From 23b6826e9989a26e728fe3781e3185b5a79e066c Mon Sep 17 00:00:00 2001 From: Julius Volz Date: Sat, 31 Aug 2024 19:08:08 +0200 Subject: [PATCH] Catch up to all latest PromQL features, enable experimental functions This updates UI and backend dependencies such that PromLens supports the latest PromQL features, such as: * limitk() / limit_ratio() operators * all current experimental functions, such as mad_over_time() and native histogram ones * updated function documentation Signed-off-by: Julius Volz --- app/package-lock.json | 215 +- app/package.json | 16 +- .../ExplainViews/Aggregation.tsx | 5 + .../NodeEditor/AggregationEditor.tsx | 7 +- app/src/promql/ast.ts | 2 + app/src/promql/cmd/gen_functions_docs/main.go | 1 + app/src/promql/functionDocs.tsx | 766 ++++++- app/src/promql/functionSignatures.ts | 25 + app/src/promql/utils.ts | 5 +- cmd/promlens/main.go | 7 +- go.mod | 107 +- go.sum | 1948 ++--------------- pkg/web/web.go | 2 +- 13 files changed, 1082 insertions(+), 2024 deletions(-) diff --git a/app/package-lock.json b/app/package-lock.json index 052538a..cad91bc 100644 --- a/app/package-lock.json +++ b/app/package-lock.json @@ -8,17 +8,17 @@ "name": "app", "version": "0.1.0", "dependencies": { - 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"@codemirror/view": "^6.6.0", + "@codemirror/view": "^6.17.0", "@lezer/common": "^1.0.0" }, "peerDependencies": { @@ -1906,33 +1907,36 @@ } }, "node_modules/@codemirror/commands": { - "version": "6.2.4", - "resolved": "https://registry.npmjs.org/@codemirror/commands/-/commands-6.2.4.tgz", - "integrity": "sha512-42lmDqVH0ttfilLShReLXsDfASKLXzfyC36bzwcqzox9PlHulMcsUOfHXNo2X2aFMVNUoQ7j+d4q5bnfseYoOA==", + "version": "6.6.1", + "resolved": "https://registry.npmjs.org/@codemirror/commands/-/commands-6.6.1.tgz", + "integrity": "sha512-iBfKbyIoXS1FGdsKcZmnrxmbc8VcbMrSgD7AVrsnX+WyAYjmUDWvE93dt5D874qS4CCVu4O1JpbagHdXbbLiOw==", + "license": "MIT", "dependencies": { "@codemirror/language": "^6.0.0", - "@codemirror/state": "^6.2.0", - "@codemirror/view": "^6.0.0", - "@lezer/common": "^1.0.0" + "@codemirror/state": "^6.4.0", + "@codemirror/view": "^6.27.0", + "@lezer/common": "^1.1.0" } }, "node_modules/@codemirror/language": { - "version": "6.3.0", - "resolved": "https://registry.npmjs.org/@codemirror/language/-/language-6.3.0.tgz", - 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"resolved": "https://registry.npmjs.org/style-mod/-/style-mod-4.0.0.tgz", - "integrity": "sha512-OPhtyEjyyN9x3nhPsu76f52yUGXiZcgvsrFVtvTkyGRQJ0XK+GPc6ov1z+lRpbeabka+MYEQxOYRnt5nF30aMw==" + "version": "4.1.2", + "resolved": "https://registry.npmjs.org/style-mod/-/style-mod-4.1.2.tgz", + "integrity": "sha512-wnD1HyVqpJUI2+eKZ+eo1UwghftP6yuFheBqqe+bWCotBjC2K1YnteJILRMs3SM4V/0dLEW1SC27MWP5y+mwmw==" }, "stylehacks": { "version": "4.0.3", diff --git a/app/package.json b/app/package.json index 7ab49ee..720579f 100644 --- a/app/package.json +++ b/app/package.json @@ -3,17 +3,17 @@ "version": "0.1.0", "private": true, "dependencies": { - "@codemirror/autocomplete": "^6.3.0", - "@codemirror/commands": "^6.2.4", - "@codemirror/language": "^6.2.1", - "@codemirror/lint": "^6.0.0", - "@codemirror/search": "^6.2.1", - "@codemirror/state": "^6.1.4", - "@codemirror/view": "^6.3.1", + "@codemirror/autocomplete": "^6.18.0", + "@codemirror/commands": "^6.6.1", + "@codemirror/language": "^6.10.2", + "@codemirror/lint": "^6.8.1", + "@codemirror/search": "^6.5.6", + "@codemirror/state": "^6.4.1", + "@codemirror/view": "^6.33.0", "@fortawesome/fontawesome-svg-core": "^1.2.34", "@fortawesome/free-solid-svg-icons": "^5.15.2", "@lezer/highlight": "^1.1.4", - "@prometheus-io/codemirror-promql": "^0.42.0", + "@prometheus-io/codemirror-promql": "^0.54.1", "bootstrap": "^4.5.3", "flot": "^4.2.1", "fuzzy": "^0.1.3", diff --git a/app/src/PromLens/NodeVisualizer/ExplainViews/Aggregation.tsx b/app/src/PromLens/NodeVisualizer/ExplainViews/Aggregation.tsx index 59a7579..ca1bf10 100644 --- a/app/src/PromLens/NodeVisualizer/ExplainViews/Aggregation.tsx +++ b/app/src/PromLens/NodeVisualizer/ExplainViews/Aggregation.tsx @@ -49,6 +49,11 @@ const describeAggregationType = (aggrType: aggregationType, param: ASTNode | nul }th percentile) over the sample values of the input series`; } return 'calculates a quantile over the sample values of the input series'; + + case 'limitk': + return 'limits the output to K series'; + case 'limit_ratio': + return 'limits the output to a ratio of the input series'; default: throw new Error(`invalid aggregation type ${aggrType}`); } diff --git a/app/src/PromLens/QueryList/QueryView/NodeEditor/AggregationEditor.tsx b/app/src/PromLens/QueryList/QueryView/NodeEditor/AggregationEditor.tsx index cbfa9d4..f174312 100644 --- a/app/src/PromLens/QueryList/QueryView/NodeEditor/AggregationEditor.tsx +++ b/app/src/PromLens/QueryList/QueryView/NodeEditor/AggregationEditor.tsx @@ -16,10 +16,13 @@ const AggregationEditor: FC = ({ node, onUpdate }) => { const changeOp = (newOp: aggregationType) => { let param: ASTNode | null = null; - // Keeping the param argument only makes sense when switching between bottomk/topk. - if (['topk', 'bottomk'].includes(node.op) && ['topk', 'bottomk'].includes(newOp)) { + + // Keeping the param argument only makes sense when switching between bottomk/topk/limitk. + const kOps = ['topk', 'bottomk', 'limitk']; + if (kOps.includes(node.op) && kOps.includes(newOp)) { param = node.param; } + if (!aggregatorsWithParam.includes(node.op) && aggregatorsWithParam.includes(newOp)) { param = { type: nodeType.placeholder, children: [] }; } diff --git a/app/src/promql/ast.ts b/app/src/promql/ast.ts index 9d5bfd0..be51866 100644 --- a/app/src/promql/ast.ts +++ b/app/src/promql/ast.ts @@ -25,6 +25,8 @@ export enum aggregationType { bottomk = 'bottomk', topk = 'topk', quantile = 'quantile', + limitK = 'limitk', + limitRatio = 'limit_ratio', } export enum binaryOperatorType { diff --git a/app/src/promql/cmd/gen_functions_docs/main.go b/app/src/promql/cmd/gen_functions_docs/main.go index a5cd579..89545c1 100644 --- a/app/src/promql/cmd/gen_functions_docs/main.go +++ b/app/src/promql/cmd/gen_functions_docs/main.go @@ -57,6 +57,7 @@ func main() { "stdvar_over_time", "last_over_time", "present_over_time", + "mad_over_time", } { funcDocs[fn] = currentDocs } diff --git a/app/src/promql/functionDocs.tsx b/app/src/promql/functionDocs.tsx index 93d7fb0..36c081e 100644 --- a/app/src/promql/functionDocs.tsx +++ b/app/src/promql/functionDocs.tsx @@ -11,8 +11,8 @@ const funcDocs: Record = { absent: ( <>

