Disaster recovery for an AI control plane is the plan for restoring service after a full loss of a region, environment, or the control plane itself, from backups and redundant material rather than by promoting an already-running standby. This is a different discipline from live multi-region failover, which assumes a healthy replica exists and is simply promoted; DR assumes there may be nothing healthy left to promote, and the restoration has to be built from stored state.

Live regional failover, where a standby is already running and just needs promotion, is the more common and faster-recovering scenario. This post is about the harder, less frequent case: rebuilding from backup after a loss severe enough that failover alone doesn't cover it.

What makes control-plane DR different from a conventional application

A conventional application's DR plan typically restores a database and redeploys application code — largely mechanical, well-trodden work. An AI control plane's DR plan has to restore several categories of state that have properties beyond simple data restoration:

  • Policy and configuration, which is comparatively easy — versioned configuration restores cleanly if it was backed up as a coherent, versioned unit in the first place. See guardrail policy as code and versioning.
  • The audit chain, which has an ordering and integrity requirement that a naive restore can violate. A cryptographically chained audit log's value comes from its unbroken sequence; restoring from a backup that's missing the tail end of the chain, or restoring two partial chains out of order, breaks the property that made the chain trustworthy in the first place. See tamper-evident audit logs and cryptographic proofs.
  • Credential and signing material, which must not be silently regenerated. If agent credentials or signing keys are recreated fresh during recovery rather than restored from an intact backup, every previously issued credential becomes invalid and every previously signed record becomes unverifiable against the new keys — turning a recovery into a second, self-inflicted incident. See BYO KMS and per-tenant signing keys and key rotation for agent credentials for how that material should be backed up and restored without this failure mode.
  • In-flight task state, which existed at the moment of the loss and needs an explicit decision about its fate on recovery, covered below.

Setting RTO and RPO for a control plane

Recovery Time Objective (how long recovery is allowed to take) and Recovery Point Objective (how much data loss, measured in time, is acceptable) are standard DR concepts, but for a control plane they need to be set with an important multiplier in mind: the control plane's downtime is not just its own downtime. Every agent that depends on it inherits its unavailability. If your control plane is unavailable for an hour, every agent whose authorization, guardrail evaluation, or budget enforcement depends on it is functionally degraded or unavailable for that hour too, regardless of how healthy the agents' own hosts are.

This means the RTO for a control plane should be set tighter than you might set for an equivalently-sized standalone application, because the effective impact is the control plane's downtime multiplied across everything depending on it — the same reasoning that applies to setting an SLO target for a component in the request path. See high availability for an AI control plane for the fail-open/fail-closed design that determines what "degraded" actually looks like for dependent agents during that window, and SLOs for AI services for how availability targets should account for a dependency relationship like this one.

RPO for a control plane needs particular care around the audit chain: losing even a small window of audit data is not equivalent to losing the same window of, say, dashboard analytics. If your compliance posture depends on an unbroken audit record, your RPO for that specific data category may need to be tighter than your RPO for less consequential state, which argues for treating audit as its own backup category with its own objective rather than bundling it into a single blanket RPO for "the database."

What "recovered" means for in-flight work

At the moment of loss, some tasks were mid-execution. A DR plan needs to decide, explicitly, what happens to them on restore:

  1. Resume from a checkpoint, if the task's state was durably recorded before the loss and the checkpoint is intact in the backup. This is the best outcome but depends on task state having been checkpointed with enough frequency that the checkpoint isn't itself stale relative to your RPO.
  2. Retry safely from the start, if the task is idempotent and a duplicate execution is not harmful. This requires the idempotency guarantees to already exist — see retry and idempotency for agent workflows — not be invented during the recovery.
  3. Mark explicitly failed and surface for review, if neither resumption nor safe retry is possible. This is a worse outcome than the first two, but it is categorically better than the fourth option.
  4. Silently drop, which should never be the outcome your plan produces, even by omission. A restore that comes back up and simply has no record that certain tasks were ever in flight looks like a clean recovery and is actually a silent data-loss incident wearing a clean recovery's clothes.

Decide which of the first three applies to which task types before a disaster, because triaging this live, task by task, during an actual recovery is not realistic.

Running the restore as a drill

A DR plan that has only been discussed, never executed, is a hypothesis. The only way to know your actual recovery time, and to find the steps that don't work as documented, is to run the restore in an isolated environment from real backups on a recurring schedule.

A useful drill checklist:

  • Restore configuration and policy from backup into an isolated environment and confirm it matches the last known-good version, not a stale one.
  • Restore the audit chain and verify its integrity end to end — not just that data exists, but that the chain validates.
  • Restore credential and signing material and confirm previously issued credentials and previously signed records remain valid against the restored material.
  • Exercise the in-flight-task recovery logic against synthetic tasks that were "in flight" at the simulated moment of loss, and confirm each resolves per your defined policy — resumed, retried, or explicitly marked failed.
  • Time the entire drill and compare against your stated RTO.
  • Document every deviation between what the plan says and what the drill actually required, and fix the plan.

Treat a failed or slower-than-expected drill as a successful use of the drill, not a bad outcome — that's precisely what the exercise is for. A drill that goes perfectly on the first attempt is more likely to indicate an insufficiently rigorous drill than a genuinely resilient system.

A worked example

Simulate total loss of your primary environment, including its live control-plane instances and its most recent backups' source systems, restoring only from your offsite backup copy.

  1. Stand up the control plane in an isolated recovery environment from the offsite backup.
  2. Restore configuration first and confirm version and content match expectations.
  3. Restore the audit chain and run an integrity check across the full chain, not just the most recent entries.
  4. Restore signing material and verify a sample of previously signed audit entries still validates against it.
  5. Replay a set of synthetic in-flight tasks that existed at the simulated loss point and confirm each resolves according to your defined per-task-type policy.
  6. Record total elapsed time against your RTO, and the age of the restored data against your RPO.
  7. File every gap found — a missing runbook step, a slower-than-planned restore, a task type with no defined recovery policy — as a concrete fix, then schedule the next drill to confirm the fix worked.

What good looks like

A control plane that's genuinely disaster-recovery-ready has RTO and RPO set with the dependency multiplier in mind, treats the audit chain and credential material as backup categories with their own integrity requirements rather than generic data, has an explicit, pre-decided policy for what happens to in-flight tasks on recovery, and has proven its restore time and completeness through an actual isolated-environment drill rather than a document review. The plan is only as good as the last time it was actually run.