In Chapter 4, IT Operational Analytics and Root Cause Analysis, we asked "what percentage of the data that you collect is being paid attention to?" Often, a realistic answer is likely <10% and maybe even <1%. The reason why this is the case is that the traditional approach to making data proactive is to start from scratch and then build up thresholds or rules-based alerts over time. This can be a daunting and/or tedious task that requires upfront knowledge (or at least a guess) as to what the expected behavior of each time series should be. Then, once the alerts have been configured, there can be an extended tuning process that balances alert sensitivity with annoying false positives. Additionally, there could also be metrics whose unusual behaviors could never be caught with a static threshold.
Combine this challenge...
