OpenTelemetry Collector — Tail-Sampling Policies (yaml)
Six tail-sampling policies including an inverted regex match that drops health checks and a composite policy with its own rate limit and ordered sub-policies. Policies are OR-ed and one match keeps the entire trace, which is the semantic most people get backwards.
# Tail-sampling policies for the shop namespace. Tail sampling must run in a
# single collector instance that sees every span of a trace, which is why this
# pipeline has no other processors between the receiver and the sampler.
processors:
tail_sampling:
decision_wait: 30s
num_traces: 100000
expected_new_traces_per_sec: 2000
policies:
- name: keep-all-errors
type: status_code
status_code:
status_codes: [ERROR]
- name: keep-slow-checkouts
type: latency
latency:
threshold_ms: 1000
- name: keep-flagged-customers
type: string_attribute
string_attribute:
key: enduser.id
values: [cust-000418, cust-000502]
enabled_regex_matching: false
- name: drop-health-checks
type: string_attribute
string_attribute:
key: url.path
values: ['^/healthz$', '^/readyz$']
enabled_regex_matching: true
invert_match: true
- name: probabilistic-remainder
type: probabilistic
probabilistic:
sampling_percentage: 5
- name: composite-rate-limited
type: composite
composite:
max_total_spans_per_second: 500
policy_order: [keep-all-errors, keep-slow-checkouts, probabilistic-remainder]
composite_sub_policy:
- name: keep-all-errors
type: status_code
status_code:
status_codes: [ERROR]
- name: keep-slow-checkoutsSpecifications
- Policies
- 6
- Composite Sub Policies
- 3
- Decision Wait
- 30s
- Has Inverted Match
- true
- Latency Threshold Ms
- 1000
- Probabilistic Percentage
- 5
- Note
- policies are OR-ed; one match keeps the whole trace
Testing contract
Expected to pass- Scenario
- Evaluate the trace fixtures in this category against these policies.
- Expected result
- The error-trace fixture is kept by keep-all-errors and the 2-second root also matches keep-slow-checkouts, while a healthz-only trace is dropped by the inverted match before the probabilistic policy is reached.
What is a .yaml file?
YAML (YAML Ain't Markup Language) is a human-readable data-serialization format using indentation, key-value pairs, and lists, and is a superset of JSON. It supports comments, anchors, and multiple documents per file, favoring readability for configuration. Its indentation sensitivity makes it error-prone to hand-edit.
How to use this file
Use an example YAML file to test config parsers, indentation and anchor handling, multi-document streams, and safe-loading to avoid arbitrary object construction.
How to use this file for testing
“OpenTelemetry Collector — Tail-Sampling Policies (yaml)” is a deterministic Novus Examples fixture for Observability, Config parsing, Config testing. Structured and plain-text telemetry with known timestamps, levels, request identifiers, and error states for testing log ingestion, correlation, dashboards, and alert pipelines.
Documented properties for this file: YAML · 1,909 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Telemetry fixtures use fixed trace IDs, span IDs, and timestamps so ingestion is reproducible run to run. Point your collector, parser, or query layer at the file and assert the documented span tree, metric families, or severity mix; service and host names are invented.
Code examples
import yaml # pip install pyyaml
with open("otel-collector-tail-sampling.yaml") as f:
data = yaml.safe_load(f)
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