Is there a reason why Datadog has historically won the DevOps persona? Or to phrase the question differently, do you feel like the two products cater to different types of personas within the enterprise at this point?

Datadog has historically been log-focused, starting as a logging platform, which developers prefer because they can sift through logs to diagnose issues. Dynatrace, on the other hand, started from the user experience and worked downwards, with logging as an afterthought. This difference likely influenced developers' preference for a log-first tool versus a user-first tool.

Is there a reason why Datadog has historically won the DevOps persona? Or to phrase the question differently, do you feel like the two products cater to different types of personas within the enterprise at this point?

A real developer might not struggle as much, but it still requires developer intervention to instrument the application, test it, and go through the release cycle to deploy it into production. With Dynatrace, you install the agents in non-production, test them, and simply enable them in production without deploying any new code. This approach is quicker, easier, and involves fewer touchpoints. As you're aware, the less you have to touch your code, the better.