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Datadog Trace Client

ddtrace is Datadog’s tracing client for Ruby. It is used to trace requests as they flow across web servers, databases and microservices so that developers have great visiblity into bottlenecks and troublesome requests.

Getting started

For a basic product overview, check out our setup documentation.

For details about contributing, check out the development guide.

For descriptions of terminology used in APM, take a look at the official documentation.

Table of Contents

Compatibility

Supported Ruby interpreters:

Type Documentation Version Support type
MRI https://www.ruby-lang.org/ 1.9.1 Experimental
1.9.3 Full
2.0 Full
2.1 Full
2.2 Full
2.3 Full
2.4 Full
JRuby http://jruby.org/ 9.1.5 Experimental

Full support indicates all tracer features are available.

Experimental indicates most features should be available, but unverified.

Supported web servers:

Type Documentation Version Support type
Puma http://puma.io/ 2.16+ / 3.6+ Full
Unicorn https://bogomips.org/unicorn/ 4.8+ / 5.1+ Full
Passenger https://www.phusionpassenger.com/ 5.0+ Full

Installation

The following steps will help you quickly start tracing your Ruby application.

Setup the Datadog Agent

The Ruby APM tracer sends trace data through the Datadog Agent.

Install and configure the Datadog Agent, see additional documentation for tracing Docker applications.

Quickstart for Rails applications

  1. Add the ddtrace gem to your Gemfile:

    source 'https://rubygems.org'
gem 'ddtrace'

  2. Install the gem with bundle install

  3. Create a config/initializers/datadog.rb file containing:

    Datadog.configure do |c|
  # This will activate auto-instrumentation for Rails
  c.use :rails
end

    You can also activate additional integrations here (see Integration instrumentation)

Quickstart for Ruby applications

  1. Install the gem with gem install ddtrace

  2. Add a configuration block to your Ruby application:

    require 'ddtrace'
Datadog.configure do |c|
  # Configure the tracer here.
  # Activate integrations, change tracer settings, etc...
  # By default without additional configuration, nothing will be traced.
end

  3. Add or activate instrumentation by doing either of the following:

    1. Activate integration instrumentation (see Integration instrumentation)
    2. Add manual instrumentation around your code (see Manual instrumentation)

Final steps for installation

After setting up, your services will appear on the APM services page within a few minutes. Learn more about using the APM UI.

Manual Instrumentation

If you aren't using a supported framework instrumentation, you may want to to manually instrument your code.

To trace any Ruby code, you can use the Datadog.tracer.trace method:

Datadog.tracer.trace(name, options) do |span|
  # Wrap this block around the code you want to instrument
  # Additionally, you can modify the span here.
  # e.g. Change the resource name, set tags, etc...
end

Where name should be a String that describes the generic kind of operation being done (e.g. 'web.request', or 'request.parse')

And options is an optional Hash that accepts the following parameters:

Key Type Description Default
service String The service name which this span belongs (e.g. 'my-web-service') Tracer default-service, $PROGRAM_NAME or 'ruby'
resource String Name of the resource or action being operated on. Traces with the same resource value will be grouped together for the purpose of metrics (but still independently viewable.) Usually domain specific, such as a URL, query, request, etc. (e.g. 'Article#submit', http://example.com/articles/list.) name of Span.
span_type String The type of the span (such as 'http', 'db', etc.) nil
child_of Datadog::Span / Datadog::Context Parent for this span. If not provided, will automatically become current active span. nil
start_time Integer When the span actually starts. Useful when tracing events that have already happened. Time.now.utc
tags Hash Extra tags which should be added to the span. {}

It's highly recommended you set both service and resource at a minimum. Spans without a service or resource as nil will be discarded by the Datadog agent.

Example of manual instrumentation in action:

get '/posts' do
  Datadog.tracer.trace('web.request', service: 'my-blog', resource: 'GET /posts') do |span|
    # Trace the activerecord call
    Datadog.tracer.trace('posts.fetch') do
      @posts = Posts.order(created_at: :desc).limit(10)
    end

    # Add some APM tags
    span.set_tag('http.method', request.request_method)
    span.set_tag('posts.count', @posts.length)

    # Trace the template rendering
    Datadog.tracer.trace('template.render') do
      erb :index
    end
  end
end

Asynchronous tracing

It might not always be possible to wrap Datadog.tracer.trace around a block of code. Some event or notification based instrumentation might only notify you when an event begins or ends.

