This website uses Cookies. Click Accept to agree to our website's cookie use as described in our Privacy Policy. Click Preferences to customize your cookie settings.
Ingesting logs into Dynatrace is the first step to get answers from your data. But once your log data is flowing in, how do you use it to investigate issues and answer business-critical questions? And when should you look at logs versus other key data sources like metrics or alerts?
In this session for Dev and Ops roles, you will learn:
How to get started with analyzing your log data in Dynatrace
How Davis AI can simplify troubleshooting and reduce MTTR by leveraging log data
When to use Dynatrace metrics vs. log data to improve cost efficiency
Common use cases and best practices for log analysis
Which apps you can use in Dynatrace to analyze your logs in context
Where to learn more about DQL to advance your log analysis skills