Sum
A Sum metric represents a value that changes over time by accumulating observations. It can be monotonic, such as a request counter, or non-monotonic, depending on the instrument and exporter.
A Sum metric can be reported with either Delta or Cumulative temporality.
Temporal Aggregation
Section titled “Temporal Aggregation”When you choose a time interval in Explore, KloudMate groups data points into buckets and applies an aggregation inside each bucket.
For Sum metrics, the most useful temporal aggregations are:
- Rate: per-second rate of change
- Increase: absolute increase during the interval
- Sum: total of all delta values within the interval when the metric is reported as Delta
How Rate and Increase Are Calculated
Section titled “How Rate and Increase Are Calculated”For each interval time window, the system evaluates data points differently based on the Sum temporality:
- For Cumulative Sum, the system selects the maximum, typically the last value, inside the time window and compares it with the previous window.
- For Delta Sum, each point already represents a change, so the system sums all values inside the time window.
The system automatically detects the metric temporality and applies the correct internal formula.
Increase
Section titled “Increase”Cumulative:
increase = current_window_value − previous_window_value
Delta:
increase = SUM(all values in the current time window)
Cumulative:
rate = (current_window_value − previous_window_value) / (timestamp_current − timestamp_previous)
Delta:
rate = SUM(all values in current time window) / time interval (seconds)
Where:
current_window_valueis the latest value in the current time window for cumulative sumsprevious_window_valueis the latest value in the previous time window for cumulative sumstimestamp_current - timestamp_previousis measured in seconds
For counter reset handling in cumulative metrics, if the difference between two windows is negative, KloudMate treats it as a reset and sets the computed value to 0.
Spatial Aggregation
Section titled “Spatial Aggregation”Spatial aggregation combines values from multiple time series at the same timestamp or interval bucket. It is applied after temporal aggregation is completed and aggregates across all matching series.
If you select Sum for spatial aggregation without any grouping, KloudMate combines all matching series into one result.