change-lifecycle

Plan and execute safe host configuration changes by generating a structured change plan and rollback bundle before applying patches, config edits, or restarts. This dry-run planning approach captures durable evidence and ensures rollback readiness to reduce outage risk during maintenance.

Change management drift detection compares post-change behavior against a baseline configuration snapshot to flag anomalies. You need it after applying patches, upgrades, or restarts across single units or clusters to verify controlled admin changes did not introduce unexpected state drift.

Capture pre-change and post-change verification evidence using helper scripts like change_collect.py and change_store.py. These scripts record change_request, config_snapshot, change_plan, rollback_bundle, and change_result data in a SQLite-backed runtime state for durable auditability.

Yes, you can use SQLite for runtime state tracking during cluster upgrades and rollbacks. The workflow requires a SQLite-backed runtime to store change plans, configuration snapshots, and rollback bundles, ensuring controlled execution and drift verification across managed hosts.

The best way to verify rollback readiness is to initiate a dry-run change lifecycle that collects current state, diffs against the target configuration, and validates the generated rollback bundle. This pre-change verification ensures safe rollout before any actual patch is applied.

Yes, you need helper scripts like change_capture_run.py and change_query.py to automate drift detection and evidence capture. They execute the workflow that records state and flags post-change anomalies across single units or clusters during admin maintenance.