PostgresqlExporterError #

Postgresql exporter is showing errors. A query may be buggy in query.yaml

alert: PostgresqlExporterError
annotations:
  description: |-
    Postgresql exporter is showing errors. A query may be buggy in query.yaml
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/postgres-exporter/postgresqlexportererror/
  summary: Postgresql exporter error (instance {{ $labels.instance }})
expr: pg_exporter_last_scrape_error > 0
for: 0m
labels:
  severity: critical

Here is a runbook for the Prometheus alert rule “PostgresqlExporterError”:

Meaning #

The PostgresqlExporterError alert is triggered when the pg_exporter_last_scrape_error metric is greater than 0, indicating that the PostgreSQL exporter is experiencing errors. This can be caused by a variety of issues, including bugs in the query.yaml file or issues with the PostgreSQL database itself.

Impact #

If left unaddressed, this error can lead to incomplete or inaccurate metric data, which can impact the reliability of monitoring and alerting systems. This can result in delayed or missed responses to critical issues, potentially leading to downtime or data loss.

Diagnosis #

To diagnose the issue, follow these steps:

1. Check the PostgreSQL exporter logs for error messages related to the query.yaml file or database connection issues.
2. Review the query.yaml file for any recent changes or updates that may be causing the errors.
3. Verify that the PostgreSQL database is reachable and that the credentials used by the exporter are valid.
4. Check the metric values and labels associated with the alert to identify any patterns or correlations that may indicate the root cause of the issue.

Mitigation #

To mitigate the issue, follow these steps:

1. Check the query.yaml file for any bugs or issues and update it as necessary.
2. Verify that the PostgreSQL database connection details are correct and that the credentials are up-to-date.
3. Restart the PostgreSQL exporter to ensure that any changes take effect.
4. Monitor the exporter metrics to ensure that the error has been resolved and that data is being collected correctly.
5. If the issue persists, consider increasing the logging verbosity of the exporter to gather more detailed information about the error.

Remember to update the runbook with any additional information or steps specific to your environment.