Migration notes for SignalFx (Splunk) to PromQL

There are several key differences between SignalFx (Splunk) and PromQL of which to be aware when migrating queries to Chronosphere:

Rollups in SignalFx are used to aggregate data points within a single time series. With Chronosphere, rollups are defined only on ingest, and not at query time. However, PromQL offers a set of functions for aggregating individual time series over time.
Analytics in SignalFx are the equivalent to functions in PromQL.

Equivalent function list

SignalFx	PromQL	Notes
Absolute value	`abs()`	none
Bottom	`bottomk()`	none
Ceiling	`ceil()`	none
Count	`count()`, `count_over_time()`	none
Delta	`delta()`	none
EWMA and Double EWMA	`holt_winters()`	`holt_winters()` is similar to, but not exactly like, Exponentially Weighted Moving Average
Exclude	Use comparators	none
Floor	`floor()`	none
Integrate	`rate()`	none
LN - Log (natural)	`ln()`	none
Log10	`log10()`	none
Maximum	`max()`, `max_over_time()`	none
Mean	`avg()`, `avg_over_time()`	none
Minimum	`min()`, `min_over_time()`	none
Percentile	`quantile()`, `quantile_over_time()`	Use histogram_quantile() with Histograms
Power	Use operators	none
Rate of change	`rate()`	none
Scale	Use operators	none
Square root	`sqrt()`	none
Standard deviation	`stddev()`, `stddev_over_time()`	none
Sum	`sum()`, `sum_over_time()`	none
Timeshift	offset	none
Top	`topk()`	none
Variance	`stdvar()`, `stdvar_over_time()`	none