To trace these operations, you can trace code asynchronously by calling Datadog.tracer.trace without a block:

# Some instrumentation framework calls this after an event began and finished...
def db_query(start, finish, query)
  span = Datadog.tracer.trace('database.query')
  span.resource = query
  span.start_time = start
  span.finish(finish)
end

Calling Datadog.tracer.trace without a block will cause the function to return a Datadog::Span that is started, but not finished. You can then modify this span however you wish, then close it finish.

You must not leave any unfinished spans. If any spans are left open when the trace completes, the trace will be discarded. You can activate debug mode to check for warnings if you suspect this might be happening.

To avoid this scenario when handling start/finish events, you can use Datadog.tracer.active_span to get the current active span.

# e.g. ActiveSupport::Notifications calls this when an event starts
def start(name, id, payload)
  # Start a span
  Datadog.tracer.trace(name)
end

# e.g. ActiveSupport::Notifications calls this when an event finishes
def finish(name, id, payload)
  # Retrieve current active span (thread-safe)
  current_span = Datadog.tracer.active_span
  unless current_span.nil?
    current_span.resource = payload[:query]
    current_span.finish
  end
end

Integration instrumentation

Many popular libraries and frameworks are supported out-of-the-box, which can be auto-instrumented. Although they are not activated automatically, they can be easily activated and configured by using the Datadog.configure API:

Datadog.configure do |c|
  # Activates and configures an integration
  c.use :integration_name, options
end

options is a Hash of integration-specific configuration settings.

For a list of available integrations, and their configuration options, please refer to the following:

Name Key Versions Supported How to configure Gem source
Active Record active_record >= 3.2, < 5.2 Link Link
AWS aws >= 2.0 Link Link
Dalli dalli >= 2.7 Link Link
Elastic Search elasticsearch >= 6.0 Link Link
Faraday faraday >= 0.14 Link Link
Grape grape >= 1.0 Link Link
GraphQL graphql >= 1.7.9 Link Link
MongoDB mongo >= 2.0, < 2.5 Link Link
Net/HTTP http (Any supported Ruby) Link Link
Racecar racecar >= 0.3.5 Link Link
Rack rack >= 1.4.7 Link Link
Rails rails >= 3.2, < 5.2 Link Link
Redis redis >= 3.2, < 4.0 Link Link
Resque resque >= 1.0, < 2.0 Link Link
Sidekiq sidekiq >= 4.0 Link Link
Sinatra sinatra >= 1.4.5 Link Link
Sucker Punch sucker_punch >= 2.0 Link Link

Active Record

Most of the time, Active Record is set up as part of a web framework (Rails, Sinatra...) however it can be set up alone:

require 'tmpdir'
require 'sqlite3'
require 'active_record'
require 'ddtrace'

Datadog.configure do |c|
  c.use :active_record, options
end

Dir::Tmpname.create(['test', '.sqlite']) do |db|
  conn = ActiveRecord::Base.establish_connection(adapter: 'sqlite3',
                                                 database: db)
  conn.connection.execute('SELECT 42') # traced!
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for database portion of active_record instrumentation. Name of database adapter (e.g. mysql2)
orm_service_name Service name used for the Ruby ORM portion of active_record instrumentation. Overrides service name for ORM spans if explicitly set, which otherwise inherit their service from their parent. active_record

AWS

The AWS integration will trace every interaction (e.g. API calls) with AWS services (S3, ElastiCache etc.).

require 'aws-sdk'
require 'ddtrace'

Datadog.configure do |c|
  c.use :aws, options
end

Aws::S3::Client.new.list_buckets # traced call

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for aws instrumentation aws

Dalli

Dalli integration will trace all calls to your memcached server:

require 'dalli'
require 'ddtrace'

Datadog.configure do |c|
  c.use :dalli, service_name: 'dalli'
end

client = Dalli::Client.new('localhost:11211', options)
client.set('abc', 123)

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for dalli instrumentation memcached

Elastic Search

The Elasticsearch integration will trace any call to perform_request in the Client object:

require 'elasticsearch/transport'
require 'ddtrace'

Datadog.configure do |c|
  c.use :elasticsearch, options
end

# now do your Elastic Search stuff, eg:
client = Elasticsearch::Client.new url: 'http://127.0.0.1:9200'
response = client.perform_request 'GET', '_cluster/health'

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for elasticsearch instrumentation elasticsearch
quantize Hash containing options for quantization. May include :show with an Array of keys to not quantize (or :all to skip quantization), or :exclude with Array of keys to exclude entirely. {}

Faraday

The faraday integration is available through the ddtrace middleware:

require 'faraday'
require 'ddtrace'

Datadog.configure do |c|
  c.use :faraday, service_name: 'faraday' # global service name
end

connection = Faraday.new('https://example.com') do |builder|
  builder.use(:ddtrace, options)
  builder.adapter Faraday.default_adapter
end

connection.get('/foo')

Where options is an optional Hash that accepts the following parameters:

Key Default Description
service_name Global service name (default: faraday) Service name for this specific connection object.
split_by_domain false Uses the request domain as the service name when set to true.
distributed_tracing false Propagates tracing context along the HTTP request when set to true.
error_handler 5xx evaluated as errors A callable object that receives a single argument – the request environment. If it evaluates to a truthy value, the trace span is marked as an error.

