[FEATURE] PromQL: Add experimental info function MVP (#14495)

The `info` function is an experiment to improve UX
around including labels from info metrics.
`info` has to be enabled via the feature flag `--enable-feature=promql-experimental-functions`.

This MVP of info simplifies the implementation by assuming:
* Only support for the target_info metric
* That target_info's identifying labels are job and instance

Also:
* Encode info samples' original timestamp as sample value
* Deduce info series select hints from top-most VectorSelector

---------

Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com>
Co-authored-by: Ying WANG <ying.wang@grafana.com>
Co-authored-by: Augustin Husson <augustin.husson@amadeus.com>
Co-authored-by: Bartlomiej Plotka <bwplotka@gmail.com>
Co-authored-by: Björn Rabenstein <github@rabenste.in>
Co-authored-by: Bryan Boreham <bjboreham@gmail.com>

CHANGELOG.md

@@ -2,6 +2,8 @@
 
 ## unreleased
 
+* [FEATURE] PromQL: Add experimental `info` function. #14495
+
 ## 2.55.0-rc.0 / 2024-09-20
 
 * [FEATURE] Support UTF-8 characters in label names - feature flag `utf8-names`. #14482, #14880, #14736, #14727

docs/querying/functions.md

@@ -432,6 +432,97 @@ 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.
 
+## `info()` (experimental)
+
+_The `info` function is an experiment to improve UX
+around including labels from [info metrics](https://grafana.com/blog/2021/08/04/how-to-use-promql-joins-for-more-effective-queries-of-prometheus-metrics-at-scale/#info-metrics).
+The behavior of this function may change in future versions of Prometheus,
+including its removal from PromQL. `info` has to be enabled via the 
+[feature flag](../feature_flags.md#experimental-promql-functions) `--enable-feature=promql-experimental-functions`._
+
+`info(v instant-vector, [data-label-selector instant-vector])` finds, for each time 
+series in `v`, all info series with matching _identifying_ labels (more on
+this later), and adds the union of their _data_ (i.e., non-identifying) labels
+to the time series. The second argument `data-label-selector` is optional.
+It is not a real instant vector, but uses a subset of its syntax.
+It must start and end with curly braces (`{ ... }`) and may only contain label matchers.
+The label matchers are used to constrain which info series to consider
+and which data labels to add to `v`.
+
+Identifying labels of an info series are the subset of labels that uniquely
+identify the info series. The remaining labels are considered
+_data labels_ (also called non-identifying). (Note that Prometheus's concept
+of time series identity always includes _all_ the labels. For the sake of the `info`
+function, we “logically” define info series identity in a different way than
+in the conventional Prometheus view.) The identifying labels of an info series
+are used to join it to regular (non-info) series, i.e. those series that have
+the same labels as the identifying labels of the info series. The data labels, which are
+the ones added to the regular series by the `info` function, effectively encode 
+metadata key value pairs. (This implies that a change in the data labels 
+in the conventional Prometheus view constitutes the end of one info series and
+the beginning of a new info series, while the “logical” view of the `info` function is
+that the same info series continues to exist, just with different “data”.)
+
+The conventional approach of adding data labels is sometimes called a “join query”,
+as illustrated by the following example:
+
+```
+  rate(http_server_request_duration_seconds_count[2m])
+* on (job, instance) group_left (k8s_cluster_name)
+  target_info
+```
+
+The core of the query is the expression `rate(http_server_request_duration_seconds_count[2m])`.
+But to add data labels from an info metric, the user has to use elaborate
+(and not very obvious) syntax to specify which info metric to use (`target_info`), what the
+identifying labels are (`on (job, instance)`), and which data labels to add
+(`group_left (k8s_cluster_name)`).
+
+This query is not only verbose and hard to write, it might also run into an “identity crisis”:
+If any of the data labels of `target_info` changes, Prometheus sees that as a change of series
+(as alluded to above, Prometheus just has no native concept of non-identifying labels).
+If the old `target_info` series is not properly marked as stale (which can happen with certain ingestion paths),
+the query above will fail for up to 5m (the lookback delta) because it will find a conflicting 
+match with both the old and the new version of `target_info`.
+
+The `info` function not only resolves this conflict in favor of the newer series, it also simplifies the syntax
+because it knows about the available info series and what their identifying labels are. The example query
+looks like this with the `info` function:
+
+```
+info(
+  rate(http_server_request_duration_seconds_count[2m]),
+  {k8s_cluster_name=~".+"}
+)
+```
+
+The common case of adding _all_ data labels can be achieved by
+omitting the 2nd argument of the `info` function entirely, simplifying
+the example even more:
+
+```
+info(rate(http_server_request_duration_seconds_count[2m]))
+```
+
+While `info` normally automatically finds all matching info series, it's possible to
+restrict them by providing a `__name__` label matcher, e.g.
+`{__name__="target_info"}`.
+
+### Limitations
+
+In its current iteration, `info` defaults to considering only info series with
+the name `target_info`. It also assumes that the identifying info series labels are
+`instance` and `job`. `info` does support other info series names however, through
+`__name__` label matchers. E.g., one can explicitly say to consider both 
+`target_info` and `build_info` as follows:
+`{__name__=~"(target|build)_info"}`. However, the identifying labels always
+have to be `instance` and `job`.
+
+These limitations are partially defeating the purpose of the `info` function.
+At the current stage, this is an experiment to find out how useful the approach
+turns out to be in practice. A final version of the `info` function will indeed
+consider all matching info series and with their appropriate identifying labels.
+
 ## `irate()`
 
 `irate(v range-vector)` calculates the per-second instant rate of increase of

promql/bench_test.go

@@ -21,6 +21,8 @@ import (
 	"testing"
 	"time"
 
+	"github.com/stretchr/testify/require"
+
 	"github.com/prometheus/prometheus/model/histogram"
 	"github.com/prometheus/prometheus/model/labels"
 	"github.com/prometheus/prometheus/promql"
@@ -380,6 +382,126 @@ func BenchmarkNativeHistograms(b *testing.B) {
 	}
 }
 