- absent(v instant-vector) returns an empty vector if the vector passed to it has any elements and a - 1-element vector with the value 1 if the vector passed to it has no elements. + absent(v instant-vector) returns an empty vector if the vector passed to it has any elements (floats or + native histograms) and a 1-element vector with the value 1 if the vector passed to it has no elements.

This is useful for alerting on when no time series exist for a given metric name and label combination.

@@ -36,7 +36,8 @@ const funcDocs: Record = { <>

absent_over_time(v range-vector) returns an empty vector if the range vector passed to it has any - elements and a 1-element vector with the value 1 if the range vector passed to it has no elements. + elements (floats or native histograms) and a 1-element vector with the value 1 if the range vector passed to it has + no elements.

@@ -124,6 +125,9 @@ const funcDocs: Record = {

  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -191,6 +195,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -258,6 +265,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -325,6 +335,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -392,6 +405,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -459,6 +475,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -498,25 +517,57 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), ceil: ( <>

    ceil(v instant-vector) rounds the sample values of all elements in v up to the nearest - integer. + integer value greater than or equal to v.

    + +
      +
    • + ceil(+Inf) = +Inf +
      • +
    • + ceil(±0) = ±0 +
      • +
    • + ceil(1.49) = 2.0 +
      • +
    • + ceil(1.78) = 2.0 +
      • +
    ), changes: ( @@ -535,10 +586,16 @@ const funcDocs: Record = { limit of max.

    -

    - Special cases: - Return an empty vector if min > max- Return NaN if min or{' '} - max is NaN -

    +

    Special cases:

    + +
      +
    • + Return an empty vector if min > max +
      • +
    • + Return NaN if min or max is NaN +
      • +
    ), clamp_max: ( @@ -621,6 +678,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -688,6 +748,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -727,17 +790,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), day_of_month: ( @@ -756,6 +836,14 @@ const funcDocs: Record = {

    ), + day_of_year: ( + <> +

    + day_of_year(v=vector(time()) instant-vector) returns the day of the year for each of the given times in + UTC. Returned values are from 1 to 365 for non-leap years, and 1 to 366 in leap years. +

    + + ), days_in_month: ( <>

    @@ -828,6 +916,9 @@ const funcDocs: Record = {

  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -849,7 +940,15 @@ const funcDocs: Record = {

    - delta should only be used with gauges. + delta acts on native histograms by calculating a new histogram where each component (sum and count of + observations, buckets) is the difference between the respective component in the first and last native histogram in + v. However, each element in v that contains a mix of float and native histogram samples + within the range, will be missing from the result vector. +

    + +

    + delta should only be used with gauges and native histograms where the components behave like gauges + (so-called gauge histograms).

    ), @@ -858,6 +957,8 @@ const funcDocs: Record = {

    deriv(v range-vector) calculates the per-second derivative of the time series in a range vector{' '} v, using simple linear regression. + The range vector must have at least two samples in order to perform the calculation. When +Inf or + -Inf are found in the range vector, the slope and offset value calculated will be NaN.

    @@ -886,70 +987,293 @@ const funcDocs: Record = { <>

    floor(v instant-vector) rounds the sample values of all elements in v down to the nearest - integer. + integer value smaller than or equal to v. +

    + +
      +
    • + floor(+Inf) = +Inf +
      • +
    • + floor(±0) = ±0 +
      • +
    • + floor(1.49) = 1.0 +
      • +
    • + floor(1.78) = 1.0 +
      • +
    + + ), + histogram_avg: ( + <> +

    + + This function only acts on native histograms, which are an experimental feature. The behavior of this function may + change in future versions of Prometheus, including its removal from PromQL. + +

    + +

    + histogram_avg(v instant-vector) returns the arithmetic average of observed values stored in a native + histogram. Samples that are not native histograms are ignored and do not show up in the returned vector. +

    + +

    + Use histogram_avg as demonstrated below to compute the average request duration over a 5-minute window + from a native histogram: +

    + + 
    +        histogram_avg(rate(http_request_duration_seconds[5m]))
+
    + +

    Which is equivalent to the following query:

    + + 
    +        
+          {' '}
+          histogram_sum(rate(http_request_duration_seconds[5m])) / histogram_count(rate(http_request_duration_seconds[5m]))
+        
+
    + + ), + 'histogram_count()` and `histogram_sum': ( + <> +

    + + Both functions only act on native histograms, which are an experimental feature. The behavior of these functions + may change in future versions of Prometheus, including their removal from PromQL. + +

    + +

    + histogram_count(v instant-vector) returns the count of observations stored in a native histogram. + Samples that are not native histograms are ignored and do not show up in the returned vector. +

    + +

    + Similarly, histogram_sum(v instant-vector) returns the sum of observations stored in a native histogram. +

    + +

    + Use histogram_count in the following way to calculate a rate of observations (in this case corresponding + to “requests per second”) from a native histogram: +

    + + 
    +        histogram_count(rate(http_request_duration_seconds[10m]))
+
    + + ), + histogram_fraction: ( + <> +

    + + This function only acts on native histograms, which are an experimental feature. The behavior of this function may + change in future versions of Prometheus, including its removal from PromQL. + +

    + +

    + For a native histogram, histogram_fraction(lower scalar, upper scalar, v instant-vector) returns the + estimated fraction of observations between the provided lower and upper values. Samples that are not native + histograms are ignored and do not show up in the returned vector. +

    + +

    + For example, the following expression calculates the fraction of HTTP requests over the last hour that took 200ms or + less: +

    + + 
    +        histogram_fraction(0, 0.2, rate(http_request_duration_seconds[1h]))
+
    + +

    + The error of the estimation depends on the resolution of the underlying native histogram and how closely the provided + boundaries are aligned with the bucket boundaries in the histogram. +

    + +

    + +Inf and -Inf are valid boundary values. For example, if the histogram in the expression + above included negative observations (which shouldn’t be the case for request durations), the appropriate lower + boundary to include all observations less than or equal 0.2 would be -Inf rather than 0. +

    + +

    + Whether the provided boundaries are inclusive or exclusive is only relevant if the provided boundaries are precisely + aligned with bucket boundaries in the underlying native histogram. In this case, the behavior depends on the schema + definition of the histogram. The currently supported schemas all feature inclusive upper boundaries and exclusive + lower boundaries for positive values (and vice versa for negative values). Without a precise alignment of boundaries, + the function uses linear interpolation to estimate the fraction. With the resulting uncertainty, it becomes + irrelevant if the boundaries are inclusive or exclusive.

