PostgreSQL Logs Monitoring & Observability

Effortlessly track PostgreSQL logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.

Monitor PostgreSQL logs and database activity in production environments

Collect PostgreSQL server logs

Ingest PostgreSQL server log output including errors, warnings, checkpoints, and background writer activity from production databases.

Analyze slow and expensive queries

Inspect PostgreSQL log entries generated by duration thresholds to identify long-running queries and inefficient execution paths.

Track database startup and shutdown

Monitor PostgreSQL startup, recovery, and shutdown logs to diagnose configuration issues and unexpected restarts.

Observe vacuum and autovacuum activity

Capture PostgreSQL vacuum and autovacuum log messages to understand table bloat, cleanup behavior, and maintenance impact.

Detect replication and WAL issues

Analyze PostgreSQL replication and write-ahead logging related messages to identify replication lag and streaming issues.

Monitor connection and authentication failures

Surface PostgreSQL connection attempts, authentication errors, and role permission issues recorded in server logs.

Correlate logs with performance metrics

Link PostgreSQL log events with query timing, connection counts, and resource usage metrics for deeper performance analysis.

Support clustered PostgreSQL setups

Aggregate logs from primary servers, replicas, and high-availability PostgreSQL deployments into a unified view.

Core Platform Capabilities

Centralize PostgreSQL Logs for Real-Time Visibility

Collect, parse, and explore PostgreSQL logs in Atatus so you can understand query behavior, spot patterns, and troubleshoot quickly without switching between servers.

Real-Time Log IngestionStructured ParsingCustom PipelinesSaved ViewsFast Search

Logs Scattered Across Instances

PostgreSQL logs live on individual database hosts and files, and centralizing them in Atatus makes it easier to explore activity across servers in one place.

Unstructured Messages Hide Meaning

Raw PostgreSQL log lines mix text and fields, and structuring them at ingestion makes attributes like timestamps, query text, and severity searchable.

High Volume Obscures Critical Events

Large volumes of PostgreSQL log output can bury important entries, and custom pipelines with filters help surface the logs that matter most.

Without Saved Views, Context Is Lost

Troubleshooting often requires narrowing logs to a specific timeframe or attribute set, and saved views let you restore that context instantly.

Finding Entries by Pattern Is Slow

Manually grepping through PostgreSQL log files is inefficient, and fast centralized search allows you to locate patterns or timing issues quickly.

Unified Logs Monitoring & Observability Across Different Platforms

Frequently Asked Questions

Find answers to common questions about our platform