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You should worry about a growing replication queue when the standby falls further behind than your application can tolerate, or when the WAL kept for that standby starts consuming the disk headroom you need. A lag number that rises for a few seconds is rarely the signal. A backlog that keeps growing while the standby is connected, and that is not shrinking, is.
This guide uses PostgreSQL physical streaming replication as the concrete example, because the PostgreSQL documentation is the authoritative reference for the metrics and behaviour described here. The view names, column names and thresholds below do not transfer unchanged to MySQL, Kafka, or managed database migration services, so check their own documentation before applying the same logic.
Start with the freshness your application actually needs
There is no universal number of seconds or bytes at which every PostgreSQL system should page someone. A reporting replica that refreshes once an hour can tolerate minutes of delay. A read replica serving logged-in users, or a standby that is the failover target for a payment system, may need delay measured in seconds. Before you look at any metric, write down three things:
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- The maximum time a failover can take before the standby must be promotable.
- The disk budget the primary can spend on WAL retained for replication.
Those three numbers are your alert thresholds. Everything else in this article is about measuring them correctly.
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What the lag columns in pg_stat_replication actually measure
The view pg_stat_replication on the primary has one row for each standby directly connected to that server. It exposes WAL positions (sent_lsn, write_lsn, flush_lsn, replay_lsn) and three interval columns, write_lag, flush_lag and replay_lag. Each interval describes how long recent WAL took to reach a particular stage on the standby.
replay_lag is the one most people mean
For an asynchronous standby, the PostgreSQL documentation states that replay_lag approximates the delay before recent transactions become visible to queries. That is the number that matters for read freshness, because it describes what a user querying the standby would see.
write and flush lag tell you where the pipeline is slow
If write_lag is large, the standby is slow to receive or write WAL, which often points to network throughput or the standby’s I/O. If write_lag is small but flush_lag or replay_lag is large, WAL is arriving but not being flushed or applied quickly enough. That usually means the standby’s replay process, a long-running query on the standby that blocks replay, or disk pressure on the standby is the bottleneck.
What lag values do not tell you
This is the most common misreading. The PostgreSQL documentation is explicit that the reported lag times are not predictions of how long the standby will take to catch up at the current replay rate. A standby showing 90 seconds of replay_lag does not mean it will be current in 90 seconds. Lag is a measurement of recent WAL progress, not an estimate of remaining work.
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Idle systems also produce confusing values. When the standby has caught up and the primary is generating little WAL, the lag columns can eventually become NULL rather than zero. A NULL in an idle period is not a failure. A NULL during a period when the primary is busy is worth investigating, because it means the standby has stopped reporting progress.
Use the byte gap to answer the catch-up question
To estimate whether the standby is gaining or losing ground, compare WAL positions over time rather than reading a single lag value. Run this on the primary:
SELECT application_name,
client_addr,
state,
pg_size_pretty(pg_wal_lsn_diff(pg_current_wal_lsn(), replay_lsn)) AS replay_gap,
replay_lag
FROM pg_stat_replication;Sample this every minute or so and record the replay_gap value. The question to ask is whether the gap is shrinking, flat, or growing. A flat or growing gap while the standby is connected means replay is not keeping pace with newly generated WAL. A shrinking gap means the standby is catching up, even if replay_lag still looks high.
When a growing queue is a real problem
A growing queue is worth acting on when one of these conditions holds:
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- The replay gap has grown across several consecutive samples and is not returning to a baseline after normal load drops.
- The observed replay delay exceeds the freshness objective you wrote down earlier.
replay_lsnhas stopped advancing whilesent_lsnkeeps moving.- The standby has disconnected, so the view no longer shows it and the primary is retaining WAL for it.
A single spike during a bulk load or a large vacuum on the primary is not the same as a sustained trend. Give the standby time to recover from known events before escalating.