+func BenchmarkInfoFunction(b *testing.B) {
+	// Initialize test storage and generate test series data.
+	testStorage := teststorage.New(b)
+	defer testStorage.Close()
+
+	start := time.Unix(0, 0)
+	end := start.Add(2 * time.Hour)
+	step := 30 * time.Second
+
+	// Generate time series data for the benchmark.
+	generateInfoFunctionTestSeries(b, testStorage, 100, 2000, 3600)
+
+	// Define test cases with queries to benchmark.
+	cases := []struct {
+		name  string
+		query string
+	}{
+		{
+			name:  "Joining info metrics with other metrics with group_left example 1",
+			query: "rate(http_server_request_duration_seconds_count[2m]) * on (job, instance) group_left (k8s_cluster_name) target_info{k8s_cluster_name=\"us-east\"}",
+		},
+		{
+			name:  "Joining info metrics with other metrics with info() example 1",
+			query: `info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name="us-east"})`,
+		},
+		{
+			name:  "Joining info metrics with other metrics with group_left example 2",
+			query: "sum by (k8s_cluster_name, http_status_code) (rate(http_server_request_duration_seconds_count[2m]) * on (job, instance) group_left (k8s_cluster_name) target_info)",
+		},
+		{
+			name:  "Joining info metrics with other metrics with info() example 2",
+			query: `sum by (k8s_cluster_name, http_status_code) (info(rate(http_server_request_duration_seconds_count[2m]), {k8s_cluster_name=~".+"}))`,
+		},
+	}
+
+	// Benchmark each query type.
+	for _, tc := range cases {
+		// Initialize the PromQL engine once for all benchmarks.
+		opts := promql.EngineOpts{
+			Logger:               nil,
+			Reg:                  nil,
+			MaxSamples:           50000000,
+			Timeout:              100 * time.Second,
+			EnableAtModifier:     true,
+			EnableNegativeOffset: true,
+		}
+		engine := promql.NewEngine(opts)
+		b.Run(tc.name, func(b *testing.B) {
+			b.ResetTimer()
+			for i := 0; i < b.N; i++ {
+				b.StopTimer() // Stop the timer to exclude setup time.
+				qry, err := engine.NewRangeQuery(context.Background(), testStorage, nil, tc.query, start, end, step)
+				require.NoError(b, err)
+				b.StartTimer()
+				result := qry.Exec(context.Background())
+				require.NoError(b, result.Err)
+			}
+		})
+	}
+
+	// Report allocations.
+	b.ReportAllocs()
+}
+
+// Helper function to generate target_info and http_server_request_duration_seconds_count series for info function benchmarking.
+func generateInfoFunctionTestSeries(tb testing.TB, stor *teststorage.TestStorage, infoSeriesNum, interval, numIntervals int) {
+	tb.Helper()
+
+	ctx := context.Background()
+	statusCodes := []string{"200", "400", "500"}
+
+	// Generate target_info metrics with instance and job labels, and k8s_cluster_name label.
+	// Generate http_server_request_duration_seconds_count metrics with instance and job labels, and http_status_code label.
+	// the classic target_info metrics is gauge type.
+	metrics := make([]labels.Labels, 0, infoSeriesNum+len(statusCodes))
+	for i := 0; i < infoSeriesNum; i++ {
+		clusterName := "us-east"
+		if i >= infoSeriesNum/2 {
+			clusterName = "eu-south"
+		}
+		metrics = append(metrics, labels.FromStrings(
+			"__name__", "target_info",
+			"instance", "instance"+strconv.Itoa(i),
+			"job", "job"+strconv.Itoa(i),
+			"k8s_cluster_name", clusterName,
+		))
+	}
+
+	for _, statusCode := range statusCodes {
+		metrics = append(metrics, labels.FromStrings(
+			"__name__", "http_server_request_duration_seconds_count",
+			"instance", "instance0",
+			"job", "job0",
+			"http_status_code", statusCode,
+		))
+	}
+
+	// Append the generated metrics and samples to the storage.
+	refs := make([]storage.SeriesRef, len(metrics))
+
+	for i := 0; i < numIntervals; i++ {
+		a := stor.Appender(context.Background())
+		ts := int64(i * interval)
+		for j, metric := range metrics[:infoSeriesNum] {
+			ref, _ := a.Append(refs[j], metric, ts, 1)
+			refs[j] = ref
+		}
+
+		for j, metric := range metrics[infoSeriesNum:] {
+			ref, _ := a.Append(refs[j+infoSeriesNum], metric, ts, float64(i))
+			refs[j+infoSeriesNum] = ref
+		}
+
+		require.NoError(tb, a.Commit())
+	}
+
+	stor.DB.ForceHeadMMap() // Ensure we have at most one head chunk for every series.
+	stor.DB.Compact(ctx)
+}
+
 func generateNativeHistogramSeries(app storage.Appender, numSeries int) error {
 	commonLabels := []string{labels.MetricName, "native_histogram_series", "foo", "bar"}
 	series := make([][]*histogram.Histogram, numSeries)

promql/engine.go

@@ -734,6 +734,7 @@ func (ng *Engine) execEvalStmt(ctx context.Context, query *query, s *parser.Eval
 			samplesStats:             query.sampleStats,
 			noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
 			enableDelayedNameRemoval: ng.enableDelayedNameRemoval,
+			querier:                  querier,
 		}
 		query.sampleStats.InitStepTracking(start, start, 1)
 
@@ -792,6 +793,7 @@ func (ng *Engine) execEvalStmt(ctx context.Context, query *query, s *parser.Eval
 		samplesStats:             query.sampleStats,
 		noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
 		enableDelayedNameRemoval: ng.enableDelayedNameRemoval,
+		querier:                  querier,
 	}
 	query.sampleStats.InitStepTracking(evaluator.startTimestamp, evaluator.endTimestamp, evaluator.interval)
 	val, warnings, err := evaluator.Eval(ctxInnerEval, s.Expr)
@@ -1058,6 +1060,7 @@ type evaluator struct {
 	samplesStats             *stats.QuerySamples
 	noStepSubqueryIntervalFn func(rangeMillis int64) int64
 	enableDelayedNameRemoval bool
+	querier                  storage.Querier
 }
 
 // errorf causes a panic with the input formatted into an error.
@@ -1430,19 +1433,18 @@ func (ev *evaluator) rangeEvalAgg(ctx context.Context, aggExpr *parser.Aggregate
 	return result, warnings
 }
 
