I am a big fan of data and metrics (.. that is data that we can turn into knowledge and Commander Data from Star Trek). In IT we tend to collect a lot of it, especially as it relates to our infrastructure and reporting it within to our business folks is sometimes a challenge. For one, we tend to report in terms we understand, take for example the following DNS resolution time, TCP connection time, HTTP redirect time and Full page object load time. But do business folks really understand what we are saying?
Its important that our systems and reporting translates those metrics into understandable business language, an intuitive web dashboard that helps both IT and Business understand the impact of a web performance metric. Take for instance a simple dashboard that has a green - yellow - red system, for indicating problems and the metric next to it is a roll-up of different IT data points. Its some much easier to deal with - Web forums from Austin OK rather than process xyz on server-abc is in a not running. Its easier because you know the complete impact of the issue rather than just focusing on one issue and not understanding how its tied to other items.
I think machine learning is going to play an important part in future web performance monitoring applications, as business demands more from IT. Machine learning will help correlate IT and business metrics. Business will want to know more than just if something is down or up, they need metrics delivered in a way that help them understand business impact. BTW - Commander Data would also communicate in terms the Captain and staff would understand after compiling the data.
Are you more concerned about actionable IT metrics and not concerned with the business impact?
What are the metrics that matter to you?
Do you translate IT metrics for the business or do they manage a different set of metrics?
Have your business teams stared asking for more relationship mapping between metrics?
Do you see machine learning as a next phase in matching IT and business metrics?