OpenTelemetry Service

IMPORTANT: This is a pre-released version of the OpenTelemetry Service. For now, please use the OpenCensus Service.

Some frameworks and ecosystems are now providing out-of-the-box instrumentation by using OpenTelemetry, but the user is still expected to register an exporter in order to export data. This is a problem during an incident. Even though our users can benefit from having more diagnostics data coming out of services already instrumented with OpenTelemetry, they have to modify their code to register an exporter and redeploy. Asking our users recompile and redeploy is not an ideal at an incident time. In addition, currently users need to decide which service backend they want to export to, before they distribute their binary instrumented by OpenTelemetry.

The OpenTelemetry Service is trying to eliminate these requirements. With the OpenTelemetry Service, users do not need to redeploy or restart their applications as long as it has the OpenTelemetry exporter. All they need to do is just configure and deploy the OpenTelemetry Service separately. The OpenTelemetry Service will then automatically collect traces and metrics and export to any backend of users' choice.

Currently the OpenTelemetry Service consists of a single binary and two deployment methods:

Agent running with the application or on the same host as the application
Collector running as a standalone application

For the detailed design specs, please see design.md.

For OpenTelemetry Service performance specs, please see performance.md.

For the future vision of OpenTelemetry Service please see vision.md.

Deployment

The OpenTelemetry Service can be deployed in a variety of different ways depending on requirements. The Agent can be deployed with the application either as a separate process, as a sidecar, or via a Kubernetes daemonset. The Collector is deployed as a separate application as either a Docker container, VM, or Kubernetes pod.

While the Agent and Collector share the same binary, the configuration between the two may differ depending on requirements (e.g. queue size and feature-set enabled).

Getting Started

Demo

Instructions for setting up an end-to-end demo environment can be found here

Kubernetes

Apply the sample YAML file:

$ kubectl apply -f example/k8s.yaml

Standalone

Create an Agent configuration file based on the options described below. By default, the Agent has the opencensus receiver enabled, but no exporters configured.

Build the Agent and start it with the example configuration:

$ ./bin/$(go env GOOS)/otelsvc  --config ./examples/demo/otel-agent-config.yaml
$ 2018/10/08 21:38:00 Running OpenTelemetry receiver as a gRPC service at "127.0.0.1:55678"

Create an Collector configuration file based on the options described below. By default, the Collector has the opencensus receiver enabled, but no exporters configured.

Build the Collector and start it with the example configuration:

$ make otelsvc
$ ./bin/$($GOOS)/otelsvc --config ./examples/demo/otel-collector-config.yaml

Run the demo application:

$ go run "$(go env GOPATH)/src/github.com/open-telemetry/opentelemetry-service/examples/main.go"

You should be able to see the traces in your exporter(s) of choice. If you stop the otelsvc, the example application will stop exporting. If you run it again, exporting will resume.

Configuration

The OpenTelemetry Service (both the Agent and Collector) is configured via a YAML file. In general, at least one enabled receiver and one enabled exporter needs to be configured.

Note This documentation is still in progress. For any questions, please reach out in the OpenTelemetry Gitter or refer to the issues page.

There are four main parts to a config:

receivers:
  ...
exporters:
  ...
processors:
  ...
pipelines:
  ...

Receivers

A receiver is how data gets into OpenTelemetry Service. One or more receivers must be configured.

A basic example of all available receivers is provided below. For detailed receiver configuration, please see the receiver README.md.

receivers:
  opencensus:
    address: "127.0.0.1:55678"

  zipkin:
    address: "127.0.0.1:9411"

  jaeger:
    jaeger-thrift-tchannel-port: 14267
    jaeger-thrift-http-port: 14268

  prometheus:
    config:
      scrape_configs:
        - job_name: 'caching_cluster'
          scrape_interval: 5s
          static_configs:
            - targets: ['localhost:8889']

Exporters

An exporter is how you send data to one or more backends/destinations. One or more exporters can be configured. By default, no exporters are configured on the OpenTelemetry Service (either the Agent or Collector).

