Query Plan Analysis
Analyzes execution plans, index scans, and sequential scans to detect inefficient SQL execution paths.
Operational Logs and Concurrency Analysis
From slow queries and lock contention to replication health and resource utilization, everything you need to optimize PostgreSQL performance.
Challenges
PostgreSQL Database Monitoring
Lock and Wait Events
Tracks row, table, and advisory locks that cause transaction blocking and latency spikes.
Connection Saturation
Monitors active sessions, idle transactions, and max connection limits.
Autovacuum Activity
Observes vacuum frequency, table bloat growth, and dead tuple accumulation.
WAL and Replication Lag
Measures WAL generation rate and replica replay delay affecting data consistency.
Cache Hit Efficiency
Tracks shared buffer cache effectiveness and disk read dependency.
Error Log Monitoring
Captures PostgreSQL errors related to crashes, checkpoints, and replication.
Resource Usage Trends
Analyzes CPU, memory, and disk IO consumption under transactional workloads.
Key Features
Deep Visibility Into PostgreSQL Workloads and Query Execution Behavior
Understand performance across execution plans, transactions, memory, and I/O.
Workload Trends & Query Health
- Track query latency percentiles, throughput, and peak load in real time to understand database performance under live production traffic.
- Identify performance drops during traffic surges, reporting jobs, or heavy batch workloads before they impact users.
- Monitor read and write pressure across schemas and databases to detect imbalance and scaling constraints.
- Measure the impact of tuning actions such as index creation, configuration changes, and query rewrites over time.
Active Queries & Long-Running Sessions
- View currently running SQL statements with execution duration, user context, and application source for full workload visibility.
- Instantly spot runaway queries consuming excessive CPU, memory, and I/O resources.
- Filter active sessions by state, application name, user, or runtime to isolate performance issues quickly.
- Understand real concurrency behavior under production load to prevent blocking and resource saturation.
Execution Plans & Index Effectiveness
- Visualize PostgreSQL execution plans to clearly understand joins, scans, and index access paths used by each query.
- Automatically detect sequential scans slowing down large table queries and driving high I/O consumption.
- Compare estimated versus actual execution cost to uncover planner inaccuracies and optimization opportunities.
- Optimize performance using real execution behavior rather than theoretical plans alone.
Transaction Throughput & Resource Pressure
- Track transaction commit and rollback rates to evaluate workload stability and application behavior.
- Monitor buffer cache hit ratios and disk read pressure to understand memory efficiency and storage load.
- Identify I/O bottlenecks that slow down write-heavy and analytics workloads.
- Maintain consistent database performance during peak concurrency and high transaction volume periods.
Why Atatus
Why choose Atatus for PostgreSQL database monitoring?
01
PostgreSQL execution insights
Analyze query plans, index usage, and sequential scans to spot inefficient execution paths.
02
Lock contention visibility
Monitor row, table, and advisory locks to identify blocking transactions quickly.
03
Autovacuum performance tracking
Track vacuum cycles, dead tuples, and table bloat to keep queries fast.
04
Replication health insights
Monitor WAL generation rates and replica replay lag for synchronization stability.
05
Connection behavior monitoring
Track idle sessions, long-running queries, and connection limits to prevent overload.
06
Full resource correlation
Link database activity with CPU, memory, and disk usage for faster root cause analysis.
Teams
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Debug errors and slow paths with the full context of what happened.
Atatus for developersDevOps
Track deployments and see how each release affects stability.
Atatus for DevOpsRelease engineers
Watch latency and error rates to ship with less production risk.
Atatus for release engineers
FAQ
Frequently Asked Questions
Pricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.
PostgreSQL monitoring involves the systematic observation and analysis of various performance metrics and parameters within a PostgreSQL database. It is crucial for ensuring the optimal performance, availability, and reliability of PostgreSQL instances. Monitoring allows you to detect and address potential issues, optimize resource usage, and maintain the overall health of your PostgreSQL databases, which are fundamental components of many web applications.
Monitoring PostgreSQL with Atatus offers a comprehensive solution for gaining deep insights into the performance of your PostgreSQL databases. Atatus provides real-time visibility, customizable dashboards, and intelligent alerting capabilities, allowing you to proactively manage and optimize PostgreSQL instances. With Atatus, you can ensure high availability, quickly troubleshoot issues, and streamline the performance of your PostgreSQL-powered applications.
Important PostgreSQL metrics to monitor include:
- Query performance metrics (execution time, throughput, etc.)
- InnoDB metrics (buffer pool usage, transactions, etc.)
- Connection statistics (connections, aborted connections, etc.)
- Replication metrics (lag, slave status, etc.)
- Server resource utilization (CPU usage, memory usage, disk I/O)
Atatus supports a wide range of popular databases, including but not limited to MySQL, MS SQL, PostgreSQL, MongoDB, MariaDB, Redis, Memcached, SQLite, and Aerospike. The platform provides integrations and pre-built dashboards tailored to each supported database, allowing users to monitor and analyze their database performance effectively. Whether your application relies on MySQL or a combination of different databases, Atatus provides a unified platform for effective monitoring and optimization.
Atatus provides Query Performance Monitoring, allowing you to identify slow queries, view query plans, and assess overall query performance. With this information, you can optimize queries for better database efficiency.
Yes, Atatus is designed to monitor PostgreSQL databases in both traditional and distributed environments. It supports monitoring across on-premises, cloud, and hybrid infrastructure, providing a unified view of your PostgreSQL performance regardless of the deployment model.
Atatus supports various notification channels, including email, Slack, PagerDuty, and others. You can configure alerting policies with specific thresholds and conditions to receive timely notifications when PostgreSQL metrics deviate from expected values.
Data retention for PostgreSQL monitoring is set to 7 days by default. This can be changed in your billing settings to 60 or 90 days. Contact our Customer Success Representative if you require a longer retention period.