-// evalVectorSelector generates a Matrix between ev.startTimestamp and ev.endTimestamp (inclusive), each point spaced ev.interval apart, from vs.
+// evalSeries generates a Matrix between ev.startTimestamp and ev.endTimestamp (inclusive), each point spaced ev.interval apart, from series given offset.
-// vs.Series has to be expanded before calling this method.
+// For every storage.Series iterator in series, the method iterates in ev.interval sized steps from ev.startTimestamp until and including ev.endTimestamp,
-// For every series iterator in vs.Series, the method iterates in ev.interval sized steps from ev.startTimestamp until and including ev.endTimestamp,
 // collecting every corresponding sample (obtained via ev.vectorSelectorSingle) into a Series.
 // All of the generated Series are collected into a Matrix, that gets returned.
-func (ev *evaluator) evalVectorSelector(ctx context.Context, vs *parser.VectorSelector) Matrix {
+func (ev *evaluator) evalSeries(ctx context.Context, series []storage.Series, offset time.Duration, recordOrigT bool) Matrix {
 	numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
 
-	mat := make(Matrix, 0, len(vs.Series))
+	mat := make(Matrix, 0, len(series))
 	var prevSS *Series
 	it := storage.NewMemoizedEmptyIterator(durationMilliseconds(ev.lookbackDelta))
 	var chkIter chunkenc.Iterator
-	for _, s := range vs.Series {
+	for _, s := range series {
 		if err := contextDone(ctx, "expression evaluation"); err != nil {
 			ev.error(err)
 		}
@@ -1455,7 +1457,7 @@ func (ev *evaluator) evalVectorSelector(ctx context.Context, vs *parser.VectorSe
 
 		for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts += ev.interval {
 			step++
-			_, f, h, ok := ev.vectorSelectorSingle(it, vs, ts)
+			origT, f, h, ok := ev.vectorSelectorSingle(it, offset, ts)
 			if !ok {
 				continue
 			}
@@ -1469,8 +1471,18 @@ func (ev *evaluator) evalVectorSelector(ctx context.Context, vs *parser.VectorSe
 				if ss.Floats == nil {
 					ss.Floats = reuseOrGetFPointSlices(prevSS, numSteps)
 				}
+				if recordOrigT {
+					// This is an info metric, where we want to track the original sample timestamp.
+					// Info metric values should be 1 by convention, therefore we can re-use this
+					// space in the sample.
+					f = float64(origT)
+				}
 				ss.Floats = append(ss.Floats, FPoint{F: f, T: ts})
 			} else {
+				if recordOrigT {
+					ev.error(fmt.Errorf("this should be an info metric, with float samples: %s", ss.Metric))
+				}
+
 				point := HPoint{H: h, T: ts}
 				histSize := point.size()
 				ev.currentSamples += histSize
@@ -1640,6 +1652,8 @@ func (ev *evaluator) eval(ctx context.Context, expr parser.Expr) (parser.Value,
 			return ev.evalLabelReplace(ctx, e.Args)
 		case "label_join":
 			return ev.evalLabelJoin(ctx, e.Args)
+		case "info":
+			return ev.evalInfo(ctx, e.Args)
 		}
 
 		if !matrixArg {
@@ -1932,7 +1946,7 @@ func (ev *evaluator) eval(ctx context.Context, expr parser.Expr) (parser.Value,
 		if err != nil {
 			ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), ws})
 		}
-		mat := ev.evalVectorSelector(ctx, e)
+		mat := ev.evalSeries(ctx, e.Series, e.Offset, false)
 		return mat, ws
 
 	case *parser.MatrixSelector:
@@ -1953,6 +1967,7 @@ func (ev *evaluator) eval(ctx context.Context, expr parser.Expr) (parser.Value,
 			samplesStats:             ev.samplesStats.NewChild(),
 			noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
 			enableDelayedNameRemoval: ev.enableDelayedNameRemoval,
+			querier:                  ev.querier,
 		}
 
 		if e.Step != 0 {
@@ -1997,6 +2012,7 @@ func (ev *evaluator) eval(ctx context.Context, expr parser.Expr) (parser.Value,
 			samplesStats:             ev.samplesStats.NewChild(),
 			noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
 			enableDelayedNameRemoval: ev.enableDelayedNameRemoval,
+			querier:                  ev.querier,
 		}
 		res, ws := newEv.eval(ctx, e.Expr)
 		ev.currentSamples = newEv.currentSamples
@@ -2097,7 +2113,7 @@ func (ev *evaluator) rangeEvalTimestampFunctionOverVectorSelector(ctx context.Co
 		vec := make(Vector, 0, len(vs.Series))
 		for i, s := range vs.Series {
 			it := seriesIterators[i]
-			t, _, _, ok := ev.vectorSelectorSingle(it, vs, enh.Ts)
+			t, _, _, ok := ev.vectorSelectorSingle(it, vs.Offset, enh.Ts)
 			if !ok {
 				continue
 			}
@@ -2121,10 +2137,10 @@ func (ev *evaluator) rangeEvalTimestampFunctionOverVectorSelector(ctx context.Co
 }
 
 // vectorSelectorSingle evaluates an instant vector for the iterator of one time series.
-func (ev *evaluator) vectorSelectorSingle(it *storage.MemoizedSeriesIterator, node *parser.VectorSelector, ts int64) (
+func (ev *evaluator) vectorSelectorSingle(it *storage.MemoizedSeriesIterator, offset time.Duration, ts int64) (
 	int64, float64, *histogram.FloatHistogram, bool,
 ) {
-	refTime := ts - durationMilliseconds(node.Offset)
+	refTime := ts - durationMilliseconds(offset)
 	var t int64
 	var v float64
 	var h *histogram.FloatHistogram

promql/functions.go

@@ -1677,6 +1677,7 @@ var FunctionCalls = map[string]FunctionCall{
 	"hour":               funcHour,
 	"idelta":             funcIdelta,
 	"increase":           funcIncrease,
+	"info":               nil,
 	"irate":              funcIrate,
 	"label_replace":      funcLabelReplace,
 	"label_join":         funcLabelJoin,

