Apply suggestions from code review

Co-authored-by: Owen Williams <owen-github@ywwg.com>
Signed-off-by: Bartlomiej Plotka <bwplotka@gmail.com>

Author: bwplotka

docs/specs/om/open_metrics_spec_2_0.md

@@ -1434,7 +1434,7 @@ Specific limits run the risk of preventing reasonable use cases, for example whi
 
 On the other hand, an exposition which is too large in some dimension could cause significant performance problems compared to the benefit of the metrics exposed. Thus some guidelines on the size of any single exposition would be useful.
 
-ingestors may choose to impose limits themselves, for in particular to prevent attacks or outages. Still, ingestors need to consider reasonable use cases and try not to disproportionately impact them. If any single value/metric/exposition exceeds such limits then the whole exposition must be [rejected](#failure-modes).
+Ingestors may choose to impose limits themselves, for in particular to prevent attacks or outages. Still, ingestors need to consider reasonable use cases and try not to disproportionately impact them. If any single value/metric/exposition exceeds such limits then the whole exposition must be [rejected](#failure-modes).
 
 In general there are three things which impact the performance of a general purpose monitoring system ingestion time series data: the number of unique time series, the number of samples over time in those series, and the number of unique strings such as metric names, label names, label values, and HELP. ingestors can control how often they ingest, so that aspect does not need further consideration.