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feat(om2.0): have one line for classic-native histogram #2863

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feat(om2.0): have one line for classic-native histogram
krajorama Mar 4, 2026
4d91df6
fix(consistency): attempt to implement new multi exemplars wow
krajorama Mar 5, 2026
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85 changes: 53 additions & 32 deletions docs/specs/om/open_metrics_spec_2_0.md
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Original file line number Diff line number Diff line change
Expand Up @@ -283,6 +283,10 @@ If the Histogram Metric has MetricPoints with Classic Buckets, the Histogram's M

The Histogram type is cumulative over time, but MAY be reset. When a Histogram is reset, the Sum, Count, Classic Buckets and Native Buckets MUST be reset to their zero state, and if the Start Timestamp is present then it MUST be set to the approximate reset time. Histogram resets can be useful for limiting the number of Native Buckets used by Histograms.

A Histogram MetricPoint MAY have exemplars. The values of exemplars in a Histogram MetricPoint
SHOULD be evenly distributed, such as by keeping one exemplar for each Classic Bucket if Classic
Buckets are included.

##### Classic Buckets

Every Classic Bucket MUST have a threshold. Classic Bucket thresholds within a MetricPoint MUST be unique. Classic Bucket thresholds MAY be negative.
Expand All @@ -297,8 +301,6 @@ Exposed Classic Bucket thresholds SHOULD stay constant over time and between tar

If the NaN value is allowed, it MUST be counted in the +Inf bucket, and MUST NOT be counted in any other bucket. The rationale is that NaN does not belong to any bucket mathematically, however instrumentation libraries traditionally put it into the +Inf bucket.

A Histogram MetricPoint MAY have exemplars. The values of exemplars in a Histogram MetricPoint SHOULD be evenly distributed, such as by keeping one exemplar for each Classic Bucket.

##### Native Buckets

Histogram MetricPoints with Native Buckets MUST have a Schema value. The Schema MUST be an 8 bit signed integer between -4 and 8 (inclusive), these are called Standard (exponential) schemas.
Expand Down Expand Up @@ -342,10 +344,6 @@ If the NaN value is not allowed, then the Count value MUST be equal to the sum o

If the NaN value is allowed, it MUST NOT be counted in any Native Bucket, and MUST be counted towards the Count. The difference between the Count and the sum of the negative, positive and zero Native Buckets MUST BE the number of NaN observations. The rationale is that NaN does not belong to any bucket mathematically.

A Histogram MetricPoint with Native Buckets MAY contain exemplars.

The values of exemplars in a Histogram MetricPoint with Native Buckets SHOULD be evenly distributed to avoid only representing the bucket with the highest value and therefore most common case.

#### GaugeHistogram

GaugeHistograms measure current distributions. Common examples are how long items have been waiting in a queue, or size of the requests in a queue.
Expand Down Expand Up @@ -518,14 +516,19 @@ normal-char = %x00-09 / %x0B-21 / %x23-5B / %x5D-D7FF / %xE000-10FFFF
start-timestamp = %d115.116 "@" timestamp

; Composite values
composite-value = native-histogram / classic-histogram / classic-summary
composite-value = histogram-value / summary-value

native-histogram = nh-count "," nh-sum "," nh-schema "," nh-zero-threshold "," nh-zero-count [ "," nh-negative-spans "," nh-negative-buckets ] [ "," nh-positive-spans "," nh-positive-buckets ]
; Histograms
histogram-value = h-count "," h-sum "," histogram-buckets

; count:x
nh-count = %d99.111.117.110.116 ":" number
h-count = %d99.111.117.110.116 ":" number
; sum:f allows real numbers and +-Inf and NaN
nh-sum = %d115.117.109 ":" number
h-sum = %d115.117.109 ":" number

histogram-buckets = classic-buckets / native-buckets [ "," classic-buckets ]
native-buckets = nh-schema "," nh-zero-threshold "," nh-zero-count [ "," nh-negative-spans "," nh-negative-buckets ] [ "," nh-positive-spans "," nh-positive-buckets ]

