It's cheaper for several tools that bill by number of events rather than total volume of data in GB. The way this works with very high volumes of data is to employ smarter sampling to make sure you get as good a ratio of good vs. useless events as possible within a given budget.
Observability in this fashion is much more like real-time analytics (with an appropriate backend, i.e., not a timeseries database), where the cost of querying an event that as 2 fields compared to 200 fields is marginal. And so in a world like this, you're encouraged to pack more information into each log/event/span. There's a lot of details underlying that, like some backends still requiring you to define a subset you'd like to always be able to group by, whereas other backends have no such limitations, but this is largely the category of system that's being talked about.
It's cheaper for several tools that bill by number of events rather than total volume of data in GB. The way this works with very high volumes of data is to employ smarter sampling to make sure you get as good a ratio of good vs. useless events as possible within a given budget.
Observability in this fashion is much more like real-time analytics (with an appropriate backend, i.e., not a timeseries database), where the cost of querying an event that as 2 fields compared to 200 fields is marginal. And so in a world like this, you're encouraged to pack more information into each log/event/span. There's a lot of details underlying that, like some backends still requiring you to define a subset you'd like to always be able to group by, whereas other backends have no such limitations, but this is largely the category of system that's being talked about.