Replication Lag Debugger

Replication Lag Debugger

Stop stale-read bugs caused by reads racing ahead of replication. A read replica is eventually consistent: a write committed on the primary is not instantly visible on replicas, so most "the data disappeared after I saved it" reports are reads hitting a replica that hasn't caught up - not data loss.

Workflow

1. Confirm it's a lag bug, not data loss. Re-read the same row from the primary. If it's present on the primary but missing/stale on a replica, it's replication lag. If it's missing on the primary too, this is the wrong skill - it's a write/transaction bug.
2. Measure the lag with real numbers - never prescribe a fix without this.
   • Postgres: on the primary capture pg_current_wal_lsn(); on each replica read pg_last_wal_replay_lsn() and pg_last_xact_replay_timestamp(); inspect pg_stat_replication for the write/flush/replay LSN gaps.
   • MySQL: read Seconds_Behind_Source from SHOW REPLICA STATUS (treat as approximate - it stalls at 0 then jumps).
   • Record the actual gap (LSN delta and time) and whether it's steady or spiking. For calibration: healthy same-region replicas typically sit well under 1 second (often tens of milliseconds); sustained lag above 10-30 seconds under normal traffic means replay genuinely cannot keep up, not just a blip.
3. Split send lag from replay lag. Compare flush-LSN gap (network/send) against replay-LSN gap (replica busy applying). The cause and fix differ; don't guess.
4. Find why it lags, matched to the split above:
   • Single-threaded replay can't keep a write-heavy primary - enable parallel apply (MySQL replica_parallel_workers; Postgres has limited parallel recovery).
   • A long-running query on the replica conflicts with WAL replay and pauses it (Postgres hot_standby_feedback / max_standby_streaming_delay tradeoff).
   • A bulk write, backfill migration, or VACUUM floods the WAL stream - throttle the backfill into smaller batches (1,000-10,000 rows per batch with a pause between batches is a common working range).
   • Cross-region network saturation adds send lag.
5. Fix the stale read with read-after-write, cheapest first:
   • Route a user's reads to the primary for a short window after their write (session stickiness keyed by user) - 5-10 seconds comfortably covers normal lag without pinning traffic to the primary for long.
   • Or always read your own writes from the primary, replicas for other users' data.
   • Or use LSN/GTID tracking: capture the write's LSN, then have the read wait until the chosen replica's replay LSN passes it (Postgres poll pg_last_wal_replay_lsn(); MySQL WAIT_FOR_EXECUTED_GTID_SET).
6. Make read routing deliberate. Tag every query strongly-consistent (primary) or staleness-tolerant (replica). Dashboards, analytics, and lists tolerate seconds of lag; a user re-reading the form they just submitted does not. Build routing into the data layer, not ad hoc per call site.

Deliverable

Produce a lag diagnosis and fix plan containing: the measured lag (LSN delta and seconds, with the send-vs-replay split, steady vs spiking), the identified root cause from step 4, the chosen read-after-write strategy and its scope (which users/queries, what window), the query routing classification (which reads go primary vs replica and why), and the alert thresholds tied to your consistency SLA rather than an arbitrary number.

Quality bar

• A captured lag measurement (LSN gap and time, with send-vs-replay split) exists before any fix is proposed.
• The fix scopes primary-reads to the read-after-write window - it does not force all reads to the primary.
• Lag alarm thresholds map to your consistency SLA, not an arbitrary number.

Do NOT

• Do not force every read to the primary to dodge lag - that defeats the replica and overloads the primary.
• Do not alarm on sub-second lag, and do not page on lag spikes that coincide with a known backfill - fix the backfill batching instead.
• Do not prescribe parallel apply, hot_standby_feedback, or routing changes from the symptom alone; measure first (step 2).
• Do NOT use when the problem is connection-limit, pool-exhaustion, or "too many connections" errors - use connection-pool-tuner instead.
• Do NOT use when a single query is slow on the replica with no staleness involved - that's query tuning; use query-rewriter or n-plus-one-hunter instead.