Grape

The Grape integration adds the instrumentation to Grape endpoints and filters. This integration can work side by side with other integrations like Rack and Rails.

To activate your integration, use the Datadog.configure method before defining your Grape application:

# api.rb
require 'grape'
require 'ddtrace'

Datadog.configure do |c|
  c.use :grape, options
end

# then define your application
class RackTestingAPI < Grape::API
  desc 'main endpoint'
  get :success do
    'Hello world!'
  end
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for grape instrumentation grape

GraphQL

The GraphQL integration activates instrumentation for GraphQL queries.

To activate your integration, use the Datadog.configure method:

# Inside Rails initializer or equivalent
Datadog.configure do |c|
  c.use :graphql,
        service_name: 'graphql',
        schemas: [YourSchema]
end

# Then run a GraphQL query
YourSchema.execute(query, variables: {}, context: {}, operation_name: nil)

The use :graphql method accepts the following parameters:

Key Description Default
service_name Service name used for graphql instrumentation ruby-graphql
schemas Required. Array of GraphQL::Schema objects which to trace. Tracing will be added to all the schemas listed, using the options provided to this configuration. If you do not provide any, then tracing will not be activated. []
tracer A Datadog::Tracer instance used to instrument the application. Usually you don't need to set that. Datadog.tracer

Manually configuring GraphQL schemas

If you prefer to individually configure the tracer settings for a schema (e.g. you have multiple schemas with different service names), in the schema definition, you can add the following using the GraphQL API:

YourSchema = GraphQL::Schema.define do
  use(
    GraphQL::Tracing::DataDogTracing,
    service: 'graphql'
  )
end

Or you can modify an already defined schema:

YourSchema.define do
  use(
    GraphQL::Tracing::DataDogTracing,
    service: 'graphql'
  )
end

Do not use :graphql in Datadog.configure if you choose to configure manually, as to avoid double tracing. These two means of configuring GraphQL tracing are considered mutually exclusive.

MongoDB

The integration traces any Command that is sent from the MongoDB Ruby Driver to a MongoDB cluster. By extension, Object Document Mappers (ODM) such as Mongoid are automatically instrumented if they use the official Ruby driver. To activate the integration, simply:

require 'mongo'
require 'ddtrace'

Datadog.configure do |c|
  c.use :mongo, options
end

# now create a MongoDB client and use it as usual:
client = Mongo::Client.new([ '127.0.0.1:27017' ], :database => 'artists')
collection = client[:people]
collection.insert_one({ name: 'Steve' })

# In case you want to override the global configuration for a certain client instance
Datadog.configure(client, service_name: 'mongodb-primary')

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for mongo instrumentation mongodb

Net/HTTP

The Net/HTTP integration will trace any HTTP call using the standard lib Net::HTTP module.

require 'net/http'
require 'ddtrace'

Datadog.configure do |c|
  c.use :http, options
end

Net::HTTP.start('127.0.0.1', 8080) do |http|
  request = Net::HTTP::Get.new '/index'
  response = http.request request
end

content = Net::HTTP.get(URI('http://127.0.0.1/index.html'))

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for http instrumentation http
distributed_tracing Enables distributed tracing false

If you wish to configure each connection object individually, you may use the Datadog.configure as it follows:

client = Net::HTTP.new(host, port)
Datadog.configure(client, options)

Racecar

The Racecar integration provides tracing for Racecar jobs.

You can enable it through Datadog.configure:

require 'ddtrace'

Datadog.configure do |c|
  c.use :racecar, options
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for racecar instrumentation racecar
tracer A Datadog::Tracer instance used to instrument the application. Usually you don't need to set that. Datadog.tracer

Rack

The Rack integration provides a middleware that traces all requests before they reach the underlying framework or application. It responds to the Rack minimal interface, providing reasonable values that can be retrieved at the Rack level.

