· Cloud · 2 min read
Observability during migrations: metrics that matter first
Which signals to wire up before the first workload moves.
Observability during migrations needs to be stronger than normal operations. When systems move, you need to see both the old and new environments clearly. The goal is fast detection and fast response, not perfect charts.
Start with a baseline. Capture latency, error rate, and throughput for key user flows before the first migration step. These baseline dashboards become your reference during cutover and validation. Without baselines, you cannot prove that the new system is stable.
Signals that matter first
Create side by side views of old and new environments. Track replication delay, queue lag, and critical API error rates. Keep the dashboard simple so it is readable under pressure. If a view does not support a decision, remove it.
Logs and traces should use consistent identifiers across environments. Tag versions, environments, and tenant identifiers so you can filter quickly. For traces, focus sampling on high value paths rather than trying to trace everything.
Include data validation metrics. During migration you can have silent data loss even when services are up. Track record counts, checksum mismatches, and processing delays in the pipeline. These indicators are often more useful than generic CPU charts.
Alerting during migration
Prioritize alerts tied to user impact. Avoid noisy infrastructure alerts that do not require action. During migration, alerting should help the team decide whether to continue, pause, or roll back.
Keep an on call playbook close to the dashboards. The goal is not to collect metrics but to use them for fast, confident decisions.
Good observability shortens the time from detection to action. That is the real value during a migration.
Instrument the migration tooling itself. Track time spent in data copy, validation, and cutover steps. This helps you estimate the next wave and identify where automation can save time.
Make it easy to compare user impact across environments. Use synthetic checks or simple end to end tests that run every few minutes. If a synthetic check fails, you can pause before customers notice.
Keep dashboards and alerts close to the runbook. If the team has to search for the right view during the cutover, response time suffers. A small set of known views is better than a large set of unused ones.
