mirror of https://github.com/grafana/grafana
prometheushacktoberfestmetricsmonitoringalertinggrafanagoinfluxdbmysqlpostgresanalyticsdata-visualizationdashboardbusiness-intelligenceelasticsearch
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
373 lines
16 KiB
373 lines
16 KiB
import { getAutoQueriesForMetric } from './AutoQueryEngine';
|
|
|
|
function expandExpr(shortenedExpr: string) {
|
|
return shortenedExpr.replace('...', '${metric}{${filters}}');
|
|
}
|
|
|
|
const otelJoinQuery = '${otel_join_query}';
|
|
|
|
describe('getAutoQueriesForMetric', () => {
|
|
describe('for the summary/histogram types', () => {
|
|
const etc = '{${filters}}[$__rate_interval]';
|
|
const byGroup = 'by(${groupby})';
|
|
|
|
describe('metrics with _sum suffix', () => {
|
|
const result = getAutoQueriesForMetric('SUM_OR_HIST_sum');
|
|
|
|
test('main query is the mean', () => {
|
|
const [{ expr }] = result.main.queries;
|
|
const mean = `sum(rate(SUM_OR_HIST_sum${etc}) ${otelJoinQuery})/sum(rate(SUM_OR_HIST_count${etc}) ${otelJoinQuery})`;
|
|
|
|
expect(expr).toBe(mean);
|
|
});
|
|
|
|
test('preview query is the mean', () => {
|
|
const [{ expr }] = result.preview.queries;
|
|
const mean = `sum(rate(SUM_OR_HIST_sum${etc}) ${otelJoinQuery})/sum(rate(SUM_OR_HIST_count${etc}) ${otelJoinQuery})`;
|
|
expect(expr).toBe(mean);
|
|
});
|
|
|
|
test('breakdown query is the mean by group', () => {
|
|
const [{ expr }] = result.breakdown.queries;
|
|
const meanBreakdown = `sum(rate(SUM_OR_HIST_sum${etc}) ${otelJoinQuery})${byGroup}/sum(rate(SUM_OR_HIST_count${etc}) ${otelJoinQuery})${byGroup}`;
|
|
expect(expr).toBe(meanBreakdown);
|
|
});
|
|
|
|
test('there are no variants', () => {
|
|
expect(result.variants.length).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe('metrics with _count suffix', () => {
|
|
const result = getAutoQueriesForMetric('SUM_OR_HIST_count');
|
|
|
|
test('main query is an overall rate', () => {
|
|
const [{ expr }] = result.main.queries;
|
|
const overallRate = `sum(rate(\${metric}${etc}) ${otelJoinQuery})`;
|
|
expect(expr).toBe(overallRate);
|
|
});
|
|
|
|
test('preview query is an overall rate', () => {
|
|
const [{ expr }] = result.preview.queries;
|
|
const overallRate = `sum(rate(\${metric}${etc}) ${otelJoinQuery})`;
|
|
expect(expr).toBe(overallRate);
|
|
});
|
|
|
|
test('breakdown query is an overall rate by group', () => {
|
|
const [{ expr }] = result.breakdown.queries;
|
|
const overallRateBreakdown = `sum(rate(\${metric}${etc}) ${otelJoinQuery})${byGroup}`;
|
|
expect(expr).toBe(overallRateBreakdown);
|
|
});
|
|
|
|
test('there are no variants', () => {
|
|
expect(result.variants.length).toBe(0);
|
|
});
|
|
});
|
|
|
|
// ***WE DEFAULT TO HEATMAP HERE
|
|
describe('metrics with _bucket suffix', () => {
|
|
const result = getAutoQueriesForMetric('HIST_bucket');
|
|
|
|
const percentileQueries = new Map<number, string>();
|
|
percentileQueries.set(99, expandExpr('histogram_quantile(0.99, sum by(le) (rate(...[$__rate_interval])))'));
|
|
percentileQueries.set(90, expandExpr('histogram_quantile(0.9, sum by(le) (rate(...[$__rate_interval])))'));
|
|
percentileQueries.set(50, expandExpr('histogram_quantile(0.5, sum by(le) (rate(...[$__rate_interval])))'));
|
|
|
|
test('there are 2 variants', () => {
|
|
expect(result.variants.length).toBe(2);
|
|
});
|
|
|
|
const percentilesVariant = result.variants.find((variant) => variant.variant === 'percentiles');
|
|
test('there is a percentiles variant', () => {
|
|
expect(percentilesVariant).not.toBeNull();
|
|
});
|
|
|
|
const heatmap = result.variants.find((variant) => variant.variant === 'heatmap');
|
|
test('there is a heatmap variant', () => {