; schema:i
nh-schema = %d115.99.104.101.109.97 ":" integer
; zero_threshold:f
Expand Down Expand Up @@ -553,22 +556,17 @@ non-negative-integer = ["+"] 1*"0" / ["+"] positive-integer
positive-integer = *"0" positive-digit *DIGIT
positive-digit = "1" / "2" / "3" / "4" / "5" / "6" / "7" / "8" / "9"

; count:12,sum:100.0,bucket:[0.1:3,05:12,+Inf:12]
classic-histogram = ch-count "," ch-sum "," ch-bucket

; count:x where x is a number
ch-count = %d99.111.117.110.116 ":" number
; sum:x where x is a number
ch-sum = %d115.117.109 ":" number
; bucket:[...,+Inf:v] The +Inf bucket is required.
ch-bucket = %d98.117.99.107.101.116 ":" "[" [ ch-le-counts "," ] ch-pos-inf-bucket "]"
classic-buckets = %d98.117.99.107.101.116 ":" "[" [ ch-le-counts "," ] ch-pos-inf-bucket "]"
ch-le-counts = (ch-neg-inf-bucket / ch-le-bucket) *("," ch-le-bucket)
ch-pos-inf-bucket = "+" %d73.110.102 ":" number
ch-neg-inf-bucket = "-" %d73.110.102 ":" number
ch-le-bucket = realnumber ":" number

; Summary

; count:12.0,sum:100.0,quantile:[0.9:2.0,0.95:3.0,0.99:20.0]
classic-summary = cs-count "," cs-sum "," cs-quantile
summary-value = cs-count "," cs-sum "," cs-quantile

; count:x where x is a number
cs-count = %d99.111.117.110.116 ":" number
Expand Down Expand Up @@ -610,8 +608,7 @@ process_cpu_seconds_total 4.20072246e+06
# TYPE acme_http_request_seconds histogram
# UNIT acme_http_request_seconds seconds
# HELP acme_http_request_seconds Latency histogram of all of ACME's HTTP requests.
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[1:2],positive_buckets:[1,1]} st@1605301325.0
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,bucket:[0.5:1,1:2,+Inf:2]} st@1605301325.0
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[1:2],positive_buckets:[1,1],bucket:[0.5:1,1:2,+Inf:2]} st@1605301325.0
# TYPE acme_http_request_seconds:rate5m gaugehistogram
acme_http_request_seconds:rate5m{path="/api/v1",method="GET"} {count:0.01,sum:2.0,schema:0,zero_threshold:1e-4,zero_count:0.0,positive_spans:[1:2],positive_buckets:[0.005,0.005]} st@1605301325.0
# TYPE "foodb.read.errors" counter
Expand Down Expand Up @@ -1040,30 +1037,56 @@ acme_http_request_seconds{path="/api/v1",method="GET"} {count:0,sum:0,schema:3,z

##### Histogram with both Classic and Native Buckets

If a Histogram MetricPoint has both Classic and Native buckets, the Sample for the Native Buckets MUST come first.
The MetricPoint's value MUST be a CompositeValue.

The CompositeValue MUST include the Count and Sum as the fields `count`, `sum` in this order.

After the `count` and `sum` the remaining fields of the Native Buckets MUST be included,
then the remaining fields of the Classic Buckets (i.e. the `bucket` field) MUST be included.

The order ensures that implementations can easily skip the Classic Buckets if the Native Buckets are preferred.

```openmetrics-add-eof
# TYPE acme_http_request_seconds histogram
# UNIT acme_http_request_seconds seconds
# HELP acme_http_request_seconds Latency histogram of all of ACME's HTTP requests.
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[1:2],positive_buckets:[1,1]}
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,bucket:[0.5:1,1:2,+Inf:2]}
acme_http_request_seconds{path="/api/v1",method="GET"} {count:2,sum:1.2e2,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[1:2],positive_buckets:[1,1],bucket:[0.5:1,1:2,+Inf:2]}
```

###### Exemplars
###### Exemplars and Start Timestamp

Exemplars MAY be attached to the Histogram MetricPoint.

