Boxplot
A box plot shows the distribution of a metric across time buckets or groups. Use it to spot variability and outliers.
A box plot visualizes the statistical distribution of a metric over time or across groups. It shows how values spread and where outliers occur.
It’s ideal for:
memory usage analysis
latency distribution
detecting outliers
identifying instability or leaks
What a box plot represents
Each box corresponds to one time bucket (for example, a timestamp window) or one group (for example, a pod).
Box: 25th to 75th percentile (IQR)
Middle line: median (P50)
Whiskers: normal min and max
Outlier dots: abnormal values outside the whiskers
Configure a box plot
Use the Plot panel to choose axes, grouping, and display settings.
Box plot options
Use these options to control how the box plot renders.
X-axis
Defines how data is bucketed into boxes.
Typical: timestamp (each box = one time window). Other options: pod, host, service.
Y-axis
Numeric metric to analyze (distribution).
Examples: value, memory_bytes, latency_ms, cpu. Must be numeric.
Group by
Split into multiple distributions per X bucket.
Example: pod gives one box per pod for each time bucket.
Y-axis label
Display label for the Y axis.
Cosmetic only. Example: “Stack Memory (Bytes)”.
Y-axis scale
Scale for Y-axis values.
Linear for most data. Logarithmic for very large ranges.
Reference line
Horizontal threshold line.
Example: 6000000000 to mark a 6 GB limit.
Legend
Show/hide series names and colors.
Useful when Group by is set.
Calculations
Summary stats derived from Y-axis values.
Count, Min, Max, Avg, P50, P90, P95, P99.
Smooth graph
Not used for box plots.
Present for consistency across chart types.
Custom color
Control colors for boxes and outliers.
Often used to differentiate normal vs outlier points.
Apply
Applies changes to the widget.
Changes do not render until you click Apply.
Box plots need enough samples per bucket to be meaningful. If boxes look “flat” or disappear, increase the time range, reduce grouping, or increase bucket size.
When to use a box plot
Use box plots when you care about:
variability and stability over time
spikes and outliers
distribution shifts (median and spread changes)
They work especially well for memory, latency, response size, and CPU metrics.
When not to use a box plot
Avoid box plots when:
You only need a single value (use Counter/Stat/Status)
You need a simple trend line (use Line/Area)
You need a part-to-whole view (use Pie/Disk)
Your buckets have too few samples to form a distribution (use a larger time range or different chart)
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