promql/info.go

@@ -0,0 +1,454 @@
+// Copyright 2024 The Prometheus Authors
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package promql
+
+import (
+	"context"
+	"errors"
+	"fmt"
+	"slices"
+	"strings"
+
+	"github.com/grafana/regexp"
+
+	"github.com/prometheus/prometheus/model/labels"
+	"github.com/prometheus/prometheus/promql/parser"
+	"github.com/prometheus/prometheus/storage"
+	"github.com/prometheus/prometheus/util/annotations"
+)
+
+const targetInfo = "target_info"
+
+// identifyingLabels are the labels we consider as identifying for info metrics.
+// Currently hard coded, so we don't need knowledge of individual info metrics.
+var identifyingLabels = []string{"instance", "job"}
+
+// evalInfo implements the info PromQL function.
+func (ev *evaluator) evalInfo(ctx context.Context, args parser.Expressions) (parser.Value, annotations.Annotations) {
+	val, annots := ev.eval(ctx, args[0])
+	mat := val.(Matrix)
+	// Map from data label name to matchers.
+	dataLabelMatchers := map[string][]*labels.Matcher{}
+	var infoNameMatchers []*labels.Matcher
+	if len(args) > 1 {
+		// TODO: Introduce a dedicated LabelSelector type.
+		labelSelector := args[1].(*parser.VectorSelector)
+		for _, m := range labelSelector.LabelMatchers {
+			dataLabelMatchers[m.Name] = append(dataLabelMatchers[m.Name], m)
+			if m.Name == labels.MetricName {
+				infoNameMatchers = append(infoNameMatchers, m)
+			}
+		}
+	} else {
+		infoNameMatchers = []*labels.Matcher{labels.MustNewMatcher(labels.MatchEqual, labels.MetricName, targetInfo)}
+	}
+
+	// Don't try to enrich info series.
+	ignoreSeries := map[int]struct{}{}
+loop:
+	for i, s := range mat {
+		name := s.Metric.Get(labels.MetricName)
+		for _, m := range infoNameMatchers {
+			if m.Matches(name) {
+				ignoreSeries[i] = struct{}{}
+				continue loop
+			}
+		}
+	}
+
+	selectHints := ev.infoSelectHints(args[0])
+	infoSeries, ws, err := ev.fetchInfoSeries(ctx, mat, ignoreSeries, dataLabelMatchers, selectHints)
+	if err != nil {
+		ev.error(err)
+	}
+	annots.Merge(ws)
+
+	res, ws := ev.combineWithInfoSeries(ctx, mat, infoSeries, ignoreSeries, dataLabelMatchers)
+	annots.Merge(ws)
+	return res, annots
+}
+
+// infoSelectHints calculates the storage.SelectHints for selecting info series, given expr (first argument to info call).
+func (ev *evaluator) infoSelectHints(expr parser.Expr) storage.SelectHints {
+	var nodeTimestamp *int64
+	var offset int64
+	parser.Inspect(expr, func(node parser.Node, path []parser.Node) error {
+		switch n := node.(type) {
+		case *parser.VectorSelector:
+			if n.Timestamp != nil {
+				nodeTimestamp = n.Timestamp
+			}
+			offset = durationMilliseconds(n.OriginalOffset)
+			return fmt.Errorf("end traversal")
+		default:
+			return nil
+		}
+	})
+
+	start := ev.startTimestamp
+	end := ev.endTimestamp
+	if nodeTimestamp != nil {
+		// The timestamp on the selector overrides everything.
+		start = *nodeTimestamp
+		end = *nodeTimestamp
+	}
+	// Reduce the start by one fewer ms than the lookback delta
+	// because wo want to exclude samples that are precisely the
+	// lookback delta before the eval time.
+	start -= durationMilliseconds(ev.lookbackDelta) - 1
+	start -= offset
+	end -= offset
+
+	return storage.SelectHints{
+		Start: start,
+		End:   end,
+		Step:  ev.interval,
+		Func:  "info",
+	}
+}
+
+// fetchInfoSeries fetches info series given matching identifying labels in mat.
+// Series in ignoreSeries are not fetched.
+// dataLabelMatchers may be mutated.
+func (ev *evaluator) fetchInfoSeries(ctx context.Context, mat Matrix, ignoreSeries map[int]struct{}, dataLabelMatchers map[string][]*labels.Matcher, selectHints storage.SelectHints) (Matrix, annotations.Annotations, error) {
+	// A map of values for all identifying labels we are interested in.
+	idLblValues := map[string]map[string]struct{}{}
+	for i, s := range mat {
+		if _, exists := ignoreSeries[i]; exists {
+			continue
+		}
+
+		// Register relevant values per identifying label for this series.
+		for _, l := range identifyingLabels {
+			val := s.Metric.Get(l)
+			if val == "" {
+				continue
+			}
+
+			if idLblValues[l] == nil {
+				idLblValues[l] = map[string]struct{}{}
+			}
+			idLblValues[l][val] = struct{}{}
+		}
+	}
+	if len(idLblValues) == 0 {
+		return nil, nil, nil
+	}
+
+	// Generate regexps for every interesting value per identifying label.
+	var sb strings.Builder
+	idLblRegexps := make(map[string]string, len(idLblValues))
+	for name, vals := range idLblValues {
+		sb.Reset()
+		i := 0
+		for v := range vals {
+			if i > 0 {
+				sb.WriteRune('|')
+			}
+			sb.WriteString(regexp.QuoteMeta(v))
+			i++
+		}
