Manipulating/aggregating metrics is a giant pain, you have to understand what exactly the implementors though `max` or whatever means and try to match it up to

Manipulating/aggregating metrics is a giant pain, you have to understand what exactly the implementors though `max` or whatever means and try to match it up to what you need. One thing the article doesn’t address is that logs have to be accurate and metrics should be consistent, but not vice versa. If your performance metrics are always 10% out, they’re still perfectly usable (as long as they’re always 10% high or low) to alert on or to compare to metrics from a known-good historical period.