SignalFx
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 (opens in a new tab) 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() | |
Bottom | bottomk() | |
Ceiling | ceil() | |
Count | count() , count_over_time() | |
Delta | delta() | |
EWMA and Double EWMA | holt_winters() | holt_winters() is similar to, but not exactly like, Exponentially Weighted Moving Average |
Exclude | Use comparators | |
Floor | floor() | |
Integrate | rate() | |
LN - Log (natural) | ln() | |
Log10 | log10() | |
Maximum | max() , max_over_time() | |
Mean | avg() , avg_over_time() | |
Minimum | min() , min_over_time() | |
Percentile | quantile() , quantile_over_time() | Use histogram_quantile() with Histograms |
Power | Use operators | |
Rate of change | rate() | |
Scale | Use operators | |
Square root | sqrt() | |
Standard deviation | stddev() , stddev_over_time() | |
Sum | sum() , sum_over_time() | |
Timeshift | offset | |
Top | topk() | |
Variance | stdvar() , stdvar_over_time() |