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Atlas is Rootly’s AI layer. It brings together the AI capabilities that answer operational questions, investigate incidents, and use the context and tools available to your organization. AI SRE is one way to use Atlas: it runs a structured investigation of an alert or incident. You can also interact with Rootly AI by mentioning @Rootly in Slack, asking a question in the web or mobile chat, or sending a request through the Chat API. Atlas is an umbrella name, not a single switch in the Rootly app. Its entry points and supporting context have separate controls. What each one can read or do depends on its surface, enablement, your permissions, and the tools connected to your team. Where the consolidated AI SRE navigation is available, the sidebar has one AI SRE item with two tabs: Investigations lists the investigations AI SRE has run, and Atlas groups the controls behind them — entry points, context and tools, investigation settings, and organization-wide AI settings. This guide uses those paths.
The consolidated AI SRE navigation is rolling out and may not be enabled for your team yet. Until it is, the same settings live under AI & Agents, with the AI SRE settings under AI & Agents → AI SRE, and investigations under Investigations in the sidebar. See AI Settings.
AI SRE has its own enablement path through your Rootly account team; turning on conversational Rootly AI does not enable investigations. Private Agent is an Early Preview for approved customers; access, including from Slack, also requires AI SRE to be enabled. The Knowledge graph and Memory can have separate availability requirements. The Chat API has its own team-level controls and also requires Rootly Agent in Slack to be enabled. See AI Settings and Manage User Permissions.

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Ways to Use Atlas

The same context source is not necessarily available on every entry point. For example, the Knowledge graph and Memory described below are currently used by AI SRE investigations; web chat has its own tool allowlist. Use each surface’s guide for its behavior and permissions.

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Context and Tools

The Knowledge graph and Memory cards sit beside Instructions and Investigation rules. They are documented here because they are part of the AI layer, even though their current reader is AI SRE. Instructions and Investigation rules configure investigations.

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How AI SRE Uses Atlas

1

Connect Your Tools and Network

AI connectors give AI SRE live access to the SaaS tools your team already uses. Private agents reach systems inside your network over an outbound-only connection, so you don’t expose them publicly.
2

Rootly Builds the Knowledge Graph

Rootly reads your Rootly services and catalog, plus supported connectors such as AWS, Google Cloud, GitHub, Datadog and Grafana. It stores what it finds as facts: what exists, what depends on what, and who owns it. Updates run in the background, and disconnecting a connector removes the facts it contributed.
3

AI SRE Investigates

AI SRE matches the names in an alert or incident to entities in the graph. It walks their dependencies to find candidate causes and map what else could be affected, recalls the best-matching Active notes from Memory, and queries your connectors and private agents for live evidence. It attributes a cause only when evidence gathered during the investigation supports it.
4

AI SRE Proposes What It Learned

After an investigation, AI SRE can propose notes to Memory. AI SRE doesn’t recall a proposed note until it’s Active. An owner or admin selects Activate, or, where automatic activation is enabled, an eligible note activates on its own after proving helpful in at least two separate investigations. AI SRE also quarantines notes on its own, for example when live evidence contradicts one.
AI connectors and private agents keep your providers’ permission boundaries, and they aren’t guaranteed to be read-only. Built-in connector tools can accept provider-defined commands or queries that change data. A Custom MCP connection exposes whichever tools you check, and a private agent can offer write-capable HTTP and SQL capabilities when its local policy allows them. Responder-started investigations use the initiating user’s Private Agent permissions; automatic investigations use the ai-sre system actor with no responder in the loop. Expose only the tools, local policies and credentials that are safe for unattended use, and prefer read-only identities. See Evidence Sources for each boundary.

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AI SRE Settings

Two settings in the AI SRE section decide how and when investigations run. When an investigation misses a fact about your environment, fix the source it comes from: a connector, a Rootly service or a catalog field. When AI SRE should work differently, such as checking recent deploys first, write that in Instructions or in a rule’s instructions. Where it’s enabled, Generate with AI on the Instructions page drafts instructions from your Knowledge graph facts, some of your connectors and your investigation rules.