+		idLblRegexps[name] = sb.String()
+	}
+
+	var infoLabelMatchers []*labels.Matcher
+	for name, re := range idLblRegexps {
+		infoLabelMatchers = append(infoLabelMatchers, labels.MustNewMatcher(labels.MatchRegexp, name, re))
+	}
+	var nameMatcher *labels.Matcher
+	for name, ms := range dataLabelMatchers {
+		for i, m := range ms {
+			if m.Name == labels.MetricName {
+				nameMatcher = m
+				ms = slices.Delete(ms, i, i+1)
+			}
+			infoLabelMatchers = append(infoLabelMatchers, m)
+		}
+		if len(ms) > 0 {
+			dataLabelMatchers[name] = ms
+		} else {
+			delete(dataLabelMatchers, name)
+		}
+	}
+	if nameMatcher == nil {
+		// Default to using the target_info metric.
+		infoLabelMatchers = append([]*labels.Matcher{labels.MustNewMatcher(labels.MatchEqual, labels.MetricName, targetInfo)}, infoLabelMatchers...)
+	}
+
+	infoIt := ev.querier.Select(ctx, false, &selectHints, infoLabelMatchers...)
+	infoSeries, ws, err := expandSeriesSet(ctx, infoIt)
+	if err != nil {
+		return nil, ws, err
+	}
+
+	infoMat := ev.evalSeries(ctx, infoSeries, 0, true)
+	return infoMat, ws, nil
+}
+
+// combineWithInfoSeries combines mat with select data labels from infoMat.
+func (ev *evaluator) combineWithInfoSeries(ctx context.Context, mat, infoMat Matrix, ignoreSeries map[int]struct{}, dataLabelMatchers map[string][]*labels.Matcher) (Matrix, annotations.Annotations) {
+	buf := make([]byte, 0, 1024)
+	lb := labels.NewScratchBuilder(0)
+	sigFunction := func(name string) func(labels.Labels) string {
+		return func(lset labels.Labels) string {
+			lb.Reset()
+			lb.Add(labels.MetricName, name)
+			lset.MatchLabels(true, identifyingLabels...).Range(func(l labels.Label) {
+				lb.Add(l.Name, l.Value)
+			})
+			lb.Sort()
+			return string(lb.Labels().Bytes(buf))
+		}
+	}
+
+	infoMetrics := map[string]struct{}{}
+	for _, is := range infoMat {
+		lblMap := is.Metric.Map()
+		infoMetrics[lblMap[labels.MetricName]] = struct{}{}
+	}
+	sigfs := make(map[string]func(labels.Labels) string, len(infoMetrics))
+	for name := range infoMetrics {
+		sigfs[name] = sigFunction(name)
+	}
+
+	// Keep a copy of the original point slices so they can be returned to the pool.
+	origMatrices := []Matrix{
+		make(Matrix, len(mat)),
+		make(Matrix, len(infoMat)),
+	}
+	copy(origMatrices[0], mat)
+	copy(origMatrices[1], infoMat)
+
+	numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
+	originalNumSamples := ev.currentSamples
+
+	// Create an output vector that is as big as the input matrix with
+	// the most time series.
+	biggestLen := max(len(mat), len(infoMat))
+	baseVector := make(Vector, 0, len(mat))
+	infoVector := make(Vector, 0, len(infoMat))
+	enh := &EvalNodeHelper{
+		Out: make(Vector, 0, biggestLen),
+	}
+	type seriesAndTimestamp struct {
+		Series
+		ts int64
+	}
+	seriess := make(map[uint64]seriesAndTimestamp, biggestLen) // Output series by series hash.
+	tempNumSamples := ev.currentSamples
+
+	// For every base series, compute signature per info metric.
+	baseSigs := make([]map[string]string, 0, len(mat))
+	for _, s := range mat {
+		sigs := make(map[string]string, len(infoMetrics))
+		for infoName := range infoMetrics {
+			sigs[infoName] = sigfs[infoName](s.Metric)
+		}
+		baseSigs = append(baseSigs, sigs)
+	}
+
+	infoSigs := make([]string, 0, len(infoMat))
+	for _, s := range infoMat {
+		name := s.Metric.Map()[labels.MetricName]
+		infoSigs = append(infoSigs, sigfs[name](s.Metric))
+	}
+
+	var warnings annotations.Annotations
+	for ts := ev.startTimestamp; ts <= ev.endTimestamp; ts += ev.interval {
+		if err := contextDone(ctx, "expression evaluation"); err != nil {
+			ev.error(err)
+		}
+
+		// Reset number of samples in memory after each timestamp.
+		ev.currentSamples = tempNumSamples
+		// Gather input vectors for this timestamp.
+		baseVector, _ = ev.gatherVector(ts, mat, baseVector, nil, nil)
+		infoVector, _ = ev.gatherVector(ts, infoMat, infoVector, nil, nil)
+
+		enh.Ts = ts
+		result, err := ev.combineWithInfoVector(baseVector, infoVector, ignoreSeries, baseSigs, infoSigs, enh, dataLabelMatchers)
+		if err != nil {
+			ev.error(err)
+		}
+		enh.Out = result[:0] // Reuse result vector.
+
+		vecNumSamples := result.TotalSamples()
+		ev.currentSamples += vecNumSamples
+		// When we reset currentSamples to tempNumSamples during the next iteration of the loop it also
+		// needs to include the samples from the result here, as they're still in memory.
+		tempNumSamples += vecNumSamples
+		ev.samplesStats.UpdatePeak(ev.currentSamples)
+		if ev.currentSamples > ev.maxSamples {
+			ev.error(ErrTooManySamples(env))
+		}
+
+		// Add samples in result vector to output series.
