Configuration
Please be sure to review the following documentation:
- Data Collection concepts in order to understand the repositories applicable to the OpenTelemetry Collector.
- Security guidance
Basics
The Collector consists of three components that access telemetry data:
These components once configured must be enabled via pipelines within the service section.
Secondarily, there are extensions, which provide capabilities that can be added to the Collector, but which do not require direct access to telemetry data and are not part of pipelines. They are also enabled within the service section.
An example configuration would look like:
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
exporters:
otlp:
endpoint: otelcol:4317
extensions:
health_check:
pprof:
zpages:
service:
extensions: [health_check,pprof,zpages]
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
metrics:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
logs:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
Note that the same receiver, processor, exporter and/or pipeline can be defined more than once. For example:
receivers:
otlp:
protocols:
grpc:
http:
otlp/2:
protocols:
grpc:
endpoint: 0.0.0.0:55690
processors:
batch:
batch/test:
exporters:
otlp:
endpoint: otelcol:4317
otlp/2:
endpoint: otelcol2:4317
extensions:
health_check:
pprof:
zpages:
service:
extensions: [health_check,pprof,zpages]
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
traces/2:
receivers: [otlp/2]
processors: [batch/test]
exporters: [otlp/2]
metrics:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
logs:
receivers: [otlp]
processors: [batch]
exporters: [otlp]
Receivers
A receiver, which can be push or pull based, is how data gets into the Collector. Receivers may support one or more data sources.
The receivers:
section is how receivers are configured. Many receivers come
with default settings so simply specifying the name of the receiver is enough
to configure it (for example, zipkin:
). If configuration is required or a
user wants to change the default configuration then such configuration must be
defined in this section. Configuration parameters specified for which the
receiver provides a default configuration are overridden.
Configuring a receiver does not enable it. Receivers are enabled via pipelines within the service section.
One or more receivers must be configured. By default, no receivers are configured. A basic example of all available receivers is provided below.
For detailed receiver configuration, please see the receiver README.md.
receivers:
# Data sources: logs
fluentforward:
listenAddress: 0.0.0.0:8006
# Data sources: metrics
hostmetrics:
scrapers:
cpu:
disk:
filesystem:
load:
memory:
network:
process:
processes:
swap:
# Data sources: traces
jaeger:
protocols:
grpc:
thrift_binary:
thrift_compact:
thrift_http:
# Data sources: traces
kafka:
protocol_version: 2.0.0
# Data sources: traces, metrics
opencensus:
# Data sources: traces, metrics, logs
otlp:
protocols:
grpc:
http:
# Data sources: metrics
prometheus:
config:
scrape_configs:
- job_name: "otel-collector"
scrape_interval: 5s
static_configs:
- targets: ["localhost:8888"]
# Data sources: traces
zipkin:
Processors
Processors are run on data between being received and being exported. Processors are optional though some are recommended.
The processors:
section is how processors are configured. Processors may come
with default settings, but many require configuration. Any configuration for a
processor must be done in this section. Configuration parameters specified for
which the processor provides a default configuration are overridden.
Configuring a processor does not enable it. Processors are enabled via pipelines within the service section.
A basic example of all available processors is provided below.
For detailed processor configuration, please see the processor README.md.
processors:
# Data sources: traces
attributes:
actions:
- key: environment
value: production
action: insert
- key: db.statement
action: delete
- key: email
action: hash
# Data sources: traces, metrics, logs
batch:
# Data sources: metrics
filter:
metrics:
include:
match_type: regexp
metric_names:
- prefix/.*
- prefix_.*
# Data sources: traces, metrics, logs
memory_limiter:
check_interval: 5s
limit_mib: 4000
spike_limit_mib: 500
# Data sources: traces
resource:
attributes:
- key: cloud.zone
value: "zone-1"
action: upsert
- key: k8s.cluster.name
from_attribute: k8s-cluster
action: insert
- key: redundant-attribute
action: delete
# Data sources: traces
probabilistic_sampler:
hash_seed: 22
sampling_percentage: 15
# Data sources: traces
span:
name:
to_attributes:
rules:
- ^\/api\/v1\/document\/(?P<documentId>.*)\/update$
from_attributes: ["db.svc", "operation"]
separator: "::"
Exporters
An exporter, which can be push or pull based, is how you send data to one or more backends/destinations. Exporters may support one or more data sources.
The exporters:
section is how exporters are configured. Exporters may come
with default settings, but many require configuration to specify at least the
destination and security settings. Any configuration for an exporter must be
done in this section. Configuration parameters specified for which the exporter
provides a default configuration are overridden.
Configuring an exporter does not enable it. Exporters are enabled via pipelines within the service section.
One or more exporters must be configured. By default, no exporters are configured. A basic example of all available exporters is provided below.
