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.
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.
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.
Why teams choose Atatus for MS SQL logs monitoring
SQL Server-aware log parsing
Atatus understands SQL Server ERRORLOG and Agent log formats and extracts structured fields such as severity, database name, and error codes.
Centralized log visibility
Collect logs from standalone SQL Server instances, Always On replicas, and clustered environments in a single timeline.
Fast log search and filtering
Filter SQL Server logs by database, login, error number, or severity level to isolate issues quickly.
Real-time alerting
Trigger alerts on critical SQL Server log events such as failovers, deadlocks, backup failures, or repeated login errors.
Accelerated root cause analysis
Correlate SQL Server log anomalies with application errors and infrastructure signals to reduce troubleshooting time.
Scalable log ingestion
Ingest high-volume SQL Server logs reliably during peak workloads, maintenance windows, and recovery operations.
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Trace requests, debug errors, and identify performance issues at the code level with clear context.
DevOps
Track deployments, monitor infrastructure impact, and understand how releases affect application stability.
Release Engineer
Measure service health, latency, and error rates to maintain reliability and reduce production risk.
Unified Logs Monitoring & Observability Across Different Platforms
Frequently Asked Questions
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