    ), histogram_quantile: ( <>

    - histogram_quantile(φ scalar, b instant-vector) calculates the φ-quantile (0 ≤ φ ≤ 1) from the buckets{' '} - b of ahistogram. (See - histograms and summaries for a detailed explanation of - φ-quantiles and the usage of the histogram metric type in general.) The samples in b are the counts of - observations in each bucket. Each sample must have a label le where the label value denotes the - inclusive upper bound of the bucket. (Samples without such a label are silently ignored.) The{' '} + histogram_quantile(φ scalar, b instant-vector) calculates the φ-quantile (0 ≤ φ ≤ 1) from a{' '} + classic histogram or from a native + histogram. (See histograms and summaries for a detailed + explanation of φ-quantiles and the usage of the (classic) histogram metric type in general.) +

    + +

    + + Note that native histograms are an experimental feature. The behavior of this function when dealing with native + histograms may change in future versions of Prometheus. + +

    + +

    + The float samples in b are considered the counts of observations in each bucket of one or more classic + histograms. Each float sample must have a label + le where the label value denotes the inclusive upper bound of the bucket. (Float samples without such a + label are silently ignored.) The other labels and the metric name are used to identify the buckets belonging to each + classic histogram. The{' '} histogram metric type automatically provides time series with the _bucket suffix and the appropriate labels.

    +

    + The native histogram samples in b are treated each individually as a separate histogram to calculate the + quantile from. +

    + +

    + As long as no naming collisions arise, b may contain a mix of classic and native histograms. +

    +

    Use the rate() function to specify the time window for the quantile calculation.

    - Example: A histogram metric is called http_request_duration_seconds. To calculate the 90th percentile of - request durations over the last 10m, use the following expression: + Example: A histogram metric is called http_request_duration_seconds (and therefore the metric name for + the buckets of a classic histogram is + http_request_duration_seconds_bucket). To calculate the 90th percentile of request durations over the + last 10m, use the following expression in case + http_request_duration_seconds is a classic histogram: 

             histogram_quantile(0.9, rate(http_request_duration_seconds_bucket[10m]))
    +

    For a native histogram, use the following expression instead:

    + + 
    +        histogram_quantile(0.9, rate(http_request_duration_seconds[10m]))
+
    +

    The quantile is calculated for each label combination in http_request_duration_seconds. To aggregate, use the sum() aggregator around the{' '} rate() function. Since the le label is required by - histogram_quantile(), it has to be included in the by clause. The following expression - aggregates the 90th percentile by job: + histogram_quantile() to deal with classic histograms, it has to be included in the by{' '} + clause. The following expression aggregates the 90th percentile by job for classic histograms: 

             histogram_quantile(0.9, sum by (job, le) (rate(http_request_duration_seconds_bucket[10m])))
    +

    When aggregating native histograms, the expression simplifies to:

    + + 
    +        histogram_quantile(0.9, sum by (job) (rate(http_request_duration_seconds[10m])))
+
    +

    - To aggregate everything, specify only the le label: + To aggregate all classic histograms, specify only the le label: 

             histogram_quantile(0.9, sum by (le) (rate(http_request_duration_seconds_bucket[10m])))
    +

    + With native histograms, aggregating everything works as usual without any by clause: +

    + + 
    +        histogram_quantile(0.9, sum(rate(http_request_duration_seconds[10m])))
+
    +

    The histogram_quantile() function interpolates quantile values by assuming a linear distribution within - a bucket. The highest bucket must have an upper bound of +Inf. (Otherwise, NaN is - returned.) If a quantile is located in the highest bucket, the upper bound of the second highest bucket is returned. - A lower limit of the lowest bucket is assumed to be 0 if the upper bound of that bucket is greater than 0. In that - case, the usual linear interpolation is applied within that bucket. Otherwise, the upper bound of the lowest bucket - is returned for quantiles located in the lowest bucket. + a bucket. +

    + +

    + If b has 0 observations, NaN is returned. For φ < 0, -Inf is returned. For + φ > 1, +Inf is returned. For φ = NaN, NaN is returned. +

    + +

    + The following is only relevant for classic histograms: If b contains fewer than two buckets,{' '} + NaN is returned. The highest bucket must have an upper bound of +Inf. (Otherwise,{' '} + NaN is returned.) If a quantile is located in the highest bucket, the upper bound of the second highest + bucket is returned. A lower limit of the lowest bucket is assumed to be 0 if the upper bound of that bucket is + greater than 0. In that case, the usual linear interpolation is applied within that bucket. Otherwise, the upper + bound of the lowest bucket is returned for quantiles located in the lowest bucket. +

    + +

    + You can use histogram_quantile(0, v instant-vector) to get the estimated minimum value stored in a + histogram.

    - If b has 0 observations, NaN is returned. If b contains fewer than two - buckets, - NaN is returned. For φ < 0, -Inf is returned. For φ > 1, +Inf is - returned. + You can use histogram_quantile(1, v instant-vector) to get the estimated maximum value stored in a + histogram. +

    + +

    Buckets of classic histograms are cumulative. Therefore, the following should always be the case:

    + +
      +
    • The counts in the buckets are monotonically increasing (strictly non-decreasing).
      • +
    • + A lack of observations between the upper limits of two consecutive buckets results in equal counts in those two + buckets. +
      • +
    + +

    + However, floating point precision issues (e.g. small discrepancies introduced by computing of buckets with{' '} + sum(rate(...))) or invalid data might violate these assumptions. In that case, + histogram_quantile would be unable to return meaningful results. To mitigate the issue, + histogram_quantile assumes that tiny relative differences between consecutive buckets are happening + because of floating point precision errors and ignores them. (The threshold to ignore a difference between two + buckets is a trillionth (1e-12) of the sum of both buckets.) Furthermore, if there are non-monotonic bucket counts + even after this adjustment, they are increased to the value of the previous buckets to enforce monotonicity. The + latter is evidence for an actual issue with the input data and is therefore flagged with an informational annotation + reading input to histogram_quantile needed to be fixed for monotonicity. If you encounter this + annotation, you should find and remove the source of the invalid data. +

    + + ), + 'histogram_stddev()` and `histogram_stdvar': ( + <> +

    + + Both functions only act on native histograms, which are an experimental feature. The behavior of these functions + may change in future versions of Prometheus, including their removal from PromQL. + +

    + +

    + histogram_stddev(v instant-vector) returns the estimated standard deviation of observations in a native + histogram, based on the geometric mean of the buckets where the observations lie. Samples that are not native + histograms are ignored and do not show up in the returned vector. +

    + +

    + Similarly, histogram_stdvar(v instant-vector) returns the estimated standard variance of observations in + a native histogram.

    ), @@ -1008,9 +1332,17 @@ const funcDocs: Record = {

    - increase should only be used with counters. It is syntactic sugar for rate(v) multiplied by - the number of seconds under the specified time range window, and should be used primarily for human readability. Use{' '} - rate in recording rules so that increases are tracked consistently on a per-second basis. + increase acts on native histograms by calculating a new histogram where each component (sum and count of + observations, buckets) is the increase between the respective component in the first and last native histogram in + v. However, each element in v that contains a mix of float and native histogram samples + within the range, will be missing from the result vector. +

    + +

    + increase should only be used with counters and native histograms where the components behave like + counters. It is syntactic sugar for rate(v) multiplied by the number of seconds under the specified time + range window, and should be used primarily for human readability. Use rate in recording rules so that + increases are tracked consistently on a per-second basis.

