Caution
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otelcol.processor.tail_sampling
BETA: This is a beta component. Beta components are subject to breaking changes, and may be replaced with equivalent functionality that cover the same use case.
otelcol.processor.tail_sampling samples traces based on a set of defined
policies. All spans for a given trace must be received by the same collector
instance for effective sampling decisions.
The tail_sampling component uses both soft and hard limits, where the hard limit
is always equal or larger than the soft limit. When memory usage goes above the
soft limit, the processor component drops data and returns errors to the
preceding components in the pipeline. When usage exceeds the hard
limit, the processor forces a garbage collection in order to try and free
memory. When usage is below the soft limit, no data is dropped and no forced
garbage collection is performed.
Note:
otelcol.processor.tail_samplingis a wrapper over the upstream OpenTelemetry Collector Contribtail_samplingprocessor. Bug reports or feature requests will be redirected to the upstream repository, if necessary.
Multiple otelcol.processor.tail_sampling components can be specified by
giving them different labels.
Usage
otelcol.processor.tail_sampling "LABEL" {
policy {
...
}
...
output {
traces = [...]
}
}Arguments
otelcol.processor.tail_sampling supports the following arguments:
decision_wait determines the number of batches to maintain on a channel. Its value must convert to a number of seconds greater than zero.
num_traces determines the buffer size of the trace delete channel which is composed of trace ids. Increasing the number will increase the memory usage of the component while decreasing the number will lower the maximum amount of traces kept in memory.
expected_new_traces_per_sec determines the initial slice sizing of the current batch. A larger number will use more memory but be more efficient when adding traces to the batch.
Blocks
The following blocks are supported inside the definition of
otelcol.processor.tail_sampling:
policy block
The policy block configures a sampling policy used by the component. At least one policy block is required.
The following arguments are supported:
Each policy results in a decision, and the processor evaluates them to make a final decision:
- When there’s an “inverted not sample” decision, the trace is not sampled.
- When there’s a “sample” decision, the trace is sampled.
- When there’s an “inverted sample” decision and no “not sample” decisions, the trace is sampled.
- In all other cases, the trace is not sampled.
An “inverted” decision is the one made based on the “invert_match” attribute, such as the one from the string tag policy.
latency block
The latency block configures a policy of type latency. The policy samples based on the duration of the trace. The duration is determined by looking at the earliest start time and latest end time, without taking into consideration what happened in between.
The following arguments are supported:
For a trace to be sampled, its latency should be greater than threshold_ms and lower than or equal to upper_threshold_ms.
An upper_threshold_ms of 0 will result in a policy which samples anything greater than threshold_ms.
numeric_attribute block
The numeric_attribute block configures a policy of type numeric_attribute. The policy samples based on number attributes (resource and record).
The following arguments are supported:
probabilistic block
The probabilistic block configures a policy of type probabilistic. The policy samples a percentage of traces.
The following arguments are supported:
Use hash_salt to configure the hashing salts. This is important in scenarios where multiple layers of collectors
have different sampling rates. If multiple collectors use the same salt with different sampling rates, passing one
layer may pass the other even if the collectors have different sampling rates. Configuring different salts avoids that.
status_code block
The status_code block configures a policy of type status_code. The policy samples based upon the status code.
The following arguments are supported:
status_codes values must be “OK”, “ERROR” or “UNSET”.
string_attribute block
The string_attribute block configures a policy of type string_attribute. The policy samples based on string attributes (resource and record) value matches. Both exact and regex value matches are supported.
The following arguments are supported:
rate_limiting block
The rate_limiting block configures a policy of type rate_limiting. The policy samples based on rate.
The following arguments are supported:
span_count block
The span_count block configures a policy of type span_count. The policy samples based on the minimum number of spans within a batch. If all traces within the batch have fewer spans than the threshold, the batch is not sampled.
The following arguments are supported:
Set max_spans to 0, if you do not want to limit the policy samples based on the maximum number of spans in a trace.
boolean_attribute block
The boolean_attribute block configures a policy of type boolean_attribute.
The policy samples based on a boolean attribute (resource and record).
The following arguments are supported:
ottl_condition block
The ottl_condition block configures a policy of type ottl_condition. The policy samples based on a given boolean
OTTL condition (span and span event).
The following arguments are supported:
The supported values for error_mode are:
ignore: Ignore errors returned by conditions, log them, and continue on to the next condition. This is the recommended mode.silent: Ignore errors returned by conditions, do not log them, and continue on to the next condition.propagate: Return the error up the pipeline. This will result in the payload being dropped from Grafana Agent.
At least one of span or spanevent should be specified. Both span and spanevent can also be specified.
trace_state block
The trace_state block configures a policy of type trace_state. The policy samples based on TraceState value matches.
The following arguments are supported:
and block
The and block configures a policy of type and. The policy samples based on multiple policies by creating an and policy.
and_sub_policy block
The and_sub_policy block configures a sampling policy used by the and block. At least one and_sub_policy block is required inside an and block.