+		for _, sample := range result {
+			h := sample.Metric.Hash()
+			ss, exists := seriess[h]
+			if exists {
+				if ss.ts == ts { // If we've seen this output series before at this timestamp, it's a duplicate.
+					ev.errorf("vector cannot contain metrics with the same labelset")
+				}
+				ss.ts = ts
+			} else {
+				ss = seriesAndTimestamp{Series{Metric: sample.Metric}, ts}
+			}
+			addToSeries(&ss.Series, enh.Ts, sample.F, sample.H, numSteps)
+			seriess[h] = ss
+		}
+	}
+
+	// Reuse the original point slices.
+	for _, m := range origMatrices {
+		for _, s := range m {
+			putFPointSlice(s.Floats)
+			putHPointSlice(s.Histograms)
+		}
+	}
+	// Assemble the output matrix. By the time we get here we know we don't have too many samples.
+	numSamples := 0
+	output := make(Matrix, 0, len(seriess))
+	for _, ss := range seriess {
+		numSamples += len(ss.Floats) + totalHPointSize(ss.Histograms)
+		output = append(output, ss.Series)
+	}
+	ev.currentSamples = originalNumSamples + numSamples
+	ev.samplesStats.UpdatePeak(ev.currentSamples)
+	return output, warnings
+}
+
+// combineWithInfoVector combines base and info Vectors.
+// Base series in ignoreSeries are not combined.
+func (ev *evaluator) combineWithInfoVector(base, info Vector, ignoreSeries map[int]struct{}, baseSigs []map[string]string, infoSigs []string, enh *EvalNodeHelper, dataLabelMatchers map[string][]*labels.Matcher) (Vector, error) {
+	if len(base) == 0 {
+		return nil, nil // Short-circuit: nothing is going to match.
+	}
+
+	// All samples from the info Vector hashed by the matching label/values.
+	if enh.rightSigs == nil {
+		enh.rightSigs = make(map[string]Sample, len(enh.Out))
+	} else {
+		clear(enh.rightSigs)
+	}
+
+	for i, s := range info {
+		if s.H != nil {
+			ev.error(errors.New("info sample should be float"))
+		}
+		// We encode original info sample timestamps via the float value.
+		origT := int64(s.F)
+
+		sig := infoSigs[i]
+		if existing, exists := enh.rightSigs[sig]; exists {
+			// We encode original info sample timestamps via the float value.
+			existingOrigT := int64(existing.F)
+			switch {
+			case existingOrigT > origT:
+				// Keep the other info sample, since it's newer.
+			case existingOrigT < origT:
+				// Keep this info sample, since it's newer.
+				enh.rightSigs[sig] = s
+			default:
+				// The two info samples have the same timestamp - conflict.
+				name := s.Metric.Map()[labels.MetricName]
+				ev.errorf("found duplicate series for info metric %s", name)
+			}
+		} else {
+			enh.rightSigs[sig] = s
+		}
+	}
+
+	for i, bs := range base {
+		if _, exists := ignoreSeries[i]; exists {
+			// This series should not be enriched with info metric data labels.
+			enh.Out = append(enh.Out, Sample{
+				Metric: bs.Metric,
+				F:      bs.F,
+				H:      bs.H,
+			})
+			continue
+		}
+
+		baseLabels := bs.Metric.Map()
+		enh.resetBuilder(labels.Labels{})
+
+		// For every info metric name, try to find an info series with the same signature.
+		seenInfoMetrics := map[string]struct{}{}
+		for infoName, sig := range baseSigs[i] {
+			is, exists := enh.rightSigs[sig]
+			if !exists {
+				continue
+			}
+			if _, exists := seenInfoMetrics[infoName]; exists {
+				continue
+			}
+
+			err := is.Metric.Validate(func(l labels.Label) error {
+				if l.Name == labels.MetricName {
+					return nil
+				}
+				if _, exists := dataLabelMatchers[l.Name]; len(dataLabelMatchers) > 0 && !exists {
+					// Not among the specified data label matchers.
+					return nil
+				}
+
+				if v := enh.lb.Get(l.Name); v != "" && v != l.Value {
+					return fmt.Errorf("conflicting label: %s", l.Name)
+				}
+				if _, exists := baseLabels[l.Name]; exists {
+					// Skip labels already on the base metric.
+					return nil
+				}
+
+				enh.lb.Set(l.Name, l.Value)
+				return nil
+			})
+			if err != nil {
+				return nil, err
+			}
+			seenInfoMetrics[infoName] = struct{}{}
+		}
+
+		infoLbls := enh.lb.Labels()
+		if infoLbls.Len() == 0 {
+			// If there's at least one data label matcher not matching the empty string,
+			// we have to ignore this series as there are no matching info series.
+			allMatchersMatchEmpty := true
+			for _, ms := range dataLabelMatchers {
+				for _, m := range ms {
+					if !m.Matches("") {
+						allMatchersMatchEmpty = false
+						break
+					}
+				}
+			}
+			if !allMatchersMatchEmpty {
+				continue
+			}
+		}
+
+		enh.resetBuilder(bs.Metric)
+		infoLbls.Range(func(l labels.Label) {
+			enh.lb.Set(l.Name, l.Value)
+		})
+
+		enh.Out = append(enh.Out, Sample{
+			Metric: enh.lb.Labels(),
+			F:      bs.F,
+			H:      bs.H,
+		})
+	}
+	return enh.Out, nil
+}

