Backup & Recovery
Our infrastructure layer preserves the assets required to restore the technology stack after corruption, deletion, infrastructure failure, or an unsuccessful deployment.
What is covered
Backup and recovery can apply to data, indexes, configuration, models, system state, and audit history. These assets do not all require the same recovery strategy.
Recovery classes
Authoritative company data may require durable backups and point-in-time recovery. Derived assets such as a search or vector index may be reproducible from canonical records and therefore be rebuilt rather than restored byte-for-byte. Model artifacts and configuration can be versioned so a previously approved deployment can be reconstructed. Audit history may require a different retention model, because its purpose is historical attribution rather than application state.
- Authoritative data→Restore
- Derived index→Restore or rebuild
- Configuration→Version rollback
- Model artifact→Version restore
- Workflow state→Checkpoint / resume
- Audit history→Durable retention
Recovery point and recovery time
Backup existence is not sufficient. The architecture must answer two separate questions:
- How much state can we afford to lose?
- How long can the system remain unavailable while that state is restored?
Different components can have different answers. A nightly reproducible analytics index may tolerate a different recovery point from an operating database used continuously by automation.
Recovery verification
A backup that has never been restored successfully is an assumption.
Important recovery paths should be tested enough to establish that:
- The backup is readable
- Required credentials or configuration exist
- Dependent services can be reconstructed
- State can be restored consistently
- The recovered system can actually resume operation
Recovery also needs provenance. Restoring prior system state should not erase the historical record of the failure or the actions taken afterward.
Design principle
Recovery is designed before failure.
The objective is not to preserve every byte indefinitely. It is to identify which state is authoritative, which state is reproducible, and what mechanism returns each critical part of the platform to a known operating condition when something breaks.
Dependency-aware restoration
Restoring one component does not necessarily restore a working system. A recovered database may depend on a compatible application version. A restored model endpoint may require the corresponding tokenizer, runtime, adapter, and routing configuration. A workflow checkpoint may be unusable if the external system it references has already moved to a different state.
Recovery planning therefore preserves dependency relationships as well as individual artifacts. Where possible, restoration can proceed toward a known compatible system version rather than assembling whichever backups happen to be newest independently.
This is especially important after an unsuccessful deployment, where the safest recovery state may be the last fully evaluated combination of code, model, configuration, indexes, and workflow logic — not the latest version of each component considered separately.