Diagnose the direction: data not arriving, or replay falling behind
The next decision depends on which position is moving.
| Observation | Likely meaning | First check |
|---|---|---|
sent_lsn advancing, write_lsn lagging |
WAL is sent but not written on the standby | Network throughput, standby disk I/O |
write_lsn advancing, replay_lsn flat |
WAL is received but replay is blocked or slow | Long-running standby queries, replay CPU, standby disk |
sent_lsn flat, row missing from the view |
Standby is disconnected | Standby log, network path, authentication, replication slot state |
| Lag NULL with primary idle | Standby is caught up and nothing new is generated | Confirm WAL generation rate before treating it as a fault |
When WAL is arriving but replay is blocked, a standby that serves queries is often the cause. Long-running read transactions on the standby can delay replay conflicts, depending on your settings. Check the standby’s activity and its replay settings before changing anything on the primary.
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Replication slots and disk risk
A replication slot tells the primary to keep WAL until the consumer has read it. That protects continuity: a standby that briefly disconnects can resume from where it stopped instead of needing a full base backup. The cost is that a disconnected or stalled consumer can cause WAL to accumulate on the primary.
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The PostgreSQL documentation warns that slots can retain enough WAL to fill the primary’s pg_wal space. If that happens, the primary can stop accepting writes, which turns a standby problem into an outage on the primary. This is the main reason a growing replication queue can become urgent even when the standby’s freshness looks acceptable.
Check slot retention and free space
On PostgreSQL 13 and later, pg_replication_slots exposes active, restart_lsn, wal_status and safe_wal_size. Check it together with free space on the volume holding pg_wal:
SELECT slot_name,
active,
wal_status,
pg_size_pretty(safe_wal_size) AS safe_wal_remaining,
pg_size_pretty(pg_wal_lsn_diff(pg_current_wal_lsn(), restart_lsn)) AS retained_wal
FROM pg_replication_slots;An inactive slot with a growing retained_wal value is the most urgent pattern you can see on the primary. Act on it before the standby’s lag becomes a user-facing problem.
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The max_slot_wal_keep_size tradeoff
Setting max_slot_wal_keep_size limits how much WAL a slot can retain, and PostgreSQL enforces that cap at checkpoint time. This protects the primary’s disk. The tradeoff is that if WAL required by a slot is removed because the slot fell too far behind, its standby may no longer be able to continue replication from that slot. Recovering usually means rebuilding the standby from a new base backup.
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Treat the cap as a recovery decision, not a cleanup switch. Before you set it, decide how long a standby can be disconnected before you would rather rebuild it than keep disk reserved, and make sure you monitor wal_status so you know when a slot is approaching that limit.
Setting your own alert threshold
Build the threshold from the inputs you already have. A practical starting structure is:
- Freshness alert: warn when
replay_lagor the replay gap exceeds a fraction of your freshness objective, and page when it stays above the full objective for longer than your normal recovery window. - Trend alert: warn when the replay gap grows across several consecutive samples while the standby is connected.
- Disk alert: warn when the retained WAL for any slot, or the free space on
pg_wal‘s volume, crosses a level that leaves enough time to respond at the observed WAL generation rate. - Slot state alert: alert on any inactive slot, and on any slot whose
wal_statusmoves toward a state where its required WAL is no longer guaranteed.
The exact numbers depend on your workload. A primary that generates a gigabyte of WAL an hour has very different headroom from one that generates a gigabyte a minute, so calculate time-to-full from your measured WAL rate rather than copying a fixed byte value from another system.
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A short decision checklist
- Is the standby serving reads, acting as a failover target, feeding analytics, or consuming changes? Each use has a different tolerance.
- Is the replay gap shrinking, flat, or growing over the last several samples?
- Is the standby connected, and are
sent_lsnandreplay_lsnstill moving? - Is any replication slot inactive, and how much WAL is it retaining compared with free space?
- If the cap were reached tomorrow, do you have a documented path to rebuild the standby?
If the answer to the first three questions shows a sustained trend that breaks your freshness objective, or the last two show disk or slot risk, the queue deserves immediate attention. If the lag is high only during known load and recovers on its own, it is usually a capacity question for later.
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