|
|
expect(heatmap).not.toBeNull();
|
|
});
|
|
|
|
[99, 90, 50].forEach((percentile) => {
|
|
const percentileQuery = percentileQueries.get(percentile);
|
|
test(`main panel has ${percentile}th percentile query`, () => {
|
|
const found = result.main.queries.find((query) => query.expr === percentileQuery);
|
|
expect(found).not.toBeNull();
|
|
});
|
|
});
|
|
|
|
[99, 90, 50].forEach((percentile) => {
|
|
const percentileQuery = percentileQueries.get(percentile);
|
|
test(`percentiles variant panel has ${percentile}th percentile query`, () => {
|
|
const found = percentilesVariant?.queries.find((query) => query.expr === percentileQuery);
|
|
expect(found).not.toBeNull();
|
|
});
|
|
});
|
|
|
|
test('preview panel has heatmap query', () => {
|
|
const [{ expr }] = result.preview.queries;
|
|
const expected = 'sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query})';
|
|
expect(expr).toBe(expected);
|
|
});
|
|
|
|
const percentileGroupedQueries = new Map<number, string>();
|
|
percentileGroupedQueries.set(
|
|
99,
|
|
expandExpr('histogram_quantile(0.99, sum by(le, ${groupby}) (rate(...[$__rate_interval])))')
|
|
);
|
|
percentileGroupedQueries.set(
|
|
90,
|
|
expandExpr('histogram_quantile(0.9, sum by(le, ${groupby}) (rate(...[$__rate_interval])))')
|
|
);
|
|
percentileGroupedQueries.set(
|
|
50,
|
|
expandExpr('histogram_quantile(0.5, sum by(le, ${groupby}) (rate(...[$__rate_interval])))')
|
|
);
|
|
|
|
[99, 90, 50].forEach((percentile) => {
|
|
const percentileGroupedQuery = percentileGroupedQueries.get(percentile);
|
|
test(`breakdown panel has ${percentile}th query with \${groupby} appended`, () => {
|
|
const found = result.breakdown.queries.find((query) => query.expr === percentileGroupedQuery);
|
|
expect(found).not.toBeNull();
|
|
});
|
|
});
|
|
});
|
|
});
|
|
describe('Consider result.main query (only first)', () => {
|
|
it.each([
|
|
// no rate
|
|
['PREFIX_general', 'avg(... ${otel_join_query})', 'short', 1],
|
|
['PREFIX_bytes', 'avg(... ${otel_join_query})', 'bytes', 1],
|
|
['PREFIX_seconds', 'avg(... ${otel_join_query})', 's', 1],
|
|
// rate with counts per second
|
|
['PREFIX_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps', 1], // cps = counts per second
|
|
['PREFIX_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps', 1],
|
|
['PREFIX_seconds_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps', 1],
|
|
// rate with seconds per second
|
|
['PREFIX_seconds_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'short', 1], // s/s
|
|
// rate with bytes per second
|
|
['PREFIX_bytes_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'Bps', 1], // bytes/s
|
|
// mean with non-rated units
|
|
[
|
|
'PREFIX_seconds_sum',
|
|
'sum(rate(PREFIX_seconds_sum{${filters}}[$__rate_interval]) ${otel_join_query})/sum(rate(PREFIX_seconds_count{${filters}}[$__rate_interval]) ${otel_join_query})',
|
|
's',
|
|
1,
|
|
],
|
|
[
|
|
'PREFIX_bytes_sum',
|
|
'sum(rate(PREFIX_bytes_sum{${filters}}[$__rate_interval]) ${otel_join_query})/sum(rate(PREFIX_bytes_count{${filters}}[$__rate_interval]) ${otel_join_query})',
|
|
'bytes',
|
|
1,
|
|
],
|
|
// ***WE DEFAULT TO HEATMAP HERE
|
|
// Bucket
|
|
['PREFIX_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 'short', 1],
|
|
['PREFIX_seconds_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 's', 1],
|
|
['PREFIX_bytes_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 'bytes', 1],
|
|
])('Given metric %p expect %p with unit %p', (metric, expr, unit, queryCount) => {
|
|
const result = getAutoQueriesForMetric(metric);
|
|
|
|
const queryDef = result.main;
|
|
|
|
const expected = { expr: expandExpr(expr), unit, queryCount };
