Sampling milestones blog post

content/en/blog/2025/sampling-milestones.md

@@ -0,0 +1,242 @@
+---
+title: OpenTelemetry Sampling update
+linkTitle: OpenTelemetry Sampling update
+date: 2025-10-15
+author: >-
+  [Joshua MacDonald](https://github.com/jmacd) (Microsoft), [Kent
+  Quirk](https://github.com/kentquirk) (Honeycomb), [Otmer
+  Ertl](https://github.com/oertl) (DynaTrace), [Peter
+  Findeisen](https://github.com/PeterF778) (Cisco), [Yuanyuan
+  Zhao](https://github.com/yuanyuanzhao3) (DataDog)
+sig: SIG Sampling
+cSpell:ignore: Ertl Findeisen probabilisticsampler Yuanyuan Zhao
+---
+
+## Introduction
+
+OpenTelemetry published version 1.0 of its Tracing specification over four years
+ago, and the same year [W3C TraceContext Level 1][TRACECONTEXT1] was published
+with W3C Recommendation status. We as a community and we the observability
+industry had two new standards for distributed tracing. Of course, we weren't
+finished.
+
+[TRACECONTEXT1]: https://www.w3.org/TR/trace-context-1
+[JAEGERREMOTE]: https://www.jaegertracing.io/docs/1.22/architecture/sampling/
+
+Sampling is a major topic of the Tracing SDK specification, and the original
+specification included a set of built-in Samplers, `AlwaysOn`, `AlwaysOff`,
+`ParentBased`, and `TraceIdRatioBased`, along with an interface allowing new
+samplers to be implemented, primarily [Jaeger Remote][JAEGERREMOTE].
+
+However, there was a
+[conspicuous "TODO" involving probability sampling](https://github.com/open-telemetry/opentelemetry-specification/issues/1413)
+left in the 1.0 Tracing specification affecting the `TraceIdRatioBased` sampler.
+The TODO warned specification users of "inconsistent" results, that
+`TraceIdRatioBased` samplers were only safe to configure for root spans.
+
+This meant OpenTelemetry users could not safely configure independent
+probability sampling policies in a distributed system, as the specification did
+not cover how to achieve consistency. This feature, the ability to configure
+unequal-probability sampling policies within a trace and still expect complete
+traces, is something users expect; it lets service owners configure independent
+limits on the volume of tracing data collected in a system.
+
+## Consistency by example
+
+To see why consistency is important, consider a system with a Frontend and two
+backend services, Cache and Storage. The Frontend handles high-value user
+requests, therefore frontend requests are sampled at 100%. The root span is
+significant because errors are visible to the end user, so it forms the basis of
+an SLO measurement in this example and the system operator is willing to collect
+every span.
+
+The Cache service receives a relatively high volume of requests, so to save on
+observability costs, this service is configured to sample 1-in-1000 traces.
+Because of the high rate of requests, this 0.1% policy ensures the Cache service
+produces enough traces for many observability scenarios.
+
+The Storage service receives a relatively low volume of requests, compared with
+the Cache server, but still a lot of requests compared with the Frontend
+service; Storage is configured to sample 1-in-10 traces.
+
+When we ask for consistency in distributed tracing, the goal is to ensure that
+when the smallest probability sampler (here 0.1%) chooses to sample, that higher
+probability samplers make the same decision. Here are the properties we can rely
+on in this configuration:
+
+- 100% of Frontend spans will be collected
+- 1-in-10 traces will consist of Frontend and Storage spans
+- 1-in-1000 traces will be complete.
+
+## Problems with TraceIdRatioBased
+
+OpenTelemetry's `TraceIdRatioBased` probability sampler was intended to be
+consistent from the start, however the working group had a hard time agreeing
+over specific details. The TODO about sampling consistency was mitigated by the
+fact that root-only sampling was the norm for contemporary open source tracing
+systems and the model embraced by Jaeger.
