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Monitoring / Observability / Incident

Incident.io AI Integration

Connect Incident.io to BeforeQuery for grounded AI answers and agent actions across Monitoring / Observability / Incident.

What is it?

About Incident.io

Incident.io is one of the Monitoring / Observability / Incident platforms BeforeQuery connects to. Once linked, the platform's data becomes a first-class source for grounded AI answers and a target for policy-gated agent actions — the same identity, approval, and audit-log guarantees every other integration ships with.

Setup

How to connect Incident.io

  1. Step 01

    In the BeforeQuery dashboard, go to Integrations → Monitoring / Observability / Incident and select Incident.io.

  2. Step 02

    Sign in to Incident.io with an account that has permissions to grant BeforeQuery the Monitoring / Observability / Incident scopes required.

  3. Step 03

    Confirm the connection. Incident.io is now available as a source and action target for every playbook in your workspace.

How BeforeQuery uses Incident.io

What the agent does with your Incident.io connection

  • 01

    Read metrics, alerts, and incident state from Incident.io to power incident-response playbooks.

  • 02

    Trigger playbooks on Incident.io alerts — auto-create Jira tickets, page on-call, coordinate war-room channels.

  • 03

    Draft incident-status updates for stakeholders, grounded in the specific Incident.io data driving the incident.

  • 04

    Answer "is X system healthy?" questions with live data straight from Incident.io.

Use cases

What teams actually do with the Incident.io integration

Auto-declared incident workflow

Incident.io alert fires above sev-2 → BeforeQuery declares an incident, opens a Slack war-room, pages the correct on-call rotation, and starts a running timeline in the incident record. Zero manual coordination overhead.

Stakeholder status updates

During an ongoing incident, BeforeQuery drafts an every-15-minutes status update for the customer-facing channel, grounded in the latest Incident.io data + engineer chat context. Comms lead approves; message goes out.

Retrospective draft from Incident.io timeline

Post-incident, BeforeQuery reconstructs the timeline from Incident.io events, Slack messages, and deploy logs. Draft retrospective has the timeline, contributing factors, and next steps ready for the retro meeting.

Answer questions grounded in Incident.io

Employees and customers ask Incident.io-related questions in Slack, Teams, or the widget — BeforeQuery answers with the exact Incident.io record shown alongside the response. No context switching, no "log into Monitoring / Observability / Incident to check" round-trips.

Incident.io — Frequently Asked Questions

Common questions about connecting BeforeQuery to Incident.io.

Yes — both are writeable via approved playbooks. Acking is typically autopilot (playbook confirms the alert was received + triaged); resolving typically requires operator sign-off since it clears the on-call queue.
Standard OAuth 2.0 where Incident.io supports it, otherwise API-key or bearer-token auth. Credentials are stored encrypted at rest (AES-256-GCM) per workspace, never shared across customers, and rotated on request. The connection is scoped to the least-privilege set of scopes each playbook needs — you approve the scope list on install.
No. Your Incident.io data feeds only your workspace's own agents and answers. Nothing is used to train a shared model, and nothing crosses workspace boundaries. Bring-your-own-model is available on Enterprise if you want to pin inference to your own OpenAI / Anthropic / self-hosted deployment.
Yes. Every Incident.io integration is scoped at install time — you pick which resources, users, or record types are visible. You can further restrict per-playbook: a single playbook only touches the specific Incident.io objects it needs. Scope changes take effect on the next sync.
Every write is logged with the acting user, the playbook that fired it, the exact operation, the target entity IDs, and the timestamp — all in the immutable audit log. Writes are rehearsable in simulation mode against a copy of live data before they touch Incident.io for real.

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