    ), @@ -1059,6 +1391,10 @@ const funcDocs: Record = { value. There can be any number of src_labels in this function.

    +

    + label_join acts on float and histogram samples in the same way. +

    +

    This example will return a vector with each time series having a foo label with the value{' '} a,b,c added to it: @@ -1077,11 +1413,16 @@ const funcDocs: Record = {

    For each timeseries in v,{' '} label_replace(v instant-vector, dst_label string, replacement string, src_label string, regex string) - matches the regular expression regex against the value of the label src_label. If it - matches, the value of the label dst_label in the returned timeseries will be the expansion of{' '} - replacement, together with the original labels in the input. Capturing groups in the regular expression - can be referenced with $1, $2, etc. If the regular expression doesn’t match then the - timeseries is returned unchanged. + matches the regular expression regex against the + value of the label src_label. If it matches, the value of the label dst_label in the + returned timeseries will be the expansion of replacement, together with the original labels in the + input. Capturing groups in the regular expression can be referenced with $1, $2, etc. Named + capturing groups in the regular expression can be referenced with $name (where name is the + capturing group name). If the regular expression doesn’t match then the timeseries is returned unchanged. +

    + +

    + label_replace acts on float and histogram samples in the same way.

    @@ -1095,6 +1436,15 @@ const funcDocs: Record = { "service", "(.*):.*") + +

    This second example has the same effect than the first example, and illustrates use of named capturing groups:

    + + 
    +        
+          label_replace(up{'{'}job="api-server",service="a:c"{'}'}, "foo", "$name",
+          "service", "(?P<name>.*):(?P<version>.*)")
+        
+
    ), last_over_time: ( @@ -1133,17 +1483,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), ln: ( @@ -1185,6 +1552,72 @@ const funcDocs: Record = {

    ), + mad_over_time: ( + <> +

    + The following functions allow aggregating each series of a given range vector over time and return an instant vector + with per-series aggregation results: +

    + +
      +
    • + avg_over_time(range-vector): the average value of all points in the specified interval. +
      • +
    • + min_over_time(range-vector): the minimum value of all points in the specified interval. +
      • +
    • + max_over_time(range-vector): the maximum value of all points in the specified interval. +
      • +
    • + sum_over_time(range-vector): the sum of all values in the specified interval. +
      • +
    • + count_over_time(range-vector): the count of all values in the specified interval. +
      • +
    • + quantile_over_time(scalar, range-vector): the φ-quantile (0 ≤ φ ≤ 1) of the values in the specified + interval. +
      • +
    • + stddev_over_time(range-vector): the population standard deviation of the values in the specified + interval. +
      • +
    • + stdvar_over_time(range-vector): the population standard variance of the values in the specified + interval. +
      • +
    • + last_over_time(range-vector): the most recent point value in the specified interval. +
      • +
    • + present_over_time(range-vector): the value 1 for any series in the specified interval. +
      • +
    + +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    + +

    + Note that all values in the specified interval have the same weight in the aggregation even if the values are not + equally spaced throughout the interval. +

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    + + ), max_over_time: ( <>

    @@ -1221,17 +1654,34 @@ const funcDocs: Record = { interval.

  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), min_over_time: ( @@ -1270,17 +1720,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), minute: ( @@ -1363,6 +1830,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -1371,7 +1841,9 @@ const funcDocs: Record = {

    predict_linear(v range-vector, t scalar) predicts the value of time series t seconds from now, based on the range vector v, using{' '} - simple linear regression. + simple linear regression. The range vector must + have at least two samples in order to perform the calculation. When +Inf or -Inf are found + in the range vector, the slope and offset value calculated will be NaN.

    @@ -1415,17 +1887,34 @@ const funcDocs: Record = { interval.

  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), quantile_over_time: ( @@ -1464,17 +1953,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), rad: ( @@ -1541,6 +2047,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -1565,8 +2074,16 @@ const funcDocs: Record = {

    - rate should only be used with counters. It is best suited for alerting, and for graphing of slow-moving - counters. + rate acts on native histograms by calculating a new histogram where each component (sum and count of + observations, buckets) is the rate of increase between the respective component in the first and last native + histogram in + v. However, each element in v that contains a mix of float and native histogram samples + within the range, will be missing from the result vector. +

    + +

    + rate should only be used with counters and native histograms where the components behave like counters. + It is best suited for alerting, and for graphing of slow-moving counters.

    @@ -1580,12 +2097,22 @@ const funcDocs: Record = { <>

    For each input time series, resets(v range-vector) returns the number of counter resets within the - provided time range as an instant vector. Any decrease in the value between two consecutive samples is interpreted as - a counter reset. + provided time range as an instant vector. Any decrease in the value between two consecutive float samples is + interpreted as a counter reset. A reset in a native histogram is detected in a more complex way: Any decrease in any + bucket, including the zero bucket, or in the count of observation constitutes a counter reset, but also the + disappearance of any previously populated bucket, an increase in bucket resolution, or a decrease of the zero-bucket + width. +

    + +

    + resets should only be used with counters and counter-like native histograms.

    - resets should only be used with counters. + If the range vector contains a mix of float and histogram samples for the same series, counter resets are detected + separately and their numbers added up. The change from a float to a histogram sample is not considered a + counter reset. Each float sample is compared to the next float sample, and each histogram is comprared to the next + histogram.

    ), @@ -1679,6 +2206,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -1746,13 +2276,71 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), sort: ( <>

    - sort(v instant-vector) returns vector elements sorted by their sample values, in ascending order. + sort(v instant-vector) returns vector elements sorted by their sample values, in ascending order. Native + histograms are sorted by their sum of observations. +

    + +

    + Please note that sort only affects the results of instant queries, as range query results always have a + fixed output ordering. +

    + + ), + sort_by_label: ( + <> +

    + + This function has to be enabled via the{' '} + feature flag{' '} + --enable-feature=promql-experimental-functions. + +

    + +

    + sort_by_label(v instant-vector, label string, ...) returns vector elements sorted by the values of the + given labels in ascending order. In case these label values are equal, elements are sorted by their full label sets. +

    + +

    + Please note that the sort by label functions only affect the results of instant queries, as range query results + always have a fixed output ordering. +

    + +

    + This function uses natural sort order. +

    + + ), + sort_by_label_desc: ( + <> +

    + + This function has to be enabled via the{' '} + feature flag{' '} + --enable-feature=promql-experimental-functions. + +

    + +

    + Same as sort_by_label, but sorts in descending order. +

    + +

    + Please note that the sort by label functions only affect the results of instant queries, as range query results + always have a fixed output ordering. +

    + +

    + This function uses natural sort order.

    ), @@ -1761,6 +2349,11 @@ const funcDocs: Record = {

    Same as sort, but sorts in descending order.

    + +

    + Like sort, sort_desc only affects the results of instant queries, as range query results + always have a fixed output ordering. +

    ), sqrt: ( @@ -1806,17 +2399,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), stdvar_over_time: ( @@ -1855,17 +2465,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), sum_over_time: ( @@ -1904,17 +2531,34 @@ const funcDocs: Record = { interval.
  • - last_over_time(range-vector): the most recent point value in specified interval. + last_over_time(range-vector): the most recent point value in the specified interval.
  • present_over_time(range-vector): the value 1 for any series in the specified interval.
    • +

    + If the feature flag + --enable-feature=promql-experimental-functions is set, the following additional functions are available: +

    + +
      +
    • + mad_over_time(range-vector): the median absolute deviation of all points in the specified interval. +
      • +
    +

    Note that all values in the specified interval have the same weight in the aggregation even if the values are not equally spaced throughout the interval.

