Incident Management

One queue.
Every event type.
Full context before
you open it.

FalconIO's native incident management module is not a webhook to Jira. It is a platform-native system that understands infrastructure topology, observability state, and BC Manifests — so every ticket arrives with the context your team needs to make the first decision in under a minute.

Native Module Auto-Context Every Event Type MTTR Intelligence

The alert fired.
Now find the context. Good luck.

Standard incident tooling treats infrastructure context as something engineers assemble — from the alert, from the monitoring dashboard, from the runbook, from the infra state tool, from the DR plan. Under incident pressure this is not friction. It is the difference between minutes and hours of recovery time.

Context Lives in Four Tools

Alert in Datadog. Runbook in Confluence. Infra state in Terraform state files. DR plan in a shared drive. Under pressure, a human assembles these. Every minute of assembly is not recovery.

Event Types Are Siloed

Outages go to PagerDuty. Provisioning requests go to Jira. DR activations go to a Slack thread. Bugs go to GitHub Issues. No shared timeline. No shared MTTR metric.

Compliance Is Reconstructed

Post-incident, someone writes a post-mortem from memory. SOC 2 change management evidence is gathered manually. None of this is connected to what actually happened in the system.

The insight behind the native incident module is simple: the most expensive minutes of any incident are the first ones, spent assembling context. When the ticket already has the topology graph, the triggering metric, and the applicable BC Manifest, those minutes collapse. That is MTTR reduction.

Infrastructure-aware incident management.
Native to the platform.

Unified Event Queue

Outages, DR activations, IDP provisioning events, infrastructure changes, bugs, and post-mortems — one queue, one interface, one MTTR metric across all event types. Events are not actually separate — a provisioning failure is an incident, a DR activation is an incident, a bug causing service degradation is an incident.

Auto-Context Attachment

When an observability alert triggers an incident, the ticket is created with: the triggering metric and its current value, historical baseline from ClickHouse, affected services from the topology graph, applicable BC Manifests, and the last DR test result for this failure mode. The engineer reads. They do not assemble.

Incident Timeline

A chronological, automated record of every action taken during an incident — platform actions, operator decisions, state changes, BC Manifest executions — generated automatically, not written retrospectively. The timeline is the post-mortem input and the compliance artefact simultaneously.

BC/DR Activation From Incident

Trigger a BC Manifest failover directly from the incident ticket. The platform handles execution sequencing and logs every step into the same incident timeline. The operator confirms critical thresholds. There is no context switch between incident management and DR execution.

Post-Mortem Generation

Structured post-mortem template pre-populated from the incident timeline, observability data, topology state at incident time, and RTO actual vs declared. Engineers edit and add analysis — they do not reconstruct what happened from Slack messages and calendar entries.

MTTR Intelligence

Recovery time tracked per incident type, per service tier, per environment, per team. Trended over time in the unified dashboard. The input that tells you whether your BC Manifests, autoscaling models, and on-call practices are actually improving recovery velocity — or not.

Not just outages.
Every operational event.

P1 / P2 Outages
Full topology context, BC Manifest auto-suggestion, BC activation in one click, automated timeline, MTTR tracking from detection to resolution.
BC/DR Activations
BC Manifest execution from the incident ticket, Pulumi stack status embedded, failover sequencing logged step-by-step in the incident timeline.
Infrastructure Changes
Pulumi diff, policy check result, deployment status, rollback trigger — in the change ticket. FluxCD reconciliation status updated in real time.
IDP Provisioning Events
Request spec, policy gate result, Crossplane provisioning status, topology registration confirmation — full lifecycle in one ticket, automatically.
Bugs & Degradations
Service health from observability, topology context showing what depends on the affected service, suggested BC Manifest if degradation crosses threshold.
Post-Mortems
Auto-generated from incident timeline, observability replay, RTO actual vs declared. Linked to the originating incident and its BC Manifest for full traceability.

Native first.
Your existing tools
as integrations.

FalconIO does not require abandoning existing incident tooling. For enterprises that need Jira Service Management or ServiceNow as the system of record, FalconIO syncs bidirectionally — incident state visible in both systems, platform context available in the external tool, MTTR data flowing back into the FalconIO dashboard.

Jira Software
Bidirectional sync — incidents created in FalconIO appear in Jira with topology context embedded
Jira Service Mgmt
IT service management workflow with FalconIO infra context attached to every ticket
ServiceNow ITSM
Incident and change management records synced. ServiceNow as system of record — FalconIO adds context
PagerDuty
On-call routing with topology context and BC Manifest link embedded in the notification
OpsGenie
On-call scheduling and alert routing with same context enrichment as PagerDuty integration
Linear
Engineering bug tracking — FalconIO incidents escalate to Linear with infrastructure context attached
Slack
Real-time incident notifications, BC activation alerts, MTTR updates, and post-mortem publication
GitHub Issues
Bug and issue tracking integration for engineering-native teams, with infra context passed through