StormaticsStormatics

Guide to Auditing and Monitoring Access in PostgreSQL

In the data-driven world of today, maintaining the security and integrity of your database is paramount. Auditing and monitoring access to your database are critical components of an effective security strategy. These processes help ensure that only authorized users are accessing sensitive information and that any unauthorized access attempts are detected and addressed promptly.

PostgreSQL is renowned for its robustness, extensibility, and adherence to standards. It offers a rich set of features for auditing and monitoring, which can be leveraged to enhance security and compliance.

Purpose and Scope of the Blog

This blog aims to provide an in-depth guide on auditing and monitoring access in PostgreSQL. We will explore various tools, techniques, and best practices to help you implement effective auditing and monitoring strategies in your PostgreSQL environment.

Understanding Auditing and Monitoring

What is Auditing?

Auditing in the context of databases involves tracking and recording database activities and access. It helps organizations maintain a record of who accessed the database, what actions they performed, and when these actions occurred.

What is Monitoring?

Monitoring involves continuously observing database activities and performance to detect unusual behavior or potential security threats. It provides real-time insights into the state of the database and helps in proactively managing and securing the database environment.

Why Are They Important?

Security: Detect and prevent unauthorized access.
Compliance: Meet regulatory requirements (e.g., GDPR, HIPAA).
Performance: Identify and resolve performance bottlenecks.
Accountability: Maintain a trail of user activities for analysis and accountability.

PostgreSQL Auditing Tools

pgAudit

`pgAudit` is a popular PostgreSQL extension designed to provide detailed logging of database activities. It allows you to audit SQL statements, including SELECT, INSERT, UPDATE, DELETE, and DDL operations.

Installing pgAudit

To install `pgAudit`, follow these steps:

  1. Install the extension
sudo apt-get install postgresql-contrib
  1. Add the extension to your PostgreSQL instance
CREATE EXTENSION pgaudit;

Configuring pgAudit

Configuration options for `pgAudit` are set in the `postgresql.conf` file. Here are some key parameters:

  • pgaudit.log: Specifies the classes of statements to be logged (e.g., READ, WRITE, FUNCTION, ROLE).
  • pgaudit.log_level: Sets the log level (e.g., `log`, `info`, `notice`, `warning`, `error`).

Example configuration:

pgaudit.log = 'read, write'
pgaudit.log_level = 'log'

Using pgAudit

Once configured, `pgAudit` will start logging the specified activities. You can view the audit logs in the PostgreSQL log files.

SELECT * FROM pg_log;

PostgreSQL Logging

PostgreSQL’s built-in logging capabilities can also be leveraged for auditing purposes. By configuring the logging settings, you can capture a wide range of database activities.

Configuring PostgreSQL Logging

Edit the `postgresql.conf` file to enable and configure logging:

  • logging_collector: Enable the logging collector.
    logging_collector = on
  • log_destination: Set the log destination (e.g., `stderr`, `csvlog`).
    log_destination = ‘csvlog’
  • log_statement: Log SQL statements (e.g., `none`, `ddl`, `mod`, `all`).
    log_statement = ‘all’
  • log_line_prefix: Customize the log line prefix.
    log_line_prefix = ‘%m [%p] %q%u@%d ‘

Viewing Logs

Logs are typically stored in the `pg_log` directory within the PostgreSQL data directory. You can view and analyze these logs using various tools or custom scripts.

Advanced Auditing Techniques

Fine-Grained Auditing

Fine-grained auditing allows you to audit specific actions or conditions. This can be achieved using triggers or custom logging functions.

Using Triggers for Auditing

Create a trigger function to log specific changes:

CREATE FUNCTION audit_log() RETURNS trigger AS $$
BEGIN
    INSERT INTO audit_table(user_name, action, timestamp)
    VALUES (current_user, TG_OP, now());
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

Create a trigger to call the function:

CREATE TRIGGER audit_trigger
AFTER INSERT OR UPDATE OR DELETE ON employees
FOR EACH ROW EXECUTE FUNCTION audit_log();

Conditional Auditing

Conditional auditing involves logging activities based on specific conditions, such as user roles or data values.

Example: Auditing Specific User Actions

CREATE OR REPLACE FUNCTION conditional_audit() RETURNS trigger AS $$
BEGIN
    IF current_user = 'analyst' THEN
        INSERT INTO audit_log(user_name, action, timestamp)
        VALUES (current_user, TG_OP, now());
    END IF;
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

Monitoring Tools and Techniques

pg_stat_statements

`pg_stat_statements` is an extension that provides detailed statistics on SQL statements executed in the database.

Installing and Configuring pg_stat_statements

  1. Install the extension:
CREATE EXTENSION pg_stat_statements;
  1. Configure the extension in `postgresql.conf`:
shared_preload_libraries = 'pg_stat_statements'

Using pg_stat_statements

Query the `pg_stat_statements` view to get insights into query performance and frequency:

SELECT * FROM pg_stat_statements;

pgAdmin

`pgAdmin` is a feature-rich administration and monitoring tool for PostgreSQL. It provides a graphical interface for managing and monitoring databases.