    + +

    + avg_over_time, sum_over_time, count_over_time, last_over_time, + and + present_over_time handle native histograms as expected. All other functions ignore histogram samples. +

    ), tan: ( @@ -1981,6 +2625,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -2048,6 +2695,9 @@ const funcDocs: Record = {
  • pi(): returns pi.
    • +
  • + rad(v instant-vector): converts degrees to radians for all elements in v. +
    • ), @@ -2063,11 +2713,7 @@ const funcDocs: Record = { <>

    timestamp(v instant-vector) returns the timestamp of each of the samples of the given vector as the - number of seconds since January 1, 1970 UTC. -

    - -

    - This function was added in Prometheus 2.0 + number of seconds since January 1, 1970 UTC. It also works with histogram samples.

    ), diff --git a/app/src/promql/functionSignatures.ts b/app/src/promql/functionSignatures.ts index 192c16e..9f5b617 100644 --- a/app/src/promql/functionSignatures.ts +++ b/app/src/promql/functionSignatures.ts @@ -36,18 +36,30 @@ export const functionSignatures: Record = { count_over_time: { name: 'count_over_time', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, day_of_month: { name: 'day_of_month', argTypes: [valueType.vector], variadic: 1, returnType: valueType.vector }, day_of_week: { name: 'day_of_week', argTypes: [valueType.vector], variadic: 1, returnType: valueType.vector }, + day_of_year: { name: 'day_of_year', argTypes: [valueType.vector], variadic: 1, returnType: valueType.vector }, days_in_month: { name: 'days_in_month', argTypes: [valueType.vector], variadic: 1, returnType: valueType.vector }, deg: { name: 'deg', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, delta: { name: 'delta', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, deriv: { name: 'deriv', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, exp: { name: 'exp', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, floor: { name: 'floor', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + histogram_avg: { name: 'histogram_avg', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + histogram_count: { name: 'histogram_count', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + histogram_fraction: { + name: 'histogram_fraction', + argTypes: [valueType.scalar, valueType.scalar, valueType.vector], + variadic: 0, + returnType: valueType.vector, + }, histogram_quantile: { name: 'histogram_quantile', argTypes: [valueType.scalar, valueType.vector], variadic: 0, returnType: valueType.vector, }, + histogram_stddev: { name: 'histogram_stddev', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + histogram_stdvar: { name: 'histogram_stdvar', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + histogram_sum: { name: 'histogram_sum', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, holt_winters: { name: 'holt_winters', argTypes: [valueType.matrix, valueType.scalar, valueType.scalar], @@ -74,6 +86,7 @@ export const functionSignatures: Record = { ln: { name: 'ln', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, log10: { name: 'log10', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, log2: { name: 'log2', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + mad_over_time: { name: 'mad_over_time', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, max_over_time: { name: 'max_over_time', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, min_over_time: { name: 'min_over_time', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, minute: { name: 'minute', argTypes: [valueType.vector], variadic: 1, returnType: valueType.vector }, @@ -101,6 +114,18 @@ export const functionSignatures: Record = { sin: { name: 'sin', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, sinh: { name: 'sinh', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, sort: { name: 'sort', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, + sort_by_label: { + name: 'sort_by_label', + argTypes: [valueType.vector, valueType.string], + variadic: -1, + returnType: valueType.vector, + }, + sort_by_label_desc: { + name: 'sort_by_label_desc', + argTypes: [valueType.vector, valueType.string], + variadic: -1, + returnType: valueType.vector, + }, sort_desc: { name: 'sort_desc', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, sqrt: { name: 'sqrt', argTypes: [valueType.vector], variadic: 0, returnType: valueType.vector }, stddev_over_time: { name: 'stddev_over_time', argTypes: [valueType.matrix], variadic: 0, returnType: valueType.vector }, diff --git a/app/src/promql/utils.ts b/app/src/promql/utils.ts index 5e59c3d..a0308b0 100644 --- a/app/src/promql/utils.ts +++ b/app/src/promql/utils.ts @@ -146,11 +146,14 @@ export const childDescription = (node: ASTNode, idx: number): string => { switch (node.op) { case 'topk': case 'bottomk': + case 'limitk': return 'k'; case 'quantile': return 'quantile'; case 'count_values': return 'target label name'; + case 'limit_ratio': + return 'ratio'; } } @@ -176,7 +179,7 @@ export const childDescription = (node: ASTNode, idx: number): string => { } }; -export const aggregatorsWithParam = ['topk', 'bottomk', 'quantile', 'count_values']; +export const aggregatorsWithParam = ['topk', 'bottomk', 'quantile', 'count_values', 'limitk', 'limit_ratio']; export const anyValueType = [valueType.scalar, valueType.string, valueType.matrix, valueType.vector]; diff --git a/cmd/promlens/main.go b/cmd/promlens/main.go index 0cb08ec..ae042fc 100644 --- a/cmd/promlens/main.go +++ b/cmd/promlens/main.go @@ -22,6 +22,7 @@ import ( "strings" "time" + kingpin "github.com/alecthomas/kingpin/v2" "github.com/go-kit/log" "github.com/go-kit/log/level" "github.com/pkg/errors" @@ -29,7 +30,7 @@ import ( promlogflag "github.com/prometheus/common/promlog/flag" "github.com/prometheus/common/version" "github.com/prometheus/exporter-toolkit/web/kingpinflag" - "gopkg.in/alecthomas/kingpin.v2" + "github.com/prometheus/prometheus/promql/parser" "github.com/prometheus/promlens/pkg/grafana" "github.com/prometheus/promlens/pkg/sharer" @@ -167,6 +168,10 @@ func main() { toolkitConfig := kingpinflag.AddFlags(app, ":8080") + // Always enable experimental functions from the PromLens UI point of view. If the backend does not support them, + // the query will simply fail and report that the --enable-feature=promql-experimental-functions flag needs to be set. + parser.EnableExperimentalFunctions = true + _, err := app.Parse(os.Args[1:]) if err != nil { fmt.Fprintln(os.Stderr, errors.Wrapf(err, "error parsing commandline arguments")) diff --git a/go.mod b/go.mod index 0af00ce..8fd62ef 100644 --- a/go.mod +++ b/go.mod @@ -1,84 +1,81 @@ module github.com/prometheus/promlens -go 1.17 +go 1.21.0 + +toolchain go1.23.0 require ( - cloud.google.com/go/storage v1.28.1 + cloud.google.com/go/storage v1.41.0 + github.com/alecthomas/kingpin/v2 v2.4.0 github.com/glebarez/go-sqlite v1.21.1 github.com/go-kit/log v0.2.1 github.com/go-sql-driver/mysql v1.7.1 - github.com/grafana/regexp v0.0.0-20221122212121-6b5c0a4cb7fd + github.com/grafana/regexp v0.0.0-20240518133315-a468a5bfb3bc github.com/lib/pq v1.10.7 github.com/pkg/errors v0.9.1 - github.com/prometheus/client_golang v1.14.0 - github.com/prometheus/common v0.39.0 + github.com/prometheus/client_golang v1.19.1 + github.com/prometheus/common v0.55.0 github.com/prometheus/common/assets v0.2.0 - github.com/prometheus/exporter-toolkit v0.8.2 - github.com/prometheus/prometheus v0.41.0 + github.com/prometheus/exporter-toolkit v0.11.0 + github.com/prometheus/prometheus v0.54.1 github.com/russross/blackfriday/v2 v2.1.0 - golang.org/x/net v0.14.0 - gopkg.in/alecthomas/kingpin.v2 v2.2.6 + golang.org/x/net v0.27.0 ) require ( - cloud.google.com/go v0.105.0 // indirect - cloud.google.com/go/compute v1.13.0 // indirect - cloud.google.com/go/compute/metadata v0.2.2 // indirect - cloud.google.com/go/iam v0.8.0 // indirect - github.com/alecthomas/template v0.0.0-20190718012654-fb15b899a751 // indirect - github.com/alecthomas/units v0.0.0-20211218093645-b94a6e3cc137 // indirect - github.com/aws/aws-sdk-go v1.44.159 // indirect + cloud.google.com/go v0.115.0 // indirect + cloud.google.com/go/auth v0.7.0 // indirect + cloud.google.com/go/auth/oauth2adapt v0.2.2 // indirect + cloud.google.com/go/compute/metadata v0.4.0 // indirect + cloud.google.com/go/iam v1.1.10 // indirect + github.com/alecthomas/units v0.0.0-20240626203959-61d1e3462e30 // indirect github.com/beorn7/perks v1.0.1 // indirect - github.com/cespare/xxhash/v2 v2.2.0 // indirect - github.com/coreos/go-systemd/v22 v22.4.0 // indirect - github.com/davecgh/go-spew v1.1.1 // indirect + github.com/cespare/xxhash/v2 v2.3.0 // indirect + github.com/coreos/go-systemd/v22 v22.5.0 // indirect github.com/dennwc/varint v1.0.0 // indirect github.com/dustin/go-humanize v1.0.1 // indirect github.com/edsrzf/mmap-go v1.1.0 // indirect - github.com/go-logfmt/logfmt v0.5.1 // indirect - github.com/go-logr/logr v1.2.3 // indirect + github.com/facette/natsort v0.0.0-20181210072756-2cd4dd1e2dcb // indirect + github.com/felixge/httpsnoop v1.0.4 // indirect + github.com/go-logfmt/logfmt v0.6.0 // indirect + github.com/go-logr/logr v1.4.2 // indirect github.com/go-logr/stdr v1.2.2 // indirect github.com/gogo/protobuf v1.3.2 // indirect github.com/golang/groupcache v0.0.0-20210331224755-41bb18bfe9da // indirect - github.com/golang/protobuf v1.5.2 // indirect - github.com/golang/snappy v0.0.4 // indirect - github.com/google/go-cmp v0.5.9 // indirect - github.com/google/uuid v1.3.0 // indirect - github.com/googleapis/enterprise-certificate-proxy v0.2.0 // indirect - github.com/googleapis/gax-go/v2 v2.7.0 // indirect - github.com/jmespath/go-jmespath v0.4.0 // indirect + github.com/golang/protobuf v1.5.4 // indirect + github.com/google/s2a-go v0.1.7 // indirect + github.com/google/uuid v1.6.0 // indirect + github.com/googleapis/enterprise-certificate-proxy v0.3.2 // indirect + github.com/googleapis/gax-go/v2 v2.12.5 // indirect github.com/jpillora/backoff v1.0.0 // indirect - github.com/kr/pretty v0.3.1 // indirect - github.com/mattn/go-isatty v0.0.17 // indirect - github.com/matttproud/golang_protobuf_extensions v1.0.4 // indirect + github.com/klauspost/compress v1.17.9 // indirect + github.com/mattn/go-isatty v0.0.20 // indirect + github.com/munnerz/goautoneg v0.0.0-20191010083416-a7dc8b61c822 // indirect github.com/mwitkow/go-conntrack v0.0.0-20190716064945-2f068394615f // indirect - github.com/oklog/ulid v1.3.1 // indirect - github.com/pmezard/go-difflib v1.0.0 // indirect - github.com/prometheus/client_model v0.3.0 // indirect - github.com/prometheus/common/sigv4 v0.1.0 // indirect - github.com/prometheus/procfs v0.8.0 // indirect + github.com/prometheus/client_model