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I'm confused on one point: does the anomaly correlation find other metrics that look "similar" or other metrics that also have anomalies in the same time span

I'm confused on one point: does the anomaly correlation find other metrics that look "similar" or other metrics that also have anomalies in the same time span ? The latter seems like it would be very useful. You mention elsewhere that statsd lets you do complicated aggregations over time. If you have a moving average of errors over 10 minutes or something, that's potentially not going to show up when you do anomaly correlation, since a spike is smeared across 20 minutes. Do you account for that? It would require knowing which metrics are aggregated across time and by how much, etc, I guess.

jonlives 13y ago
Oculus author here - Oculus detects other metrics that look similar, ie that have a simlar anomaly or shape in the same time span. It doesn't pick up metrics that have other, "dissimilar" anomalies - that part is left to Skyline Oculus treats all metrics that it gets from Skyline equally at the moment, ie it doesn't know if what it's looking at is an aggregation, or a single set of data points. It just takes the data as it's presented. It would be totally possible, however, to add 10 and 20 minute averages (for example) for the same metric into Skyline so that Oculus would treat them separately.