+
+The "ratio-based" part of the name hints at the form of solution to the
+consistent sampling problem:
+
+1. Consider the TraceID value as an N-bit random value
+2. Compute the Nth power of two
+3. Multiply the power-of-two by the ratio, yielding a "threshold" value
+4. Compare the TraceID with the threshold value, yielding a consistent decision.
+
+We had trouble agreeing on this form of solution because of a larger question.
+_Which bits of the TraceID can we trust to be random?_ Without foundational
+requirements about randomness, OpenTelemetry could not specify a consistent
+sampling decision.
+
+When lacking firm randomness requirements, a common approach is to use a hash
+function instead. Using `Hash(TraceID)` to produce N-bits randomness works
+reasonably well if the hash function is good, but this approach is not suitable
+in a cross-language SDK specification.
+
+The details here are tricky. How many bits of the TraceID would be enough? Could
+every language SDK efficiently implement the required logic?
+
+## Introducing W3C TraceContext Level 2
+
+OpenTelemetry turned to the W3C Trace Context working group with this larger
+problem in mind. Could we, including OpenTelemetry and non-OpenTelemetry tracing
+systems, agree on how many bits of the TraceID were random?
+
+The [W3C TraceContext Level 2][TRACECONTEXT2] specification, currently a
+[Candidate Recommendation Draft](https://www.w3.org/standards/types/#x4-2-1-candidate-recommendation-draft),
+answers this question with a new
+[`Random` Trace Flag value](https://www.w3.org/TR/trace-context-2/#random-trace-id-flag).
+With this flag, the new W3C specification requires the least-significant 56 bits
+of the TraceID to be "sufficiently" random. This means, for example, when we
+[represent the TraceID as 32 hexadecimal digits](/docs/specs/otel/trace/api/#retrieving-the-traceid-and-spanid),
+the last, rightmost 14 digits are random. Represented as 16 bytes, the last,
+rightmost 7 bytes are random.
+
+[TRACECONTEXT2]: https://www.w3.org/TR/trace-context-2
+
+OpenTelemetry is adopting the W3C TraceContext Level 2 draft recommendation as
+the foundation for consistent sampling. All SDKs will set the `Random` flag and
+ensure that TraceIDs they generate have the required 56 bits of randomness by
+default.
+
+## Consistent sampling threshold for rejection
+
+Turning back to consistent "ratio-based" logic, now we're able to obtain 56 bits
+of randomness from a TraceID, and the decision process described in outline
+above calls for a threshold to compare with.
+
+There was one more thing we as a group wanted for the probability sampling
+specification: a way for SDKs to communicate their sampling decisions, both to
+one another in the TraceContext, as well as on the collection path after spans
+are finished.
+
+The new specification lets OpenTelemetry components communicate about "how much
+sampling" has been applied to a span. This supports many advanced sampling
+architectures:
+
+- Reliable estimates of span count
+- Consistent rate-limited sampling
+- Adaptive sampling
+- Consistent multi-stage sampling.
+
+The key points of our design are summarized next, but curious readers may want
+to see the
+[full specification](/docs/specs/otel/trace/tracestate-probability-sampling/).
+
+Given the number of bits, there is not much left to specify. However, we wanted
+an approach that:
+
+- Supports both lexicographical and numerical comparison
+- Minimizes TraceContext overhead
+- Is legible for advanced OpenTelemetry users.
+
+Our approach is based on what we call the _sampling threshold for rejection_.
+Given randomness value `R` and threshold for rejection `T`, we make a positive
+sampling decision when `T <= R`. Equivalently, we make a negative sampling
+decision when `T > R`.
+
+By design, the threshold value `0` corresponds with 100% sampling, so users can
+easily recognize this configuration. Abstractly, both `R` and `T` have a range
+of 56 bits, which can be represented as unsigned integers, 7-byte slices, or
+14-hex-digit strings.
