. Explore Better Stack.
Rootly lists both of its Essentials products at $20 a user, quotes the AI SRE separately, and has no free tier. Grafana IRM costs nothing for 3 or fewer active users and $20 per active user beyond that, on top of a $19 monthly platform charge, with Enterprise starting at $25,000 a year. Grafana Cloud observability is billed separately by usage.
For 25 engineers with 10 on rotation, at list prices:
| Cost component | Rootly Essentials | Grafana IRM Pro |
|---|---|---|
| If all 25 take part in incidents | 25 at $20 plus 10 at $20 for on-call, so $700 | 25 at $20 plus $19, so $519 |
| If only the 10 on rotation take part | 10 at $20 plus 10 at $20, so $400 | 10 at $20 plus $19, so $219 |
| SMS and voice | Part of On-Call | Included |
| Status pages | Included | Separate product |
| AI root-cause work | AI SRE quote on top | Sift included |
| Free tier | ✘ | Up to 3 active users |
Grafana IRM costs less at both team shapes and includes its AI checks, though it requires Grafana Cloud for the telemetry that makes Sift useful. Rootly costs more and adds an AI SRE quote, but includes status pages and a much deeper response process.
Pick Grafana IRM when Grafana Cloud already holds your telemetry and your engineers solve problems by reading dashboards. It is a natural match for teams that want AI checks grounded in raw data, organizations with lots of people who join incidents only now and then, and regulated buyers who need FedRAMP or PCI DSS. Plan for a separate status page and a lighter incident process.
Pick Rootly when your telemetry is scattered across vendors or the struggle is organizing people rather than locating evidence. It fits chat-centric engineering teams who want fine-grained workflows and value an AI SRE that reasons over changes and history. If you have settled on a chat-first tool and are now choosing which one, start with our incident.io vs Rootly comparison.
These tools disagree about what matters most during an incident. Grafana IRM bets that the answer is in the data, so it keeps the incident next to the telemetry and lets Sift read it. Rootly bets that the hard part is people and process, and builds everything around the channel.
Look at how your last few incidents actually got solved. If someone found the answer by staring at the right graph, Grafana is built for that. If the answer was clear quickly but nobody knew who should act on it, Rootly is the tool that fixes your real problem.
Rootly's MCP server can reach incidents but not telemetry, and Grafana's has to span several backends. Better Stack's MCP server sits over one 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.
With incidents and telemetry behind one MCP endpoint, your assistant can investigate and respond without switching tools. Try Better Stack.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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