v0.6.1 // indirect + github.com/prometheus/procfs v0.15.1 // indirect github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec // indirect - github.com/stretchr/testify v1.8.1 // indirect + github.com/xhit/go-str2duration/v2 v2.1.0 // indirect go.opencensus.io v0.24.0 // indirect - go.opentelemetry.io/otel v1.11.2 // indirect - go.opentelemetry.io/otel/trace v1.11.2 // indirect - go.uber.org/atomic v1.10.0 // indirect - go.uber.org/goleak v1.2.0 // indirect - golang.org/x/crypto v0.12.0 // indirect - golang.org/x/exp v0.0.0-20221212164502-fae10dda9338 // indirect - golang.org/x/lint v0.0.0-20210508222113-6edffad5e616 // indirect - golang.org/x/oauth2 v0.3.0 // indirect - golang.org/x/sync v0.1.0 // indirect - golang.org/x/sys v0.11.0 // indirect - golang.org/x/text v0.12.0 // indirect - golang.org/x/xerrors v0.0.0-20220907171357-04be3eba64a2 // indirect - google.golang.org/api v0.104.0 // indirect - google.golang.org/appengine v1.6.7 // indirect - google.golang.org/genproto v0.0.0-20221207170731-23e4bf6bdc37 // indirect - google.golang.org/grpc v1.51.0 // indirect - google.golang.org/protobuf v1.28.1 // indirect + go.opentelemetry.io/contrib/instrumentation/google.golang.org/grpc/otelgrpc v0.49.0 // indirect + go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp v0.53.0 // indirect + go.opentelemetry.io/otel v1.28.0 // indirect + go.opentelemetry.io/otel/metric v1.28.0 // indirect + go.opentelemetry.io/otel/trace v1.28.0 // indirect + go.uber.org/atomic v1.11.0 // indirect + golang.org/x/crypto v0.25.0 // indirect + golang.org/x/oauth2 v0.21.0 // indirect + golang.org/x/sync v0.7.0 // indirect + golang.org/x/sys v0.22.0 // indirect + golang.org/x/text v0.16.0 // indirect + golang.org/x/time v0.5.0 // indirect + google.golang.org/api v0.188.0 // indirect + google.golang.org/genproto v0.0.0-20240708141625-4ad9e859172b // indirect + google.golang.org/genproto/googleapis/api v0.0.0-20240711142825-46eb208f015d // indirect + google.golang.org/genproto/googleapis/rpc v0.0.0-20240708141625-4ad9e859172b // indirect + google.golang.org/grpc v1.65.0 // indirect + google.golang.org/protobuf v1.34.2 // indirect gopkg.in/yaml.v2 v2.4.0 // indirect - gopkg.in/yaml.v3 v3.0.1 // indirect modernc.org/libc v1.22.3 // indirect modernc.org/mathutil v1.5.0 // indirect modernc.org/memory v1.5.0 // indirect diff --git a/go.sum b/go.sum index 0087521..18fc640 100644 --- a/go.sum +++ b/go.sum @@ -1,1857 +1,287 @@ cloud.google.com/go v0.26.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw= -cloud.google.com/go v0.34.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw= -cloud.google.com/go v0.38.0/go.mod h1:990N+gfupTy94rShfmMCWGDn0LpTmnzTp2qbd1dvSRU= -cloud.google.com/go v0.44.1/go.mod h1:iSa0KzasP4Uvy3f1mN/7PiObzGgflwredwwASm/v6AU= -cloud.google.com/go v0.44.2/go.mod h1:60680Gw3Yr4ikxnPRS/oxxkBccT6SA1yMk63TGekxKY= -cloud.google.com/go v0.44.3/go.mod h1:60680Gw3Yr4ikxnPRS/oxxkBccT6SA1yMk63TGekxKY= -cloud.google.com/go v0.45.1/go.mod h1:RpBamKRgapWJb87xiFSdk4g1CME7QZg3uwTez+TSTjc= -cloud.google.com/go v0.46.3/go.mod h1:a6bKKbmY7er1mI7TEI4lsAkts/mkhTSZK8w33B4RAg0= -cloud.google.com/go v0.50.0/go.mod h1:r9sluTvynVuxRIOHXQEHMFffphuXHOMZMycpNR5e6To= -cloud.google.com/go v0.52.0/go.mod h1:pXajvRH/6o3+F9jDHZWQ5PbGhn+o8w9qiu/CffaVdO4= -cloud.google.com/go v0.53.0/go.mod h1:fp/UouUEsRkN6ryDKNW/Upv/JBKnv6WDthjR6+vze6M= -cloud.google.com/go v0.54.0/go.mod h1:1rq2OEkV3YMf6n/9ZvGWI3GWw0VoqH/1x2nd8Is/bPc= -cloud.google.com/go v0.56.0/go.mod h1:jr7tqZxxKOVYizybht9+26Z/gUq7tiRzu+ACVAMbKVk= -cloud.google.com/go v0.57.0/go.mod h1:oXiQ6Rzq3RAkkY7N6t3TcE6jE+CIBBbA36lwQ1JyzZs= -cloud.google.com/go v0.62.0/go.mod h1:jmCYTdRCQuc1PHIIJ/maLInMho30T/Y0M4hTdTShOYc= -cloud.google.com/go v0.65.0/go.mod h1:O5N8zS7uWy9vkA9vayVHs65eM1ubvY4h553ofrNHObY= -cloud.google.com/go v0.72.0/go.mod h1:M+5Vjvlc2wnp6tjzE102Dw08nGShTscUx2nZMufOKPI= -cloud.google.com/go v0.74.0/go.mod h1:VV1xSbzvo+9QJOxLDaJfTjx5e+MePCpCWwvftOeQmWk= -cloud.google.com/go v0.75.0/go.mod h1:VGuuCn7PG0dwsd5XPVm2Mm3wlh3EL55/79EKB6hlPTY= -cloud.google.com/go v0.78.0/go.mod h1:QjdrLG0uq+YwhjoVOLsS1t7TW8fs36kLs4XO5R5ECHg= -cloud.google.com/go v0.79.0/go.mod h1:3bzgcEeQlzbuEAYu4mrWhKqWjmpprinYgKJLgKHnbb8= -cloud.google.com/go v0.81.0/go.mod h1:mk/AM35KwGk/Nm2YSeZbxXdrNK3KZOYHmLkOqC2V6E0= -cloud.google.com/go v0.83.0/go.mod h1:Z7MJUsANfY0pYPdw0lbnivPx4/vhy/e2FEkSkF7vAVY= -cloud.google.com/go v0.84.0/go.mod h1:RazrYuxIK6Kb7YrzzhPoLmCVzl7Sup4NrbKPg8KHSUM= -cloud.google.com/go v0.87.0/go.mod h1:TpDYlFy7vuLzZMMZ+B6iRiELaY7z/gJPaqbMx6mlWcY= -cloud.google.com/go v0.90.0/go.mod h1:kRX0mNRHe0e2rC6oNakvwQqzyDmg57xJ+SZU1eT2aDQ= -cloud.google.com/go v0.93.3/go.mod h1:8utlLll2EF5XMAV15woO4lSbWQlk8rer9aLOfLh7+YI= -cloud.google.com/go v0.94.1/go.mod h1:qAlAugsXlC+JWO+Bke5vCtc9ONxjQT3drlTTnAplMW4= -cloud.google.com/go v0.97.0/go.mod h1:GF7l59pYBVlXQIBLx3a761cZ41F9bBH3JUlihCt2Udc= -cloud.google.com/go v0.99.0/go.mod h1:w0Xx2nLzqWJPuozYQX+hFfCSI8WioryfRDzkoI/Y2ZA= -cloud.google.com/go v0.100.1/go.mod h1:fs4QogzfH5n2pBXBP9vRiU+eCny7lD2vmFZy79Iuw1U= -cloud.google.com/go v0.100.2/go.mod h1:4Xra9TjzAeYHrl5+oeLlzbM2k3mjVhZh4UqTZ//w99A= -cloud.google.com/go v0.102.0/go.mod h1:oWcCzKlqJ5zgHQt9YsaeTY9KzIvjyy0ArmiBUgpQ+nc= -cloud.google.com/go v0.102.1/go.mod h1:XZ77E9qnTEnrgEOvr4xzfdX5TRo7fB4T2F4O6+34hIU= -cloud.google.com/go