host db-postgresql1

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text

Lines expression syntax:

lines: - expression: metric(a='b', c='d*', e=['f', 'g*']) #example some load averages: select all metrics with labels matching values; a='b' matches metrics with label a equals fixed string 'b'; c='d*' matches metrics with label c starts with 'd'; e=['f', 'g*'] matches metrics with label e equals fixed string 'f' or starts with 'g'
lines: - expression: rate(EXPR) #example python cpu_user: derivative for each metric in EXPR
lines: - expression: counter_rate(EXPR) #example python cpu_user: derivative for counters – like rate but doesn`t spikes for counter reset
lines: - expression: sum(EXPR [, ignore_nan=True|False]) #example all python's cpu_user and cpu_system: sum of all metrics in EXPR; If ignore_nan=False, then result is NaN if one metric in EXPR was NaN. Default is ignore_nan=True
lines: - expression: max(EXPR) - expression: min(EXPR) - expression: std(EXPR) #standard deviation - expression: average(EXPR) #same as mean - expression: mean(EXPR) #example mean load average: at each time-point take aggregation function for all metrics in EXPR
lines: - expression: sum_by(label_name, [other_label,] EXPR) #example processes cpu usage - expression: max_by(label_name, [other_label,] EXPR) - expression: min_by(label_name, [other_label,] EXPR) - expression: std_by(label_name, [other_label,] EXPR) #standard deviation - expression: mean_by(label_name, [other_label,] EXPR) #same as average - expression: average_by(label_name, [other_label,] EXPR) #example mean load average: group all metrics in EXPR by value of label_name label and aggregate metrics in the same group into one metric; Accepts parametrignore_nan=False|True, just like ordinary sum
lines: - expression: win_sum(window_size_in_seconds, EXPR) - expression: win_mean(window_size_in_seconds, EXPR) #same as win_avg - expression: win_min(window_size_in_seconds, EXPR) - expression: win_max(window_size_in_seconds, EXPR) - expression: win_std(window_size_in_seconds, EXPR) - expression: win_avg(window_size_in_seconds, EXPR) #example mean load average on hour window: Applies specified function sum|mean|min|max|std for each metric in EXPR on moving time window window_size_in_seconds. See Moving average
lines: - expression: cum_sum(EXPR) #example: Cumulative sum for each metric in EXPR.
lines: - expression: top(N, EXPR[, include_other=true|false][, by="exp"|"sum"|"max"]) #example top 5 processes by CPU - expression: bottom(N, EXPR[, by="exp"|"sum"|"max"]): show top|bottom N metrics from EXPR by ews|exp(exponentialy weighted sum) or sum or max in current timespan
lines: - expression: filter_with(EXPR, FILTER_EXPR) #example memory usage of long running processes: filters metrics in EXPR returning only those for which FILTER_EXPR not zero (or NaN).
lines: - expression: const(v[, label="value", ...]) #example: constant metric with value v and additonal labels for legend
lines: - expression: time(): timestamp from x-axis as y-value
lines: - expression: from_string("1,2,3,3,2,1,", [,repeat=false] [,sep=' '] [,label="value", ...]) #example: construct metric from string like "1,2,3,3,2,1,", where each number becomes the value of the metric for corresponding minute
lines: - expression: defined(EXPR) #example all processes: 1 if there is data from EXPR in this time-point or 0 if there is NaN
lines: - expression: replace(old_val, new_val, EXPR) #example - expression: n2z(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: zero_if_none(EXPR) #shortcut for "replace(nan, 0, EXPR)" - expression: z2n(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: zero_if_negative(EXPR) - expression: none_if_zero(EXPR) #shortcut for "replace(0, nan, EXPR)" - expression: remove_below(EXPR, value) - expression: remove_above(EXPR, value) - expression: clamp_min(EXPR, min) - expression: clamp_max(EXPR, max): sets new_val instead of old_val
lines: - expression: sum_by(label, [other_label,] metric(..)) / max_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) * sum_by(label, [other_label,] metric(.)) - expression: sum_by(label, [other_label,] metric(..)) - min_by(label, [other_label,] metric(.)): if labels for bothsum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
lines: - expression: sum_by(label, [other_label,] metric(..)) / EXPR - expression: min_by(label, [other_label,] metric(..)) * EXPR - expression: max_by(label, [other_label,] metric(..)) - EXPR: Applies / EXPR * EXPR or - EXPR for each metric from left XXX_by(label, ...)

Lines legend syntax:

lines: - expression: metric(...) legend: '%s': for each line show all label_name:label_value pairs in legend
lines: - expression: metric(...) legend: '%(label_name)s anything': for each line show `label_value` anything in legend

Colors syntax:

lines: - expression: metric(...) color: '#81ff22' - expression: metric(...) color: 'red': color is color
lines: - expression: metric(...) colors: ['#80AB00', 'red', 'rgb(127,0,20)', 'hsla(100,10%,20%,0.8)']: will cycle through specified colors
lines: - expression: metric(...) colors: /regex.*/: '#fff' /regex2/: 'gold': will match legend to regexes
lines: - expression: metric(...) options: colors: semaphore #OR colors: semaphore inv: will color all, previously uncolored lines, with a gradient from red to green; or from greento red if semaphore inv

Sorting syntax:

lines: - expression: metric(...) options: sort: alpha|num: sort all lines by legend in alphabetical or numeric (default) order
lines: - expression: metric(...) options: sort: ['fixed', 'order', 'for', 'legend', 'items']: fixed sort order by item's legend
lines: - expression: metric(...) options: sort: ... order: DESC: change sort order to descending

Sorting tooltip syntax:

lines: - expression: metric(...) options: tooltip: sort_order: name|-name|value|-value

Sorting lines in tooltip (no sorting by default):

in alphabetical(name | -name).
by values(value | -value)

Captions:

lines: - expression: metric(...) - expression: metric(...) title: 'some %(label_name)s': format chart title with labels from all expressions combined
lines: - expression: metric(...) - expression: metric(...) options: y_title: 'some text': Y-axis vertical title as plain text