A basic example of all available exporters is provided below. For detailed exporter configuration, please see the exporter README.md.

exporters:
  opencensus:
    headers: {"X-test-header": "test-header"}
    compression: "gzip"
    cert-pem-file: "server_ca_public.pem" # optional to enable TLS
    endpoint: "127.0.0.1:55678"
    reconnection-delay: 2s

  jaeger:
    collector_endpoint: "http://127.0.0.1:14268/api/traces"

  zipkin:
    endpoint: "http://127.0.0.1:9411/api/v2/spans"

Pipelines

Pipelines can be of two types:

metrics: collects and processes metrics data.
traces: collects and processes trace data.

A pipeline consists of a set of receivers, processors, and exporters. Each receiver/processor/exporter must be specified in the configuration to be included in a pipeline and each receiver/processor/exporter can be used in more than one pipeline.

Note: 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, one instance of a receiver/exporter is reference by all the pipelines.

The following is an example pipeline configuration. For more information, refer to pipeline documentation

pipelines:
  traces:
    receivers: [examplereceiver]
    processors: [exampleprocessor]
    exporters: [exampleexporter]

Diagnostics

zPages is provided for monitoring running by default on port 55679. These routes below contain the various diagnostic resources:

Resource	Route
RPC stats	/debug/rpcz
Trace information	/debug/tracez

The zPages configuration can be updated in the config.yaml file with fields:

disabled: if set to true, won't run zPages
port: by default is 55679, otherwise should be set to a value between 0 an 65535

For example:

zpages:
    port: 8888 # To override the port from 55679 to 8888

To disable zPages, you can use disabled like this:

zpages:
    disabled: true

Global Attributes

TODO Remove this once processors have been documented since that handles these features now.

The OpenTelemetry Service also takes some global configurations that modify its behavior for all receivers / exporters. This configuration is typically applied on the Collector, but could also be added to the Agent.

Add Attributes to all spans passing through this collector. These additional attributes can be configured to either overwrite existing keys if they already exist on the span, or respect the original values.
The key of each attribute can also be mapped to different strings using the key-mapping configuration. The key matching is case sensitive.

An example using these configurations of this is provided below.

global:
  attributes:
    overwrite: true
    values:
      # values are key value pairs where the value can be an int, float, bool, or string
      some_string: "hello world"
      some_int: 1234
      some_float: 3.14159
      some_bool: false
    key-mapping:
      # key-mapping is used to replace the attribute key with different keys
      - key: servertracer.http.responsecode
        replacement: http.status_code
      - key:  servertracer.http.responsephrase
        replacement: http.message
        overwrite: true # replace attribute key even if the replacement string is already a key on the span attributes
        keep: true # keep the attribute with the original key

Sampling

Sampling can also be configured on the OpenTelemetry Service. Both head-based and tail-based sampling are supported. Either the Agent or the Collector may enable head-based sampling. Tail sampling must be configured on the Collector as it requires all spans for a given trace to make a sampling decision.

Head-based Example

sampling:
  # mode indicates if the sampling is head or tail based. For probabilistic the mode is head-based.
  mode: head
  policies:
    # section below defines a probabilistic trace sampler based on hashing the trace ID associated to
    # each span and sampling the span according to the given spans.
    probabilistic:
      configuration:
        # sampling-percentage is the percentage of sampling to be applied to all spans, unless their service is specified
        # on sampling-percentage.
        sampling-percentage: 5
        # hash-seed allows choosing the seed for the hash function used in the trace sampling. This is important when
        # multiple layers of collectors are being used with head sampling, in such scenarios make sure to
        # choose different seeds for each layer.
        hash-seed: 1

Tail-based Example

sampling:
  mode: tail
  # amount of time from seeing the first span in a trace until making the sampling decision
  decision-wait: 10s
  # maximum number of traces kept in the memory
  num-traces: 10000
  policies:
    # user-defined policy name
    my-string-attribute-filter:
      # exporters the policy applies to
      exporters:
        - jaeger
      policy: string-attribute-filter
      configuration:
        key: key1
        values:
          - value1
          - value2
    my-numeric-attribute-filter:
      exporters:
        - zipkin
      policy: numeric-attribute-filter
      configuration:
        key: key1
        min-value: 0
        max-value: 100

Note that an exporter can only have a single sampling policy today.

