Comprehensive Guide to PostgreSQL Exporter

PostgreSQL Exporter: Monitoring PostgreSQL Metrics

PostgreSQL Exporter is a powerful tool that integrates with Prometheus to monitor PostgreSQL database metrics. It collects and exports essential database performance indicators, helping administrators ensure their database operates efficiently.

Key Features of PostgreSQL Exporter

• Integration with Prometheus: Seamlessly integrates for metric collection and visualization.
• Comprehensive Metrics: Exports queries, locks, indexes, and other performance indicators.
• Customizable Queries: Allows adding custom queries to monitor specific metrics.
• Support for Multiple Databases: Can monitor multiple PostgreSQL instances.

Setup and Syntax

Step 1: Install PostgreSQL Exporter

# Download PostgreSQL Exporter
wget https://github.com/prometheus-community/postgres_exporter/releases/latest/download/postgres_exporter

# Make it executable
chmod +x postgres_exporter

Step 2: Configure Environment Variables

# Set PostgreSQL connection details
export DATA_SOURCE_NAME="postgresql://user:password@localhost:5432/dbname?sslmode=disable"

Step 3: Run PostgreSQL Exporter

# Start PostgreSQL Exporter
./postgres_exporter

Step 4: Access Metrics

Metrics are exposed at http://localhost:9187/metrics and can be scraped by Prometheus.

Examples and Code with Explanation

Example 1: Monitoring Active Connections

PostgreSQL Exporter exposes metrics like pg_stat_activity_count.

PromQL Query:

Code:

pg_stat_activity_count{state='active'}

Explanation:

• pg_stat_activity_count provides the count of active connections to the PostgreSQL database.
• state='active' filters only active connections.

Example 2: Tracking Cache Hit Ratio

To monitor how efficiently the database is using its cache:

PromQL Query:

Code:

(rate(pg_stat_database_blks_hit[5m]) / rate(pg_stat_database_blks_read[5m])) * 100

Explanation:

• pg_stat_database_blks_hit tracks blocks fetched from cache.
• pg_stat_database_blks_read tracks blocks read from disk.
• The ratio indicates cache efficiency.

Example 3: Custom Query Setup

To monitor specific metrics, define a custom query in a YAML file:

Code:

custom_queries:
  - query: "SELECT COUNT(*) FROM users WHERE active = true;"
    metrics:
      - name: active_users_count
        type: gauge
        help: "Number of active users in the database"

Explanation:

• The custom_queries field allows defining specific SQL queries.
• Each query is mapped to a metric with a name, type, and description.

Why use PostgreSQL Exporter?

• Database Health Monitoring: Tracks slow queries, locks, and memory usage.
• Performance Optimization: Identifies bottlenecks for tuning.
• Real-Time Alerts: Works with Prometheus to send alerts for critical issues.

Best Practices

• Secure Connection Strings: Use environment variables to protect sensitive data.
• Customize Queries: Focus on the most relevant metrics for your workload.
• Regular Updates: Keep PostgreSQL Exporter up to date for new features and fixes.

All PostgreSQL Questions, Answers, and Code Snippets Collection.