Database Anomaly Detection Powered by Machine Learning

Improve database performance by using an anomaly detection tool

Automatically learn about database wait behavior patterns using an anomaly detection tool

When you rely on tribal knowledge, it’s hard for someone new to acquire it. Sometimes, the sheer scale in larger environments prohibits in-depth, broad understanding. Remove the need for tribal knowledge and let the machine learning algorithm in SolarWinds® Database Performance Analyzer (DPA) help automate the “understanding” of normal behavior patterns. Don’t let knowledge walk out the door when a key resource moves on; automate and retain the knowledge to benefit everyone on your team.

The machine learning algorithm in DPA is designed to get smarter over time and improves its predictive accuracy as more data is collected.

Dig deeper into anomaly-based database monitoring by going beyond spikes

Database administrators tend to focus on spikes in database performance. While this can be a good way to zero in on problem behavior, analyzing behavior spikes isn’t the only indicator of performance changes. In fact, performance variability is normal in most production databases and should be expected. Database administrators need a way to account for expected variations and call out anything unexpected.

The smart SQL database anomaly detection in DPA can go beyond spikes to account for expected variations and point out when something unexpected happens. This anomaly detection tool highlights such occurrences, giving you multiple ways to know when things deviate from the norm.

Troubleshoot effectively using an anomaly detection tool designed to alert on significant behavioral changes

Detecting database anomalies is one thing, but since no one stares at a dashboard 24/7, DPA can send alerts when behavior changes are detected. Reduce noise by customizing the sensitivity to a level you’re comfortable with and let DPA do the watching for you.

DPA constantly monitors your database and can send alerts when behavior changes are detected. This anomaly detection tool can let you know when the workload shifts, when maintenance jobs run into business hours, or when other unexpected changes you want to investigate occur.

Leverage the most recent data available for SQL database anomaly detection

A database anomaly detection tool is only as good as the data going into it. DPA offers 24/7, down-to-the-minute anomaly-based monitoring, with a machine learning algorithm designed to offer updated insights. If monitoring stops for more than 30 days, DPA’s algorithm won’t make predictions on stale data. Instead, DPA starts learning from new data, and after three days, it starts making predictions again based on the most current data. This feature helps ensure your anomaly detection efforts are backed by only the most recent, relevant data.

Use a robust anomaly detection tool compatible with multiple database types

As environments become larger and more complex, database administrators need an anomaly detection tool capable of monitoring a wide variety of database types. Database Performance Analyzer offers an anomaly-based database monitoring tool for virtualized, physical, and cloud-based database instances on Windows and Linux servers, in Azure, or as an AWS subscription using one installation. The DPA anomaly detection tool is built to support Oracle, MySQL, Azure SQL Database, Microsoft SQL Server, and more. DPA also features integrated VMware ESXi visualization with VM option.

Get More on Anomaly Detection Tools

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Better optimize your databases with an anomaly detection tool

Database Performance Analyzer

  • Combine a robust anomaly detection tool with easy data drill downs, context setting, and consistent navigation.
  • Use a database anomaly detection tool to see what’s blocked and what’s doing the blocking.
  • Unlock the right data to get the most out of your database with SQL database anomaly detection.

Starts at $1,275

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