v0.104.0/go.mod h1:OO6xxXdJyvuJPcEPBLN9BJPD+jep5G1+2U5B5gkRYtA= -cloud.google.com/go v0.105.0 h1:DNtEKRBAAzeS4KyIory52wWHuClNaXJ5x1F7xa4q+5Y= -cloud.google.com/go v0.105.0/go.mod h1:PrLgOJNe5nfE9UMxKxgXj4mD3voiP+YQ6gdt6KMFOKM= -cloud.google.com/go/accessapproval v1.4.0/go.mod h1:zybIuC3KpDOvotz59lFe5qxRZx6C75OtwbisN56xYB4= -cloud.google.com/go/accessapproval v1.5.0/go.mod h1:HFy3tuiGvMdcd/u+Cu5b9NkO1pEICJ46IR82PoUdplw= -cloud.google.com/go/accesscontextmanager v1.3.0/go.mod h1:TgCBehyr5gNMz7ZaH9xubp+CE8dkrszb4oK9CWyvD4o= -cloud.google.com/go/accesscontextmanager v1.4.0/go.mod h1:/Kjh7BBu/Gh83sv+K60vN9QE5NJcd80sU33vIe2IFPE= -cloud.google.com/go/aiplatform v1.22.0/go.mod h1:ig5Nct50bZlzV6NvKaTwmplLLddFx0YReh9WfTO5jKw= -cloud.google.com/go/aiplatform v1.24.0/go.mod h1:67UUvRBKG6GTayHKV8DBv2RtR1t93YRu5B1P3x99mYY= -cloud.google.com/go/aiplatform v1.27.0/go.mod h1:Bvxqtl40l0WImSb04d0hXFU7gDOiq9jQmorivIiWcKg= -cloud.google.com/go/analytics v0.11.0/go.mod h1:DjEWCu41bVbYcKyvlws9Er60YE4a//bK6mnhWvQeFNI= -cloud.google.com/go/analytics v0.12.0/go.mod h1:gkfj9h6XRf9+TS4bmuhPEShsh3hH8PAZzm/41OOhQd4= -cloud.google.com/go/apigateway v1.3.0/go.mod h1:89Z8Bhpmxu6AmUxuVRg/ECRGReEdiP3vQtk4Z1J9rJk= -cloud.google.com/go/apigateway v1.4.0/go.mod h1:pHVY9MKGaH9PQ3pJ4YLzoj6U5FUDeDFBllIz7WmzJoc= -cloud.google.com/go/apigeeconnect v1.3.0/go.mod h1:G/AwXFAKo0gIXkPTVfZDd2qA1TxBXJ3MgMRBQkIi9jc= -cloud.google.com/go/apigeeconnect v1.4.0/go.mod h1:kV4NwOKqjvt2JYR0AoIWo2QGfoRtn/pkS3QlHp0Ni04= -cloud.google.com/go/appengine v1.4.0/go.mod h1:CS2NhuBuDXM9f+qscZ6V86m1MIIqPj3WC/UoEuR1Sno= -cloud.google.com/go/appengine v1.5.0/go.mod h1:TfasSozdkFI0zeoxW3PTBLiNqRmzraodCWatWI9Dmak= -cloud.google.com/go/area120 v0.5.0/go.mod h1:DE/n4mp+iqVyvxHN41Vf1CR602GiHQjFPusMFW6bGR4= -cloud.google.com/go/area120 v0.6.0/go.mod h1:39yFJqWVgm0UZqWTOdqkLhjoC7uFfgXRC8g/ZegeAh0= -cloud.google.com/go/artifactregistry v1.6.0/go.mod h1:IYt0oBPSAGYj/kprzsBjZ/4LnG/zOcHyFHjWPCi6SAQ= -cloud.google.com/go/artifactregistry v1.7.0/go.mod h1:mqTOFOnGZx8EtSqK/ZWcsm/4U8B77rbcLP6ruDU2Ixk= -cloud.google.com/go/artifactregistry v1.8.0/go.mod h1:w3GQXkJX8hiKN0v+at4b0qotwijQbYUqF2GWkZzAhC0= -cloud.google.com/go/artifactregistry v1.9.0/go.mod h1:2K2RqvA2CYvAeARHRkLDhMDJ3OXy26h3XW+3/Jh2uYc= -cloud.google.com/go/asset v1.5.0/go.mod h1:5mfs8UvcM5wHhqtSv8J1CtxxaQq3AdBxxQi2jGW/K4o= -cloud.google.com/go/asset v1.7.0/go.mod h1:YbENsRK4+xTiL+Ofoj5Ckf+O17kJtgp3Y3nn4uzZz5s= -cloud.google.com/go/asset v1.8.0/go.mod h1:mUNGKhiqIdbr8X7KNayoYvyc4HbbFO9URsjbytpUaW0= -cloud.google.com/go/asset v1.9.0/go.mod h1:83MOE6jEJBMqFKadM9NLRcs80Gdw76qGuHn8m3h8oHQ= -cloud.google.com/go/asset v1.10.0/go.mod h1:pLz7uokL80qKhzKr4xXGvBQXnzHn5evJAEAtZiIb0wY= -cloud.google.com/go/assuredworkloads v1.5.0/go.mod h1:n8HOZ6pff6re5KYfBXcFvSViQjDwxFkAkmUFffJRbbY= -cloud.google.com/go/assuredworkloads v1.6.0/go.mod h1:yo2YOk37Yc89Rsd5QMVECvjaMKymF9OP+QXWlKXUkXw= -cloud.google.com/go/assuredworkloads v1.7.0/go.mod h1:z/736/oNmtGAyU47reJgGN+KVoYoxeLBoj4XkKYscNI= -cloud.google.com/go/assuredworkloads v1.8.0/go.mod h1:AsX2cqyNCOvEQC8RMPnoc0yEarXQk6WEKkxYfL6kGIo= -cloud.google.com/go/assuredworkloads v1.9.0/go.mod h1:kFuI1P78bplYtT77Tb1hi0FMxM0vVpRC7VVoJC3ZoT0= -cloud.google.com/go/automl v1.5.0/go.mod h1:34EjfoFGMZ5sgJ9EoLsRtdPSNZLcfflJR39VbVNS2M0= -cloud.google.com/go/automl v1.6.0/go.mod h1:ugf8a6Fx+zP0D59WLhqgTDsQI9w07o64uf/Is3Nh5p8= -cloud.google.com/go/automl v1.7.0/go.mod h1:RL9MYCCsJEOmt0Wf3z9uzG0a7adTT1fe+aObgSpkCt8= -cloud.google.com/go/automl v1.8.0/go.mod h1:xWx7G/aPEe/NP+qzYXktoBSDfjO+vnKMGgsApGJJquM= -cloud.google.com/go/baremetalsolution v0.3.0/go.mod h1:XOrocE+pvK1xFfleEnShBlNAXf+j5blPPxrhjKgnIFc= -cloud.google.com/go/baremetalsolution v0.4.0/go.mod h1:BymplhAadOO/eBa7KewQ0Ppg4A4Wplbn+PsFKRLo0uI= -cloud.google.com/go/batch v0.3.0/go.mod h1:TR18ZoAekj1GuirsUsR1ZTKN3FC/4UDnScjT8NXImFE= -cloud.google.com/go/batch v0.4.0/go.mod h1:WZkHnP43R/QCGQsZ+0JyG4i79ranE2u8xvjq/9+STPE= -cloud.google.com/go/beyondcorp v0.2.0/go.mod h1:TB7Bd+EEtcw9PCPQhCJtJGjk/7TC6ckmnSFS+xwTfm4= -cloud.google.com/go/beyondcorp v0.3.0/go.mod h1:E5U5lcrcXMsCuoDNyGrpyTm/hn7ne941Jz2vmksAxW8= -cloud.google.com/go/bigquery v1.0.1/go.mod h1:i/xbL2UlR5RvWAURpBYZTtm/cXjCha9lbfbpx4poX+o= -cloud.google.com/go/bigquery v1.3.0/go.mod h1:PjpwJnslEMmckchkHFfq+HTD2DmtT67aNFKH1/VBDHE= -cloud.google.com/go/bigquery v1.4.0/go.mod h1:S8dzgnTigyfTmLBfrtrhyYhwRxG72rYxvftPBK2Dvzc= -cloud.google.com/go/bigquery v1.5.0/go.mod h1:snEHRnqQbz117VIFhE8bmtwIDY80NLUZUMb4Nv6dBIg= -cloud.google.com/go/bigquery v1.7.0/go.mod h1://okPTzCYNXSlb24MZs83e2Do+h+VXtc4gLoIoXIAPc= -cloud.google.com/go/bigquery v1.8.0/go.mod h1:J5hqkt3O0uAFnINi6JXValWIb1v0goeZM77hZzJN/fQ= -cloud.google.com/go/bigquery v1.42.0/go.mod h1:8dRTJxhtG+vwBKzE5OseQn/hiydoQN3EedCaOdYmxRA= -cloud.google.com/go/bigquery v1.43.0/go.mod h1:ZMQcXHsl+xmU1z36G2jNGZmKp9zNY5BUua5wDgmNCfw= -cloud.google.com/go/bigquery v1.44.0/go.mod h1:0Y33VqXTEsbamHJvJHdFmtqHvMIY28aK1+dFsvaChGc= -cloud.google.com/go/billing v1.4.0/go.mod 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"github.com/prometheus/client_golang/prometheus/collectors/version" "github.com/prometheus/client_golang/prometheus/promhttp" - "github.com/prometheus/common/version" toolkitweb "github.com/prometheus/exporter-toolkit/web" "github.com/prometheus/promlens/pkg/grafana"