For detailed exporter configuration, please see the exporter README.md.
exporters:
# Data sources: traces, metrics, logs
file:
path: ./filename.json
# Data sources: traces
jaeger:
endpoint: "http://jaeger-all-in-one:14250"
tls:
insecure: true
# Data sources: traces
kafka:
protocol_version: 2.0.0
# Data sources: traces, metrics, logs
logging:
loglevel: debug
# Data sources: traces, metrics
opencensus:
endpoint: "otelcol2:55678"
# Data sources: traces, metrics, logs
otlp:
endpoint: otelcol2:4317
tls:
insecure: true
# Data sources: traces, metrics
otlphttp:
endpoint: https://example.com:4318/v1/traces
# Data sources: metrics
prometheus:
endpoint: "prometheus:8889"
namespace: "default"
# Data sources: metrics
prometheusremotewrite:
endpoint: "http://some.url:9411/api/prom/push"
# Data sources: traces
zipkin:
endpoint: "http://localhost:9411/api/v2/spans"
Extensions
Extensions are available primarily for tasks that do not involve processing telemetry data. Examples of extensions include health monitoring, service discovery, and data forwarding. Extensions are optional.
The extensions:
section is how extensions are configured. Many extensions
come with default settings so simply specifying the name of the extension is
enough to configure it (for example, health_check:
). If configuration is
required or a user wants to change the default configuration then such
configuration must be defined in this section. Configuration parameters
specified for which the extension provides a default configuration are
overridden.
Configuring an extension does not enable it. Extensions are enabled within the service section.
By default, no extensions are configured. A basic example of all available extensions is provided below.
For detailed extension configuration, please see the extension README.md.
extensions:
health_check:
pprof:
zpages:
memory_ballast:
size_mib: 512
Service
The service section is used to configure what components are enabled in the Collector based on the configuration found in the receivers, processors, exporters, and extensions sections. If a component is configured, but not defined within the service section then it is not enabled. The service section consists of two sub-sections:
- extensions
- pipelines
Extensions consist of a list of all extensions to enable. For example:
service:
extensions: [health_check, pprof, zpages]
Pipelines can be of the following types:
- traces: collects and processes trace data.
- metrics: collects and processes metric data.
- logs: collects and processes log data.
A pipeline consists of a set of receivers, processors and exporters. Each receiver/processor/exporter must be defined in the configuration outside of the service section to be included in a pipeline.
Note: Each receiver/processor/exporter can be used in more than one pipeline. For processor(s) referenced in multiple pipelines, each pipeline will get a separate instance of that processor(s). This is in contrast to receiver(s)/exporter(s) referenced in multiple pipelines, where only one instance of a receiver/exporter is used for all pipelines. Also note that the order of processors dictates the order in which data is processed.
The following is an example pipeline configuration:
service:
pipelines:
metrics:
receivers: [opencensus, prometheus]
exporters: [opencensus, prometheus]
traces:
receivers: [opencensus, jaeger]
processors: [batch]
exporters: [opencensus, zipkin]
Other Information
Configuration Environment Variables
The use and expansion of environment variables is supported in the Collector configuration. For example:
processors:
attributes/example:
actions:
- key: "${DB_KEY}"
action: "${OPERATION}"
Proxy Support
Exporters that leverage the net/http package (all do today) respect the following proxy environment variables:
- HTTP_PROXY
- HTTPS_PROXY
- NO_PROXY
If set at Collector start time then exporters, regardless of protocol, will or will not proxy traffic as defined by these environment variables.
Authentication
Most receivers exposing an HTTP or gRPC port are able to be protected using the collector’s authentication mechanism, and most exporters using HTTP or gRPC clients are able to add authentication data to the outgoing requests.
The authentication mechanism in the collector uses the extensions mechanism, allowing for custom authenticators to be plugged into collector distributions. If you are interested in developing a custom authenticator, check out the “Building a custom authenticator” document.
Each authentication extension has two possible usages: as client authenticator for exporters, adding auth data to outgoing requests, and as server authenticator for receivers, authenticating incoming connections. Refer to the authentication extension for a list of its capabilities, but in general, an authentication extension would only implement one of those traits. For a list of known authenticators, use the Registry available in this website.
To add a server authenticator to a receiver in your collector, make sure to:
- add the authenticator extension and its configuration under
.extensions
- add a reference to the authenticator to
.services.extensions
, so that it’s loaded by the collector - add a reference to the authenticator under
.receivers.<your-receiver>.<http-or-grpc-config>.auth
Here’s an example that uses the OIDC authenticator on the receiver side, making this suitable for a remote collector that receives data from an OpenTelemetry Collector acting as agent:
extensions:
oidc:
issuer_url: http://localhost:8080/auth/realms/opentelemetry
audience: collector
receivers:
otlp/auth:
protocols:
grpc:
auth:
authenticator: oidc
processors:
exporters:
logging:
service:
extensions:
- oidc
pipelines:
traces:
receivers:
- otlp/auth
processors: []
exporters:
- logging
On the agent side, this is an example that makes the OTLP exporter obtain OIDC tokens, adding them to every RPC made to a remote collector:
extensions:
oauth2clientcredentials:
client_id: agent
client_secret: some-secret
token_url: http://localhost:8080/auth/realms/opentelemetry/protocol/openid-connect/token
receivers:
otlp:
protocols:
grpc:
endpoint: localhost:4317
processors:
exporters:
otlp/auth:
endpoint: remote-collector:4317
auth:
authenticator: oauth2clientcredentials
service:
extensions:
- oauth2clientcredentials
pipelines:
traces:
receivers:
- otlp
processors: []
exporters:
- otlp/auth