Features of pgAdmin

  • Query Tool: Execute and analyze SQL queries.
  • Dashboard: Monitor database performance metrics.

Log Analysis: View and analyze PostgreSQL logs.

Real-Time Monitoring

Using Prometheus and Grafana

Prometheus is an open-source monitoring and alerting toolkit, and Grafana is a visualization tool. Together, they provide a powerful solution for real-time monitoring of PostgreSQL.

Setting Up Prometheus

  1. Install Prometheus:
sudo apt-get install prometheus
  1. Configure Prometheus to scrape PostgreSQL metrics:
   scrape_configs:
     - job_name: 'postgresql'
       static_configs:
         - targets: ['localhost:9187']

Setting Up Grafana

  1. Install Grafana:
sudo apt-get install grafana
  1. Add Prometheus as a data source in Grafana.

     

  2. Create dashboards to visualize PostgreSQL metrics.

Best Practices for Auditing and Monitoring

General Best Practices

  • Define Clear Objectives: Know what you need to audit and monitor.
  • Enable Comprehensive Logging: Capture all relevant activities.
  • Use Extensions and Tools: Leverage available tools for enhanced capabilities.
  • Regularly Review Logs: Analyze logs to detect and respond to anomalies.

Security Configuration Tips

  • Secure Logging: Ensure logs are stored securely and access is restricted.
  • Encrypt Connections: Use SSL/TLS to encrypt database connections.
  • Regular Updates: Keep PostgreSQL and its extensions up to date.

Common Pitfalls and How to Avoid Them

  • Overlogging: Avoid excessive logging, which can lead to performance issues.
  • Ignoring Logs: Regularly review and act on logged data.
  • Inconsistent Policies: Ensure auditing policies are consistently applied.

Future Trends in Database Auditing and Monitoring

Increasing Role of AI and Machine Learning

AI and machine learning will play a significant role in enhancing database auditing and monitoring by providing advanced anomaly detection and predictive analytics.

Integration with Cloud Services

As more databases move to the cloud, integration with cloud-native monitoring and auditing services will become more prevalent.

Enhanced Privacy and Compliance Features

Future versions of PostgreSQL and related tools are likely to include enhanced features for privacy and compliance, driven by evolving regulations.

Concluding Thoughts

In this blog, we explored the importance of auditing and monitoring access in PostgreSQL. We covered various tools and techniques, including `pgAudit`, PostgreSQL logging, and real-time monitoring with Prometheus and Grafana. We also discussed best practices, advanced strategies, and future trends.

Implementing robust auditing and monitoring practices in PostgreSQL is essential for maintaining database security, ensuring compliance, and optimizing performance. By leveraging the tools and techniques discussed in this blog, you can create a secure and efficient PostgreSQL environment.


 

Further reading

Stormatics Professional Services

Blogs

Frequently Asked Questions (FAQs)

Q. How does pgAudit differ from standard PostgreSQL logging for compliance purposes?

Standard PostgreSQL logging is primarily intended for operational troubleshooting and performance analysis, and it lacks the structured semantics required for compliance auditing. pgAudit is designed specifically for audit use cases (such as GDPR, HIPAA, or SOX) by providing detailed, session-aware logging of statement classes (e.g., READ, WRITE, ROLE) and object access. Sensitive credentials are not logged by either system, but pgAudit offers deterministic, compliance-friendly audit trails that standard logging cannot reliably provide.

Fine-grained auditing of data changes is typically implemented using row-level DML triggers (AFTER INSERT, UPDATE, or DELETE) on sensitive tables. These triggers can record the acting user, timestamp, and modified keys into a dedicated audit table only when required. Event triggers, by contrast, apply exclusively to DDL operations and are used to audit schema changes rather than row-level data access.

The industry-standard approach combines postgres_exporter to scrape database metrics, Prometheus to store this time-series data, and Grafana to visualize it. This stack allows you to create real-time dashboards for critical metrics like active connections, cache hit ratios, and replication lag.

Enable the pg_stat_statements extension, which aggregates execution statistics for all SQL statements run against the server. By querying the pg_stat_statements view, you can instantly rank queries by total execution time or call frequency to pinpoint exactly which operations are degrading system performance.

Enabling excessive logging (e.g., log_statement = ‘all’) generates massive I/O overhead that can slow down transaction processing and rapidly consume disk storage. Best practice dictates logging only DDL changes and authentication events globally, while reserving detailed statement logging for specific sessions or debugging scenarios.

Latest Blogs

February 3, 2026

PostgreSQL Materialized Views: When Caching Your Query Results Makes Sense (And When It Doesn’t)

Your dashboard queries are timing out at 30 seconds. Your BI tool is showing spinners. Your users are refreshing the…
January 29, 2026

Unlocking High-Performance PostgreSQL: Key Memory Optimizations

PostgreSQL can scale extremely well in production, but many deployments run on conservative defaults that are safe yet far from…
January 27, 2026

Unused Indexes In PostgreSQL: Risks, Detection, And Safe Removal

Indexes exist to speed up data access. They allow PostgreSQL to avoid full table scans, significantly reducing query execution time…

Leave A Comment