The following arguments are supported:
composite block
The composite block configures a policy of type composite. This policy samples based on a combination of the above samplers, with ordering and rate allocation per sampler. Rate allocation allocates certain percentages of spans per policy order. For example, if max_total_spans_per_second is set to 100, then rate_allocation is set as follows:
- test-composite-policy-1 = 50% of max_total_spans_per_second = 50 spans_per_second
- test-composite-policy-2 = 25% of max_total_spans_per_second = 25 spans_per_second
- To ensure remaining capacity is filled, use always_sample as one of the policies.
composite_sub_policy block
The composite_sub_policy block configures a sampling policy used by the composite block. At least onecomposite_sub_policy block is required inside a composite block.
The following arguments are supported:
output block
The output block configures a set of components to forward resulting telemetry data to.
The following arguments are supported:
You must specify the output block, but all its arguments are optional.
By default, telemetry data is dropped.
Configure the metrics, logs, and traces arguments accordingly to send telemetry data to other components.
Exported fields
The following fields are exported and can be referenced by other components:
input accepts otelcol.Consumer data for any telemetry signal (metrics,
logs, or traces).
Component health
otelcol.processor.tail_sampling is only reported as unhealthy if given an invalid
configuration.
Debug information
otelcol.processor.tail_sampling does not expose any component-specific debug
information.
Example
This example batches trace data from Grafana Agent Flow before sending it to otelcol.exporter.otlp for further processing. This example shows an impractical number of policies for the purpose of demonstrating how to set up each type.
tracing {
sampling_fraction = 1
write_to = [otelcol.processor.tail_sampling.default.input]
}
otelcol.processor.tail_sampling "default" {
decision_wait = "10s"
num_traces = 100
expected_new_traces_per_sec = 10
policy {
name = "test-policy-1"
type = "always_sample"
}
policy {
name = "test-policy-2"
type = "latency"
latency {
threshold_ms = 5000
}
}
policy {
name = "test-policy-3"
type = "numeric_attribute"
numeric_attribute {
key = "key1"
min_value = 50
max_value = 100
}
}
policy {
name = "test-policy-4"
type = "probabilistic"
probabilistic {
sampling_percentage = 10
}
}
policy {
name = "test-policy-5"
type = "status_code"
status_code {
status_codes = ["ERROR", "UNSET"]
}
}
policy {
name = "test-policy-6"
type = "string_attribute"
string_attribute {
key = "key2"
values = ["value1", "value2"]
}
}
policy {
name = "test-policy-7"
type = "string_attribute"
string_attribute {
key = "key2"
values = ["value1", "val*"]
enabled_regex_matching = true
cache_max_size = 10
}
}
policy {
name = "test-policy-8"
type = "rate_limiting"
rate_limiting {
spans_per_second = 35
}
}
policy {
name = "test-policy-9"
type = "string_attribute"
string_attribute {
key = "http.url"
values = ["/health", "/metrics"]
enabled_regex_matching = true
invert_match = true
}
}
policy {
name = "test-policy-10"
type = "span_count"
span_count {
min_spans = 2
}
}
policy {
name = "test-policy-11"
type = "trace_state"
trace_state {
key = "key3"
values = ["value1", "value2"]
}
}
policy {
name = "test-policy-12"
type = "ottl_condition"
ottl_condition {
error_mode = "ignore"
span = [
"attributes[\"test_attr_key_1\"] == \"test_attr_val_1\"",
"attributes[\"test_attr_key_2\"] != \"test_attr_val_1\"",
]
spanevent = [
"name != \"test_span_event_name\"",
"attributes[\"test_event_attr_key_2\"] != \"test_event_attr_val_1\"",
]
}
}
policy {
name = "and-policy-1"
type = "and"
and {
and_sub_policy {
name = "test-and-policy-1"
type = "numeric_attribute"
numeric_attribute {
key = "key1"
min_value = 50
max_value = 100
}
}
and_sub_policy {
name = "test-and-policy-2"
type = "string_attribute"
string_attribute {
key = "key1"
values = ["value1", "value2"]
}
}
}
}
policy {
name = "composite-policy-1"
type = "composite"
composite {
max_total_spans_per_second = 1000
policy_order = ["test-composite-policy-1", "test-composite-policy-2", "test-composite-policy-3"]
composite_sub_policy {
name = "test-composite-policy-1"
type = "numeric_attribute"
numeric_attribute {
key = "key1"
min_value = 50
max_value = 100
}
}
composite_sub_policy {
name = "test-composite-policy-2"
type = "string_attribute"
string_attribute {
key = "key1"
values = ["value1", "value2"]
}
}
composite_sub_policy {
name = "test-composite-policy-3"
type = "always_sample"
}
rate_allocation {
policy = "test-composite-policy-1"
percent = 50
}
rate_allocation {
policy = "test-composite-policy-2"
percent = 50
}
}
}
output {
traces = [otelcol.exporter.otlp.production.input]
}
}
otelcol.exporter.otlp "production" {
client {
endpoint = env("OTLP_SERVER_ENDPOINT")
}
}Compatible components
otelcol.processor.tail_sampling can accept arguments from the following components:
- Components that export OpenTelemetry
otelcol.Consumer
otelcol.processor.tail_sampling has exports that can be consumed by the following components:
- Components that consume OpenTelemetry
otelcol.Consumer
Note
Connecting some components may not be sensible or components may require further configuration to make the connection work correctly. Refer to the linked documentation for more details.