promql/info_test.go

@@ -0,0 +1,140 @@
+// Copyright 2024 The Prometheus Authors
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package promql_test
+
+import (
+	"testing"
+
+	"github.com/prometheus/prometheus/promql/promqltest"
+)
+
+// The "info" function is experimental. This is why we write those tests here for now instead of promqltest/testdata/info.test.
+func TestInfo(t *testing.T) {
+	engine := promqltest.NewTestEngine(t, false, 0, promqltest.DefaultMaxSamplesPerQuery)
+	promqltest.RunTest(t, `
+load 5m
+  metric{instance="a", job="1", label="value"} 0 1 2
+  metric_not_matching_target_info{instance="a", job="2", label="value"} 0 1 2
+  metric_with_overlapping_label{instance="a", job="1", label="value", data="base"} 0 1 2
+  target_info{instance="a", job="1", data="info", another_data="another info"} 1 1 1
+  build_info{instance="a", job="1", build_data="build"} 1 1 1
+
+# Include one info metric data label.
+eval range from 0m to 10m step 5m info(metric, {data=~".+"})
+  metric{data="info", instance="a", job="1", label="value"} 0 1 2
+
+# Include all info metric data labels.
+eval range from 0m to 10m step 5m info(metric)
+  metric{data="info", instance="a", job="1", label="value", another_data="another info"} 0 1 2
+
+# Try including all info metric data labels, but non-matching identifying labels.
+eval range from 0m to 10m step 5m info(metric_not_matching_target_info)
+  metric_not_matching_target_info{instance="a", job="2", label="value"} 0 1 2
+
+# Try including a certain info metric data label with a non-matching matcher not accepting empty labels.
+# Metric is ignored, due there being a data label matcher not matching empty labels,
+# and there being no info series matches.
+eval range from 0m to 10m step 5m info(metric, {non_existent=~".+"})
+
+# Include a certain info metric data label together with a non-matching matcher accepting empty labels.
+# Since the non_existent matcher matches empty labels, it's simply ignored when there's no match.
+# XXX: This case has to include a matcher not matching empty labels, due the PromQL limitation
+# that vector selectors have to contain at least one matcher not accepting empty labels.
+# We might need another construct than vector selector to get around this limitation.
+eval range from 0m to 10m step 5m info(metric, {data=~".+", non_existent=~".*"})
+  metric{data="info", instance="a", job="1", label="value"} 0 1 2
+
+# Info series data labels overlapping with those of base series are ignored.
+eval range from 0m to 10m step 5m info(metric_with_overlapping_label)
+  metric_with_overlapping_label{data="base", instance="a", job="1", label="value", another_data="another info"} 0 1 2
+
+# Include data labels from target_info specifically.
+eval range from 0m to 10m step 5m info(metric, {__name__="target_info"})
+  metric{data="info", instance="a", job="1", label="value", another_data="another info"} 0 1 2
+
+# Try to include all data labels from a non-existent info metric.
+eval range from 0m to 10m step 5m info(metric, {__name__="non_existent"})
+  metric{instance="a", job="1", label="value"} 0 1 2
+
+# Try to include a certain data label from a non-existent info metric.
+eval range from 0m to 10m step 5m info(metric, {__name__="non_existent", data=~".+"})
+
+# Include data labels from build_info.
+eval range from 0m to 10m step 5m info(metric, {__name__="build_info"})
+  metric{instance="a", job="1", label="value", build_data="build"} 0 1 2
+
+# Include data labels from build_info and target_info.
+eval range from 0m to 10m step 5m info(metric, {__name__=~".+_info"})
+  metric{instance="a", job="1", label="value", build_data="build", data="info", another_data="another info"} 0 1 2
+
+# Info metrics themselves are ignored when it comes to enriching with info metric data labels.
+eval range from 0m to 10m step 5m info(build_info, {__name__=~".+_info", build_data=~".+"})
+  build_info{instance="a", job="1", build_data="build"} 1 1 1
+
+clear
+
+# Overlapping target_info series.
+load 5m
+  metric{instance="a", job="1", label="value"} 0 1 2
+  target_info{instance="a", job="1", data="info", another_data="another info"} 1 1 _
+  target_info{instance="a", job="1", data="updated info", another_data="another info"} _ _ 1
+
+# Conflicting info series are resolved through picking the latest sample.
+eval range from 0m to 10m step 5m info(metric)
+  metric{data="info", instance="a", job="1", label="value", another_data="another info"} 0 1 _
+  metric{data="updated info", instance="a", job="1", label="value", another_data="another info"} _ _ 2
+
+clear
+
+# Non-overlapping target_info series.
+load 5m
+  metric{instance="a", job="1", label="value"} 0 1 2
+  target_info{instance="a", job="1", data="info"} 1 1 stale
+  target_info{instance="a", job="1", data="updated info"} _ _ 1
+
+# Include info metric data labels from a metric which data labels change over time.
+eval range from 0m to 10m step 5m info(metric)
+  metric{data="info", instance="a", job="1", label="value"} 0 1 _
+  metric{data="updated info", instance="a", job="1", label="value"} _ _ 2
+
+clear
+
+# Info series selector matches histogram series, info metrics should be float type.
+load 5m
+  metric{instance="a", job="1", label="value"} 0 1 2
+  histogram{instance="a", job="1"} {{schema:1 sum:3 count:22 buckets:[5 10 7]}}
+
+eval_fail range from 0m to 10m step 5m info(metric, {__name__="histogram"})
+
+clear
+
+# Series with skipped scrape.
+load 1m
+  metric{instance="a", job="1", label="value"} 0 _ 2 3 4
+  target_info{instance="a", job="1", data="info"} 1 _ 1 1 1
+
+# Lookback works also for the info series.
+eval range from 1m to 4m step 1m info(metric)
+  metric{data="info", instance="a", job="1", label="value"} 0 2 3 4
+
+# @ operator works also with info.
+# Note that we pick the timestamp missing a sample, lookback should pick previous sample.
+eval range from 1m to 4m step 1m info(metric @ 60)
+  metric{data="info", instance="a", job="1", label="value"} 0 0 0 0
+
+# offset operator works also with info.
+eval range from 1m to 4m step 1m info(metric offset 1m)
+  metric{data="info", instance="a", job="1", label="value"} 0 0 2 3
+`, engine)
+}

promql/parser/ast.go

@@ -208,6 +208,10 @@ type VectorSelector struct {
 	UnexpandedSeriesSet storage.SeriesSet
 	Series              []storage.Series
 
+	// BypassEmptyMatcherCheck is true when the VectorSelector isn't required to have at least one matcher matching the empty string.
+	// This is the case when VectorSelector is used to represent the info function's second argument.
+	BypassEmptyMatcherCheck bool
+
 	PosRange posrange.PositionRange
 }
 

promql/parser/functions.go

@@ -223,6 +223,13 @@ var Functions = map[string]*Function{
 		ArgTypes:   []ValueType{ValueTypeMatrix},
 		ReturnType: ValueTypeVector,
 	},
+	"info": {
+		Name:         "info",
+		ArgTypes:     []ValueType{ValueTypeVector, ValueTypeVector},
+		ReturnType:   ValueTypeVector,
+		Experimental: true,
+		Variadic:     1,
+	},
 	"irate": {
 		Name:       "irate",
 		ArgTypes:   []ValueType{ValueTypeMatrix},

promql/parser/parse.go

@@ -784,6 +784,19 @@ func (p *parser) checkAST(node Node) (typ ValueType) {
 			}
 		}
 
+		if n.Func.Name == "info" && len(n.Args) > 1 {
+			// Check the type is correct first
+			if n.Args[1].Type() != ValueTypeVector {
+				p.addParseErrf(node.PositionRange(), "expected type %s in %s, got %s", DocumentedType(ValueTypeVector), fmt.Sprintf("call to function %q", n.Func.Name), DocumentedType(n.Args[1].Type()))
+			}
+			// Check the vector selector in the input doesn't contain a metric name
+			if n.Args[1].(*VectorSelector).Name != "" {
+				p.addParseErrf(n.Args[1].PositionRange(), "expected label selectors only, got vector selector instead")
+			}
+			// Set Vector Selector flag to bypass empty matcher check
+			n.Args[1].(*VectorSelector).BypassEmptyMatcherCheck = true
+		}
+
 		for i, arg := range n.Args {
 			if i >= len(n.Func.ArgTypes) {
 				if n.Func.Variadic == 0 {
@@ -830,17 +843,19 @@ func (p *parser) checkAST(node Node) (typ ValueType) {
 			// metric name is a non-empty matcher.
 			break
 		}
-		// A Vector selector must contain at least one non-empty matcher to prevent
+		if !n.BypassEmptyMatcherCheck {
-		// implicit selection of all metrics (e.g. by a typo).
+			// A Vector selector must contain at least one non-empty matcher to prevent
-		notEmpty := false
+			// implicit selection of all metrics (e.g. by a typo).
-		for _, lm := range n.LabelMatchers {
+			notEmpty := false
-			if lm != nil && !lm.Matches("") {
+			for _, lm := range n.LabelMatchers {
-				notEmpty = true
+				if lm != nil && !lm.Matches("") {
-				break
+					notEmpty = true
+					break
+				}
+			}
+			if !notEmpty {
+				p.addParseErrf(n.PositionRange(), "vector selector must contain at least one non-empty matcher")
 			}
-		}
-		if !notEmpty {
-			p.addParseErrf(n.PositionRange(), "vector selector must contain at least one non-empty matcher")
 		}
 