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Improve AI SRE Investigations

  1. Connect your primary observability provider, your code or deployment provider, and the knowledge source that holds your runbooks. Add other connectors when an investigation shows a specific gap. If you connect Datadog with OAuth, change and deploy correlation isn’t included, so use API and application keys if AI SRE needs to investigate what changed.
  2. Fill in your Rootly services and catalog. A service’s Datadog ID, GitHub repository, PagerDuty ID and Kubernetes deployment name let AI SRE match an alert to that service. Its dependencies, owners and tier fields feed the Knowledge graph. When sources disagree about what a thing is, declared data like this outranks anything inferred from telemetry.
  3. Describe your infrastructure. Connect AWS or Google Cloud, or give the GitHub connector access to your infrastructure-as-code repository. Rootly picks that repository automatically. See Knowledge Graph for every source it reads.
  4. If approved for the Private Agent Early Preview, add a private agent for systems the internet can’t reach, such as an in-cluster Prometheus or an internal database.
  5. Review Memory. Activate useful proposed notes, and deprecate or quarantine notes that are obsolete or misleading. Only Active notes reach later investigations. Manual status changes require an Incident Response Owner or Admin with a seat; where enabled, AI SRE can also activate, deprecate, quarantine, or replace notes automatically under the conditions in the Memory guide.
Let completed investigations show you what’s missing. A run that ends Could not investigate stopped before it gathered enough evidence, so check that the connectors for that alert’s source are connected and authorized. For Inconclusive — needs human, look in the Investigation path for checks that were inconclusive or gathered no evidence, then read Recommended next steps. See Reading the Result.

Knowledge Graph

Explore the services, infrastructure and relationships AI SRE uses, with the evidence behind each relationship.

AI Connectors

Connect observability, code, cloud, work-tracking and knowledge tools under AI SRE → Atlas → Connectors (AI & Agents → Connectors if your sidebar doesn’t have an AI SRE item).

Memory

Review, activate, deprecate or quarantine the learnings AI SRE recalls in later investigations.

Private Agents

Reach systems inside your network through an outbound-only, policy-controlled agent.

Rootly AI SRE

Investigate alerts and incidents through one of Atlas’s entry points.

Evidence Sources

See what an investigation reads from each part of Atlas, and the access boundaries that apply.

Rootly AI in Slack

Ask Rootly AI questions and take permitted actions in Slack.

Rootly AI in Web

Ask questions about an incident from its web page.

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Frequently Asked Questions

Atlas has no switch of its own. The Atlas tab gathers the controls, but each one is enabled separately: configure Slack, web, and mobile chat under AI SRE → Atlas → Conversations (AI & Agents → Features if your sidebar doesn’t have an AI SRE item), connections under AI SRE → Atlas → Connectors or Private agents, and investigations under AI SRE → Atlas → Instructions and Investigation rules. The Chat API has separate team-level controls and also requires the Rootly Agent in Slack toggle. Your Rootly account team enables AI SRE separately; turning on Opt in to Rootly AI capabilities doesn’t enable investigations.
Atlas is the AI layer behind the entry points above, but they do not all use the same tools or data. Currently, AI SRE reads the Knowledge graph and Memory; connectors also serve supported conversations, and web chat uses a narrower read-only tool set. Check the relevant surface guide before assuming a capability is available there.
Yes. Open AI SRE → Atlas → Knowledge graph, search for the service and select it. The detail panel lists its attributes and each relationship with its evidence and sources, such as Observed · Datadog. The page is view-only, so correct a fact in the system it came from. To see what AI SRE has learned from investigations, open AI SRE → Atlas → Memory.
For what a thing is, such as its kind, tier or environment, declared sources like infrastructure as code, the catalog and your cloud accounts outrank telemetry, and confidence breaks ties. Relationships from every source are kept and labeled by evidence: Observed, Declared, Capability or Corroborated. When Rootly finds an environment or resource type conflict it can’t settle, the Knowledge graph page shows Some graph data needs attention.
No. AI SRE recalls only Active notes, treats each one as a hypothesis to check against live evidence, and can’t conclude a root cause from a note alone.
Rootly deletes the facts that connector contributed when you disconnect it. Facts from your Rootly services and catalog stay.