|
|
const actual = { expr: queryDef.queries[0].expr, unit: queryDef.unit, queryCount: queryDef.queries.length };
|
|
|
|
expect(actual).toStrictEqual(expected);
|
|
});
|
|
});
|
|
|
|
describe('Consider result.preview query (only first)', () => {
|
|
it.each([
|
|
// no rate
|
|
['PREFIX_general', 'avg(... ${otel_join_query})', 'short'],
|
|
['PREFIX_bytes', 'avg(... ${otel_join_query})', 'bytes'],
|
|
['PREFIX_seconds', 'avg(... ${otel_join_query})', 's'],
|
|
// rate with counts per second
|
|
['PREFIX_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps'], // cps = counts per second
|
|
['PREFIX_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps'],
|
|
['PREFIX_seconds_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'cps'],
|
|
// rate with seconds per second
|
|
['PREFIX_seconds_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'short'], // s/s
|
|
// rate with bytes per second
|
|
['PREFIX_bytes_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})', 'Bps'], // bytes/s
|
|
// mean with non-rated units
|
|
[
|
|
'PREFIX_seconds_sum',
|
|
'sum(rate(PREFIX_seconds_sum{${filters}}[$__rate_interval]) ${otel_join_query})/sum(rate(PREFIX_seconds_count{${filters}}[$__rate_interval]) ${otel_join_query})',
|
|
's',
|
|
],
|
|
[
|
|
'PREFIX_bytes_sum',
|
|
'sum(rate(PREFIX_bytes_sum{${filters}}[$__rate_interval]) ${otel_join_query})/sum(rate(PREFIX_bytes_count{${filters}}[$__rate_interval]) ${otel_join_query})',
|
|
'bytes',
|
|
],
|
|
// Bucket
|
|
['PREFIX_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 'short'],
|
|
['PREFIX_seconds_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 's'],
|
|
['PREFIX_bytes_bucket', 'sum by(le) (rate(...[$__rate_interval])${otel_join_query})', 'bytes'],
|
|
])('Given metric %p expect %p with unit %p', (metric, expr, unit) => {
|
|
const result = getAutoQueriesForMetric(metric);
|
|
|
|
const queryDef = result.preview;
|
|
|
|
const queryCount = 1;
|
|
|
|
const expected = { expr: expandExpr(expr), unit, queryCount };
|
|
const actual = { expr: queryDef.queries[0].expr, unit: queryDef.unit, queryCount: queryDef.queries.length };
|
|
|
|
expect(actual).toStrictEqual(expected);
|
|
});
|
|
});
|
|
|
|
describe('Consider result.breakdown query (only first)', () => {
|
|
it.each([
|
|
// no rate
|
|
['PREFIX_general', 'avg(... ${otel_join_query})by(${groupby})', 'short'],
|
|
['PREFIX_bytes', 'avg(... ${otel_join_query})by(${groupby})', 'bytes'],
|
|
['PREFIX_seconds', 'avg(... ${otel_join_query})by(${groupby})', 's'],
|
|
// rate with counts per second
|
|
['PREFIX_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})by(${groupby})', 'cps'], // cps = counts per second
|
|
['PREFIX_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})by(${groupby})', 'cps'],
|
|
['PREFIX_seconds_count', 'sum(rate(...[$__rate_interval]) ${otel_join_query})by(${groupby})', 'cps'],
|
|
// rate with seconds per second
|
|
['PREFIX_seconds_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})by(${groupby})', 'short'], // s/s
|
|
// rate with bytes per second
|
|
['PREFIX_bytes_total', 'sum(rate(...[$__rate_interval]) ${otel_join_query})by(${groupby})', 'Bps'], // bytes/s
|
|
// mean with non-rated units
|
|
[
|
|
'PREFIX_seconds_sum',
|
|
'sum(rate(PREFIX_seconds_sum{${filters}}[$__rate_interval]) ${otel_join_query})by(${groupby})/sum(rate(PREFIX_seconds_count{${filters}}[$__rate_interval]) ${otel_join_query})by(${groupby})',
|
|
's',
|
|
],
|
|
[
|
|
'PREFIX_bytes_sum',
|
|
'sum(rate(PREFIX_bytes_sum{${filters}}[$__rate_interval]) ${otel_join_query})by(${groupby})/sum(rate(PREFIX_bytes_count{${filters}}[$__rate_interval]) ${otel_join_query})by(${groupby})',
