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- 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'
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- expression: rate(EXPR) #example python cpu_user
- derivative for each metric in
EXPR
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- expression: counter_rate(EXPR) #example python cpu_user
- derivative for counters – like
rate but doesn`t spikes for counter reset
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- 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
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- 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
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- 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 parametr
ignore_nan=False|True, just like ordinary sum
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- 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
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- expression: cum_sum(EXPR) #example
- Cumulative sum for each metric in
EXPR.
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- 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
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- 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).
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- expression: const(v[, label="value", ...]) #example
- constant metric with value
v and additonal labels for legend
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- expression: time()
- timestamp from x-axis as y-value
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- 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
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- expression: defined(EXPR) #example all processes
1 if there is data from EXPR in this time-point or 0 if there is NaN
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- 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
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- 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 both
sum_by are the same than it evaluates as / * or - for each pair of metrics (one from left and one from right metric)
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- 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, ...)