+
+## OpenTelemetry TraceState
+
+The W3C TraceContext specification defines two HTTP headers for use in
+distributed tracing systems, the `tracecontext` header, which contains version,
+TraceID, SpanID, and flags, and `tracestate` which supports "vendor-specific"
+additions to the context. OpenTelemetry Tracing SDKs will soon begin adding an
+entry under the key "ot" in the `tracestate` header. Here's an example:
+
+```http
+tracestate: ot=th:0
+```
+
+In a 100% sampling configuration, OpenTelemetry Tracing SDKs will insert
+`ot=th:0` in the TraceState. TraceState values, once entered in the context, are
+both propagated and recorded in OpenTelemetry span data. By design, the new
+OpenTelemetry TraceState value is only encoded and transmitted for positive
+sampling decisions; no `tracestate` header will appear as a result of negative
+sampling decisions.
+
+In this representation, sampling thresholds logically represent 14 hexadecimal
+digits or 56 bits of information.
+
+However, to communicate the sampling threshold efficiently, we drop trailing
+zeros (except for `0` itself). This lets us limit threshold precision to fewer
+than 56 bits, which lowers the number of bytes per context. Here is an example
+tracestate indicating 1% sampling, limited to 12-bits of precision:
+
+```http
+tracestate: ot=th:fd7
+```
+
+We gave a lot of consideration to backwards compatibility, but we also wanted to
+be sure we could always use the stated sampling threshold for extrapolation, in
+a reliable, statistical sense. With this in mind, there is one more
+OpenTelemetry TraceState value in our specification: a way to provide explicit
+randomness in the `tracestate` header.
+
+To enable consistent sampling and continue using non-random TraceIDs, for
+example, users can opt for explicit randomness:
+
+```http
+tracestate: ot=rv:abcdef01234567
+```
+
+Explicit randomness values have several other uses, for example:
+
+- Achieve consistent sampling across multiple traces, by applying the same
+  explicit randomness value to independent trace roots
+- Translate external consistent sampling decisions (for example, hash
+  function-based) into OpenTelemetry consistent sampling decisions.
+
+As a demonstration, we upgraded the OpenTelemetry Collector-Contrib
+[`probabilisticsampler` processor][PROBABILISTICSAMPLERPROCESSOR] to keep its
+original consistent sampling decision and still encode sampling probability in
+the OpenTelemetry TraceState. It does this by synthesizing an explicit
+randomness value from the hash function that it uses.
+
+[PROBABILISTICSAMPLERPROCESSOR]:
+  https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/probabilisticsamplerprocessor/README.md
+
+## Looking forward
+
+This post covers an essential upgrade to OpenTelemetry Tracing specification,
+enabling a new generation of samplers for OpenTelemetry SDKs and Collector
+components.
+
+Here are some useful references including the four OpenTelemetry enhancement
+proposals that plotted our course:
+
+- [0168 Sampling Propagation](https://github.com/open-telemetry/opentelemetry-specification/blob/main/oteps/trace/0168-sampling-propagation.md)
+- [0170 Sampling Probability](https://github.com/open-telemetry/opentelemetry-specification/blob/main/oteps/trace/0170-sampling-probability.md)
+- [0235 Sampling Threshold in TraceState](https://github.com/open-telemetry/opentelemetry-specification/blob/main/oteps/trace/0235-sampling-threshold-in-trace-state.md)
+- [0250 Composite Samplers](https://github.com/open-telemetry/opentelemetry-specification/blob/main/oteps/trace/0250-Composite_Samplers.md)
+
+The following are our primary specification documents:
+
+- [Trace Probability Sampling](/docs/specs/otel/trace/tracestate-probability-sampling/)
+- [Trace SDK Samplers](/docs/specs/otel/trace/sdk/#sampler)
+- [TraceID Randomness](/docs/specs/otel/trace/sdk/#traceid-randomness).

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