MS SQL Logs Monitoring & Observability

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

Monitor Microsoft SQL Server logs to troubleshoot performance, availability, and security issues

Analyze SQL Server error logs

Inspect SQL Server ERRORLOG entries to identify database engine errors, severity-level failures, startup issues, and unexpected shutdown events.

Detect deadlocks and blocking

Capture deadlock graphs, blocking chain messages, and lock escalation warnings from SQL Server logs to diagnose concurrency issues.

Track query execution failures

Monitor SQL Server log events related to failed queries, transaction rollbacks, arithmetic overflows, and constraint violations affecting workloads.

Monitor availability and failover

Follow SQL Server Always On and failover cluster log messages to detect replica role changes, synchronization issues, and failover events.

Observe backup and restore activity

Track SQL Server backup, restore, and recovery-related log entries to verify job execution and detect failures impacting data protection.

Identify resource pressure warnings

Analyze SQL Server logs for memory pressure, I/O subsystem delays, tempdb contention, and scheduler health warnings.

Monitor authentication and security

Capture SQL Server login failures, permission denials, certificate errors, and encryption-related log entries for security auditing.

Correlate database and application logs

Link SQL Server log events with application logs to trace database-level errors back to specific services or deployment changes.

Core Platform Capabilities

Centralize MSSQL Logs for Fast Investigation and Insight

Forward MSSQL log streams into Atatus so you can parse key fields, explore events in real time, and investigate issues without switching between database servers.

Real-Time Log IngestionStructured ParsingCustom PipelinesSaved ViewsFast Search & Exploration

Logs Scattered Across Servers

MSSQL emits logs on individual database hosts, and without centralized ingestion it becomes difficult to trace patterns across instances.

Unstructured Entries Hide Meaning

Raw MSSQL log messages mix text with execution context, and parsing them into structured fields makes searching by attributes like session ID or error type much easier.

High Volume Buries Relevant Events

Continuous SQL Server log output can overwhelm manual inspection, and filters with custom pipelines help surface only the most relevant entries.

Recreating Filters Slows Troubleshooting

Manually rebuilding search contexts wastes time, and saved views let you persist complex filters and return to them instantly.

Finding Log Patterns Takes Too Long

Grepping log files across nodes is inefficient, and centralized search allows you to locate events by timestamp, attribute, or pattern quickly.

Unified Logs Monitoring & Observability Across Different Platforms

Frequently Asked Questions

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