Automated Deployment Rollback with AI Agents
Detect a bad deploy from metrics and logs, then roll back automatically across every layer the deploy touched.
Prometheus
Terraform
KubernetesThe problem today
Your deploy succeeds technically but breaks production. Latency spikes, error rate climbs, a canary percentile goes yellow. The on-call engineer sees the graphs, starts the rollback, realizes the rollback also has to revert a Terraform change and a schema migration, pages someone else for the DB piece, and by the time it's fully reverted, the SLO burn is done for the month.
How AI agents solve it
The Orchestrator Agent watches the golden signals during and after every deploy via Prometheus/Datadog. When a rollback condition triggers (latency, error rate, canary divergence) it executes the full rollback DAG: the Kubernetes revert, the Terraform revert, and whatever else was in the original deploy graph. Humans get paged with the rollback already in progress and the evidence that triggered it.
Who this is for: SRE and release engineering teams running progressive delivery on Kubernetes
Manual workflow vs. Orchestrator Agent
Manual workflow
- Human spots the bad deploy in Grafana
- Manually pieces together which components need reverting
- Pages other teams for pieces outside their scope
- SLO burn exhausts while the rollback is improvised
- Every bad deploy is a learning opportunity: the same lessons, repeatedly
With the Orchestrator Agent
- Golden signals watched automatically from deploy time
- Rollback triggered the moment thresholds breach, not when a human sees it
- Full reverse-DAG execution, including infra and config layers
- On-call paged with rollback already running and context attached
- SLO burn window minimized because reaction time is measured in seconds
How the Orchestrator Agent runs this
- 01
Orchestrator Agent registers rollback conditions before the deploy starts
- 02
During and after deploy, watch golden signals (latency, error rate, saturation)
- 03
On any threshold breach, halt further progression and start rollback
- 04
Execute the reverse DAG: reverse order, reverse each step
- 05
Terraform Agent handles any infrastructure reverts
- 06
Verify the rollback reached a healthy state before declaring done
- 07
Page on-call with the rollback already in progress, not as a fresh task
Measurable impact
Cuts bad-deploy-to-rollback time from minutes to seconds
Eliminates partial-rollback incidents where only one layer reverts
Reduces SLO burn from bad deploys dramatically
On-call engagement is informational, not firefighting
Agents involved
Governed by the AI Gateway
Every agent action in this use case is audited, policy-checked, and cost-tracked
Structura's AI Gateway sits between every agent and the underlying LLM providers. Every decision made during this use case. Every plan review, every policy check, every fix PR, is routed through guardrails, logged to an immutable audit trail, and evaluated against NIST AI RMF and AIUC-1 controls.
Learn about the AI GatewayRelated use cases
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See this use case in a live demo
We'll walk you through exactly how the Orchestrator Agent handles this in a real environment with your stack, your policies, and your constraints.