High-performance database monitoring

Database monitoring for business-critical metrics

Gain deep visibility into database health and availability in real-time

Frustrated by CPU, memory, or I/O bottlenecks spiking under peak load or after deployments? Traditional database monitoring often misses the context of why a system is failing. We bridge that gap by tracking:

• Resource saturation: Tired of unexpected crashes? Track CPU, memory, and disk I/O to identify hardware limits before they lead to downtime.
• User sessions and locks: Stop connection leaks and deadlocks from slowing down your app. Monitor active connections and wait times to ensure a smooth end-user experience.
• Buffer and cache health: Avoid expensive disk usage. Monitor hit ratios to ensure your memory is set up for high-speed data retrieval.

 

 

 

Database monitoring for faster slow-query detection

Stop the slow SQL guessing game with deep-dive query analysis

Slow queries and latency spikes can spark endless "DB is slow" complaints. When a query lags, your whole stack suffers. Our database monitoring tool ranks SQL statements by resource consumption so you can fix what matters most:

• Wait state analysis: Pinpoint exactly what is stalling your database. Find out if the issue is a hardware limit, a table lock, or a CPU spike.
• Background task oversight: Ensure that automated backups or indexing do not silently steal resources from your active users.

 

 

 

Full stack database monitoring with application context

Bridge the gap between application code and database execution

End the finger-pointing between developers and DBAs. By integrating APM with database monitoring, you can:

• Map web actions to SQL: See exactly which user action triggered a specific backend call.
• Isolate bottlenecks: Quickly determine if a delay is caused by poor code, network lag, or actual database execution.
• Contextual collaboration: Correlate application traces with database analytics to quickly resolve issues without context switching.

Intelligent root-cause analysis (RCA)

Slash MTTR with automated anomaly detection and proactive alerting

Don't let too many alerts bury real issues. Our database monitoring platform uses machine learning to keep your team focused:

• Dynamic baselines: The system learns your normal behavior. It only alerts you when performance looks unusual, which reduces annoying false alarms.
• Instant notifications: Get actionable alerts via Slack, SMS, or e-mail the moment a limit is reached.
• Automated remediation: Trigger self-healing workflows, such as clearing temp files or restarting services, the instant a problem is detected.

Predictive capacity planning

Prevent resource exhaustion with ML-driven utilization forecasting

Facing storage crises from uncontrolled DB/log growth and no capacity forecasts? Stop reacting to "Disk Full" emergencies. Use database monitoring data to stay ahead of growth:

• Growth projections:Use smart algorithms to predict exactly when you will need to upgrade your hardware or increase your cloud budget.
• Saturation warnings: Identify memory or disk risks weeks before they happen so you can manage data growth without a service break.
• Automated reporting: Schedule PDF or Excel reports to keep stakeholders informed on long-term trends and scaling needs.

Beyond native database monitoring tools

Consolidate your stack to eliminate visibility gaps and manual overhead

Fragmented tools lead to blind spots. By moving to a unified database monitoring approach, you can:

Why choose our agentless database monitoring?