PostgresqlHighRateStatementTimeout #

Postgres transactions showing high rate of statement timeouts

alert: PostgresqlHighRateStatementTimeout
annotations:
  description: |-
    Postgres transactions showing high rate of statement timeouts
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/postgres-exporter/postgresqlhighratestatementtimeout/
  summary: Postgresql high rate statement timeout (instance {{ $labels.instance }})
expr: rate(postgresql_errors_total{type="statement_timeout"}[1m]) > 3
for: 0m
labels:
  severity: critical

Here is a runbook for the Prometheus alert rule PostgresqlHighRateStatementTimeout:

Meaning #

The PostgresqlHighRateStatementTimeout alert is triggered when the rate of statement timeouts in a PostgreSQL instance exceeds 3 per minute. This alert indicates that there is a high rate of statements timing out in the database, which can lead to performance issues and potentially cause errors or crashes.

Impact #

The impact of this alert can be significant, as statement timeouts can:

• Cause transactions to fail, leading to data inconsistencies and errors
• Increase the load on the database, leading to performance degradation
• Potentially lead to cascading failures and crashes of dependent systems

Diagnosis #

To diagnose the cause of the PostgresqlHighRateStatementTimeout alert, follow these steps:

1. Check the PostgreSQL logs for errors and warnings related to statement timeouts.
2. Analyze the query patterns to identify which queries are causing the timeouts.
3. Check the system resources (CPU, memory, disk space) to ensure they are not overloaded.
4. Verify the database configuration to ensure that the timeout settings are correctly configured.
5. Check for any recent changes to the database, such as new applications or queries that may be causing the timeouts.

Mitigation #

To mitigate the PostgresqlHighRateStatementTimeout alert, follow these steps:

1. Identify and optimize the queries causing the timeouts.
2. Adjust the timeout settings to a more reasonable value, if necessary.
3. Increase system resources (CPU, memory, disk space) to handle the load.
4. Implement query queuing to manage the concurrent query load.
5. Consider upgrading the PostgreSQL instance to a more performant version.
6. Monitor the database closely to ensure that the issue is resolved and does not recur.