 	case *NumberLiteral, *StringLiteral:

promql/parser/parse_test.go

@@ -3872,6 +3872,81 @@ var testExpr = []struct {
 			},
 		},
 	},
+	{
+		input: `info(rate(http_request_counter_total{}[5m]))`,
+		expected: &Call{
+			Func: MustGetFunction("info"),
+			Args: Expressions{
+				&Call{
+					Func: MustGetFunction("rate"),
+					PosRange: posrange.PositionRange{
+						Start: 5,
+						End:   43,
+					},
+					Args: Expressions{
+						&MatrixSelector{
+							VectorSelector: &VectorSelector{
+								Name:           "http_request_counter_total",
+								OriginalOffset: 0,
+								LabelMatchers: []*labels.Matcher{
+									MustLabelMatcher(labels.MatchEqual, model.MetricNameLabel, "http_request_counter_total"),
+								},
+								PosRange: posrange.PositionRange{
+									Start: 10,
+									End:   38,
+								},
+							},
+							EndPos: 42,
+							Range:  5 * time.Minute,
+						},
+					},
+				},
+			},
+			PosRange: posrange.PositionRange{
+				Start: 0,
+				End:   44,
+			},
+		},
+	},
+	{
+		input:  `info(rate(http_request_counter_total{}[5m]), target_info{foo="bar"})`,
+		fail:   true,
+		errMsg: `1:46: parse error: expected label selectors only, got vector selector instead`,
+	},
+	{
+		input: `info(http_request_counter_total{namespace="zzz"}, {foo="bar", bar="baz"})`,
+		expected: &Call{
+			Func: MustGetFunction("info"),
+			Args: Expressions{
+				&VectorSelector{
+					Name: "http_request_counter_total",
+					LabelMatchers: []*labels.Matcher{
+						MustLabelMatcher(labels.MatchEqual, "namespace", "zzz"),
+						MustLabelMatcher(labels.MatchEqual, model.MetricNameLabel, "http_request_counter_total"),
+					},
+					PosRange: posrange.PositionRange{
+						Start: 5,
+						End:   48,
+					},
+				},
+				&VectorSelector{
+					LabelMatchers: []*labels.Matcher{
+						MustLabelMatcher(labels.MatchEqual, "foo", "bar"),
+						MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
+					},
+					PosRange: posrange.PositionRange{
+						Start: 50,
+						End:   72,
+					},
+					BypassEmptyMatcherCheck: true,
+				},
+			},
+			PosRange: posrange.PositionRange{
+				Start: 0,
+				End:   73,
+			},
+		},
+	},
 }
 
 func makeInt64Pointer(val int64) *int64 {
@@ -3889,6 +3964,12 @@ func readable(s string) string {
 }
 
 func TestParseExpressions(t *testing.T) {
+	// Enable experimental functions testing.
+	EnableExperimentalFunctions = true
+	t.Cleanup(func() {
+		EnableExperimentalFunctions = false
+	})
+
 	model.NameValidationScheme = model.UTF8Validation
 	for _, test := range testExpr {
 		t.Run(readable(test.input), func(t *testing.T) {

web/ui/module/codemirror-promql/src/complete/promql.terms.ts

@@ -281,6 +281,12 @@ export const functionIdentifierTerms = [
     info: 'Calculate the increase in value over a range of time (for counters)',
     type: 'function',
   },
+  {
+    label: 'info',
+    detail: 'function',
+    info: 'Add data labels from corresponding info metrics',
+    type: 'function',
+  },
   {
     label: 'irate',
     detail: 'function',

web/ui/module/codemirror-promql/src/parser/parser.test.ts

@@ -968,6 +968,23 @@ describe('promql operations', () => {
       expectedValueType: ValueType.vector,
       expectedDiag: [],
     },
+    {
+      expr: 'info(rate(http_request_counter_total{}[5m]))',
+      expectedValueType: ValueType.vector,
+      expectedDiag: [],
+    },
+    {
+      expr: 'info(rate(http_request_counter_total[5m]), target_info{service_version=~".+"})',
+      expectedValueType: ValueType.vector,
+      expectedDiag: [
+        {
+          from: 0,
+          to: 78,
+          message: `expected label selectors as the second argument to "info" function, got [object Object]`,
+          severity: 'error',
+        },
+      ],
+    },
   ];
   testCases.forEach((value) => {
     const state = createEditorState(value.expr);

web/ui/module/codemirror-promql/src/parser/parser.ts

@@ -275,6 +275,13 @@ export class Parser {
       }
     }
 
+    if (funcSignature.name === 'info') {
+      // Verify that the data label selector expression is not prefixed with metric name.
+      if (args.length > 1 && args[1].getChild(Identifier)) {
+        this.addDiagnostic(node, `expected label selectors as the second argument to "info" function, got ${args[1].type}`);
+      }
+    }
+
     let j = 0;
     for (let i = 0; i < args.length; i++) {
       j = i;

web/ui/module/codemirror-promql/src/types/function.ts

@@ -50,6 +50,7 @@ import {
   Hour,
   Idelta,
   Increase,
+  Info,
   Irate,
   LabelJoin,
   LabelReplace,
@@ -336,6 +337,12 @@ const promqlFunctions: { [key: number]: PromQLFunction } = {
     variadic: 0,
     returnType: ValueType.vector,
   },
+  [Info]: {
+    name: 'info',
+    argTypes: [ValueType.vector, ValueType.vector],
+    variadic: 1,
+    returnType: ValueType.vector,
+  },
   [Irate]: {
     name: 'irate',
     argTypes: [ValueType.matrix],

web/ui/module/lezer-promql/src/promql.grammar

@@ -145,6 +145,7 @@ FunctionIdentifier {
   Hour |
   Idelta |
   Increase |
+  Info |
   Irate |
   LabelReplace |
   LabelJoin |
@@ -392,6 +393,7 @@ NumberDurationLiteralInDurationContext {
   Hour { condFn<"hour"> }
   Idelta { condFn<"idelta"> }
   Increase { condFn<"increase"> }
+  Info { condFn<"info"> }
   Irate { condFn<"irate"> }
   LabelReplace { condFn<"label_replace"> }
   LabelJoin { condFn<"label_join"> }