When present, all Exemplars of the Histogram MetricPoint SHOULD be attached.
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@dashpole dashpole Mar 9, 2026

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Not sure I understand this sentence. It sounds like it means "you should attach all exemplars you have for a histogram regardless of whether they are associated with classic or native buckets", but that clearly isn't what you mean below.

In practice this means that if the exposer is keeping a separate set of exemplars for Classic and Native Buckets, then
the exposer MAY attach only one set for performance and backwards compatibility reasons and that set SHOULD be the
exemplars associated with Classic Buckets.

If present, the MetricPoint's Start Timestamp MUST be inlined with the Metric point with a `st@` prefix. If the value's timestamp is present, the Start Timestamp MUST be added right after it. If exemplars are present, the Start Timestamp MUST be added before it.

Exemplars without Labels MUST represent an empty LabelSet as {}.
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@krajorama krajorama Mar 5, 2026

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Note to reviewers: let's move this to some common place.


An example of Exemplars showcasing several valid cases:
The Histogram Sample with Native Buckets has multiple Exemplars.
The "0.01" bucket has no Exemplar. The 0.1 bucket has an Exemplar with no Labels. The 1 bucket has an Exemplar with one Label. The 10 bucket has an Exemplar with a Label and a timestamp. In practice all buckets SHOULD have the same style of Exemplars.
Exemplars of a MetricPoint SHOULD have the same Label names to have a consistent style.
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@krajorama krajorama Mar 5, 2026

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Note to reviewers: let's move this to some common place.


An example of a Histogram with Native Buckets and Start Timestamp that has multiple Exemplars:

```openmetrics-add-eof
# TYPE foo histogram
foo {count:17,sum:324789.3,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[0:2],positive_buckets:[5,12]} st@1520430000.123 # {trace_id="shaZ8oxi"} 0.67 1520879607.789 # {trace_id="ookahn0M"} 1.2 1520879608.589
foo {count:17,sum:324789.3,bucket:[0.01:0,0.1:8,1.0:11,10.0:17,+Inf:17]} st@1520430000.123 # {} 0.054 1520879607.7 # {trace_id="KOO5S4vxi0o"} 0.67 1520879602.890 # {trace_id="oHg5SJYRHA0"} 9.8 1520879607.789
```

An example of a Histogram with Classic Buckets and Start Timestamp where no exemplar falls within the "0.01" bucket and the "+Inf" bucket. An exemplar without Labels falls within the "0.1" bucket. An exemplar with one Label falls within the "1" bucket and another in the "10" bucket.

```openmetrics-add-eof
# TYPE foo histogram
foo {count:17,sum:324789.3,bucket:[0.01:0,0.1:8,1.0:11,10.0:17,+Inf:17]} st@1520430000.123 # {} 0.054 1520879607.7 # {trace_id="KOO5S4vxi0o"} 1.67 1520879602.890 # {trace_id="oHg5SJYRHA0"} 9.8 1520879607.789
```

An example of a Histogram with both Classic and Native Buckets and Start Timestamp.

```openmetrics-add-eof
# TYPE foo histogram
foo {count:17,sum:324789.3,schema:0,zero_threshold:1e-4,zero_count:0,positive_spans:[0:2],positive_buckets:[5,12],bucket:[0.01:0,0.1:8,1.0:11,10.0:17,+Inf:17]} st@1520430000.123 # {} 0.054 1520879607.7 # {trace_id="KOO5S4vxi0o"} 1.67 1520879602.890 # {trace_id="oHg5SJYRHA0"} 9.8 1520879607.789
```

##### GaugeHistogram with Classic Buckets
Expand Down Expand Up @@ -1092,9 +1115,7 @@ acme_http_request_seconds{path="/api/v1",method="GET"} {count:59,sum:1.2e2,schem

##### GaugeHistogram with both Classic and Native buckets

If a GaugeHistogram MetricPoint has both Classic and Native buckets, the Sample for the Native Buckets MUST come first.

The order ensures that implementations can easily skip the Classic Buckets if the Native Buckets are preferred.
GaugeHistogram MetricPoints with both Classic and Native Buckets follow the same syntax as Histogram MetricPoints with both Classic and Native Buckets.

##### Unknown

Expand Down