Summary
The retail chain at which you work as a data scientist has been experiencing computer performance issues, which seem to be related to virtual machines with high CPU usage and insufficient free space.
You ran KQL queries in Azure Monitor Log Analytics to extract insights about your virtual machines from log data you collected. You applied several techniques in your analysis, including:
- Setting clear analysis goals.
- Examining log data.
- Assessing which KQL operations can help you use your log data to achieve your analysis goals.
Log analysis is critical to managing monitored resources, discovering and responding to problems, and mitigating potential issues. Raw log data contains an overwhelming amount of information that is hard to understand and correlate in meaningful ways without tools like Log Analytics and KQL.
Analyzing log data in Log Analytics using KQL lets you gain crucial insights and manage your IT environment effectively and proactively.