|
|
'bytes',
|
|
],
|
|
// Bucket
|
|
[
|
|
'PREFIX_bucket',
|
|
'histogram_quantile(0.5, sum by(le, ${groupby}) (rate(...[$__rate_interval])${otel_join_query}))',
|
|
'short',
|
|
],
|
|
[
|
|
'PREFIX_seconds_bucket',
|
|
'histogram_quantile(0.5, sum by(le, ${groupby}) (rate(...[$__rate_interval])${otel_join_query}))',
|
|
's',
|
|
],
|
|
[
|
|
'PREFIX_bytes_bucket',
|
|
'histogram_quantile(0.5, sum by(le, ${groupby}) (rate(...[$__rate_interval])${otel_join_query}))',
|
|
'bytes',
|
|
],
|
|
])('Given metric %p expect %p with unit %p', (metric, expr, unit) => {
|
|
const result = getAutoQueriesForMetric(metric);
|
|
|
|
const queryDef = result.breakdown;
|
|
|
|
const queryCount = 1;
|
|
|
|
const expected = { expr: expandExpr(expr), unit, queryCount };
|
|
const actual = { expr: queryDef.queries[0].expr, unit: queryDef.unit, queryCount: queryDef.queries.length };
|
|
|
|
expect(actual).toStrictEqual(expected);
|
|
});
|
|
});
|
|
|
|
describe('Consider result.variant', () => {
|
|
it.each([
|
|
// No variants
|
|
['PREFIX_count', []],
|
|
['PREFIX_seconds_count', []],
|
|
['PREFIX_bytes', []],
|
|
['PREFIX_seconds', []],
|
|
['PREFIX_general', []],
|
|
['PREFIX_seconds_total', []],
|
|
['PREFIX_seconds_sum', []],
|
|
// Bucket variants
|
|
[
|
|
'PREFIX_bucket',
|
|
[
|
|
{
|
|
variant: 'percentiles',
|
|
unit: 'short',
|
|
exprs: [
|
|
'histogram_quantile(0.99, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.9, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.5, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
],
|
|
},
|
|
{
|
|
variant: 'heatmap',
|
|
unit: 'short',
|
|
exprs: ['sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query})'],
|
|
},
|
|
],
|
|
],
|
|
[
|
|
'PREFIX_seconds_bucket',
|
|
[
|
|
{
|
|
variant: 'percentiles',
|
|
unit: 's',
|
|
exprs: [
|
|
'histogram_quantile(0.99, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.9, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.5, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
],
|
|
},
|
|
{
|
|
variant: 'heatmap',
|
|
unit: 's',
|
|
exprs: ['sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query})'],
|
|
},
|
|
],
|
|
],
|
|
[
|
|
'PREFIX_bytes_bucket',
|
|
[
|
|
{
|
|
variant: 'percentiles',
|
|
unit: 'bytes',
|
|
exprs: [
|
|
'histogram_quantile(0.99, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.9, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
'histogram_quantile(0.5, sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query}))',
|
|
],
|
|
},
|
|
{
|
|
variant: 'heatmap',
|
|
unit: 'bytes',
|
|
exprs: ['sum by(le) (rate(${metric}{${filters}}[$__rate_interval])${otel_join_query})'],
|
|
},
|
|
],
|
|
],
|
|
])('Given metric %p should generate expected variants', (metric, expectedVariants) => {
|
|
const defs = getAutoQueriesForMetric(metric);
|
|
|
|
const received = defs.variants.map((variant) => ({
|
|
variant: variant.variant,
|
|
unit: variant.unit,
|
|
exprs: variant.queries.map((query) => query.expr),
|
|
}));
|
|
|
|
expect(received).toStrictEqual(expectedVariants);
|
|
});
|
|
});
|
|
|
|
describe('Able to handle unconventional metric names', () => {
|
|
it.each([['PRODUCT_High_Priority_items_', 'avg(... ${otel_join_query})', 'short', 1]])(
|
|
'Given metric %p expect %p with unit %p',
|
|
(metric, expr, unit, queryCount) => {
|
|
const result = getAutoQueriesForMetric(metric);
|
|
|
|
const queryDef = result.main;
|
|
|
|
const expected = { expr: expandExpr(expr), unit, queryCount };
|
|
const actual = { expr: queryDef.queries[0].expr, unit: queryDef.unit, queryCount: queryDef.queries.length };
|
|
|
|
expect(actual).toStrictEqual(expected);
|
|
}
|
|
);
|
|
});
|
|
});
|
|
|