Usage

It is recommended that you use the latest release.

The OpenTelemetry Service can be run directly from sources, binary, or a Docker image. If you are planning to run from sources or build on your machine start by cloning the repo using go get -d github.com/open-telemetry/opentelemetry-service.

The minimum Go version required for this project is Go 1.12.5.

Run from sources:

$ GO111MODULE=on go run github.com/open-telemetry/opentelemetry-service/cmd/otelsvc --help

Run from binary (from the root of your repo):

$ make otelsvc
$ ./bin/$($GOOS)/otelsvc

Build a Docker scratch image and use the appropriate Docker command for your scenario (note: additional ports may be required depending on your receiver configuration):

$ make docker-otelsvc
$ docker run \
    --rm \
    --interactive \
    --tty \
    --publish 55678:55678 --publish 55679:55679 --publish 8888:8888 \
    --volume $(pwd)/otel-collector-config.yaml:/conf/otelsvc-config.yaml \
    otelsvc \
    --config=/conf/otelsvc-config.yaml

It can be configured via command-line or config file:

OpenTelemetry Service

Usage:
  otelsvc [flags]

Flags:
      --config string               Path to the config file
  -h, --help                        help for otelsvc
      --log-level string            Output level of logs (TRACE, DEBUG, INFO, WARN, ERROR, FATAL) (default "INFO")
      --mem-ballast-size-mib uint   Flag to specify size of memory (MiB) ballast to set. Ballast is not used when this is not specified. default settings: 0
      --metrics-level string        Output level of telemetry metrics (NONE, BASIC, NORMAL, DETAILED) (default "BASIC")
      --metrics-port uint           Port exposing collector telemetry. (default 8888)

Sample configuration file:

log-level: DEBUG

receivers:
  opencensus: {} # Runs OpenCensus receiver with default configuration (default behavior).

queued-exporters:
  jaeger-sender-test: # A friendly name for the exporter
    # num-workers is the number of queue workers that will be dequeuing batches and sending them out (default is 10)
    num-workers: 2

    # queue-size is the maximum number of batches allowed in the queue at a given time (default is 5000)
    queue-size: 100

    # retry-on-failure indicates whether queue processor should retry span batches in case of processing failure (default is true)
    retry-on-failure: true

    # backoff-delay is the amount of time a worker waits after a failed send before retrying (default is 5 seconds)
    backoff-delay: 3s

    # sender-type is the type of sender used by this processor, the default is an invalid sender so it forces one to be specified
    sender-type: jaeger-thrift-http

    # configuration of the selected sender-type, in this example Jaeger jaeger-thrift-http. Which supports 3 settings:
    # collector-endpoint: address of Jaeger collector jaeger-thrift-http endpoint
    # headers: a map of any additional headers to be sent with each batch (e.g.: api keys, etc)
    # timeout: the timeout for the sender to consider the operation as failed
    jaeger-thrift-http:
      collector-endpoint: "http://svc-jaeger-collector:14268/api/traces"
      headers: { "x-header-key":"00000000-0000-0000-0000-000000000001" }
      timeout: 5s

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README.md

README.md

OpenTelemetry Service

Table of contents

Introduction

Deployment

Getting Started

Demo

Kubernetes

Standalone

Configuration

Receivers

Exporters

Pipelines

Diagnostics

Global Attributes

Sampling

Head-based Example

Tail-based Example

Usage

Files

README.md

Latest commit

History

README.md

File metadata and controls

OpenTelemetry Service

Table of contents

Introduction

Deployment

Getting Started

Demo

Kubernetes

Standalone

Configuration

Receivers

Exporters

Pipelines

Diagnostics

Global Attributes

Sampling

Head-based Example

Tail-based Example

Usage