This integration is automatically activated with web frameworks like Rails. If you're using a plain Rack application, just enable the integration it to your config.ru:

# config.ru example
require 'ddtrace'

Datadog.configure do |c|
  c.use :rack, options
end

use Datadog::Contrib::Rack::TraceMiddleware

app = proc do |env|
  [ 200, {'Content-Type' => 'text/plain'}, ['OK'] ]
end

run app

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used when tracing application requests rack
distributed_tracing Enables distributed tracing so that this service trace is connected with a trace of another service if tracing headers are received false
middleware_names Enable this if you want to use the middleware classes as the resource names for rack spans. Must provide the application option with it. false
quantize Hash containing options for quantization. May include :query or :fragment. {}
quantize.query Hash containing options for query portion of URL quantization. May include :show or :exclude. See options below. Option must be nested inside the quantize option. {}
quantize.query.show Defines which values should always be shown. Shows no values by default. May be an Array of strings, or :all to show all values. Option must be nested inside the query option. nil
quantize.query.exclude Defines which values should be removed entirely. Excludes nothing by default. May be an Array of strings, or :all to remove the query string entirely. Option must be nested inside the query option. nil
quantize.fragment Defines behavior for URL fragments. Removes fragments by default. May be :show to show URL fragments. Option must be nested inside the quantize option. nil
application Your Rack application. Necessary for enabling middleware resource names. nil
tracer A Datadog::Tracer instance used to instrument the application. Usually you don't need to set that. Datadog.tracer

Configuring URL quantization behavior

Datadog.configure do |c|
  # Default behavior: all values are quantized, fragment is removed.
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path?category_id&sort_by
  # http://example.com/path?categories[]=1&categories[]=2 --> http://example.com/path?categories[]

  # Show values for any query string parameter matching 'category_id' exactly
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path?category_id=1&sort_by
  c.use :rack, quantize: { query: { show: ['category_id'] } }

  # Show all values for all query string parameters
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path?category_id=1&sort_by=asc
  c.use :rack, quantize: { query: { show: :all } }

  # Totally exclude any query string parameter matching 'sort_by' exactly
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path?category_id
  c.use :rack, quantize: { query: { exclude: ['sort_by'] } }

  # Remove the query string entirely
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path
  c.use :rack, quantize: { query: { exclude: :all } }

  # Show URL fragments
  # http://example.com/path?category_id=1&sort_by=asc#featured --> http://example.com/path?category_id&sort_by#featured
  c.use :rack, quantize: { fragment: :show }
end

Rails

The Rails integration will trace requests, database calls, templates rendering and cache read/write/delete operations. The integration makes use of the Active Support Instrumentation, listening to the Notification API so that any operation instrumented by the API is traced.

To enable the Rails auto instrumentation, create an initializer file in your config/initializers folder:

# config/initializers/datadog-tracer.rb

Datadog.configure do |c|
  c.use :rails, options
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used when tracing application requests (on the rack level) <app_name> (inferred from your Rails application namespace)
controller_service Service name used when tracing a Rails action controller <app_name>-controller
cache_service Cache service name used when tracing cache activity <app_name>-cache
database_service Database service name used when tracing database activity <app_name>-<adapter_name>
exception_controller Class or Module which identifies a custom exception controller class. Tracer provides improved error behavior when it can identify custom exception controllers. By default, without this option, it 'guesses' what a custom exception controller looks like. Providing this option aids this identification. nil
distributed_tracing Enables distributed tracing so that this service trace is connected with a trace of another service if tracing headers are received false
middleware_names Enables any short-circuited middleware requests to display the middleware name as resource for the trace. false
template_base_path Used when the template name is parsed. If you don't store your templates in the views/ folder, you may need to change this value views/
tracer A Datadog::Tracer instance used to instrument the application. Usually you don't need to set that. Datadog.tracer

Redis

The Redis integration will trace simple calls as well as pipelines.

require 'redis'
require 'ddtrace'

Datadog.configure do |c|
  c.use :redis, service_name: 'redis'
end

# now do your Redis stuff, eg:
redis = Redis.new
redis.set 'foo', 'bar' # traced!

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for redis instrumentation redis

You can also set per-instance configuration as it follows:

customer_cache = Redis.new
invoice_cache = Redis.new

Datadog.configure(customer_cache, service_name: 'customer-cache')
Datadog.configure(invoice_cache, service_name: invoice-cache')

customer_cache.get(...) # traced call will belong to `customer-cache` service
invoice_cache.get(...) # traced call will belong to `invoice-cache` service

Resque

The Resque integration uses Resque hooks that wraps the perform method. To add tracing to a Resque job, simply do as follows:

require 'ddtrace'

class MyJob
  def self.perform(*args)
    # do_something
  end
end

Datadog.configure do |c|
  c.use :resque, options
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for resque instrumentation resque
workers An array including all worker classes you want to trace (eg [MyJob]) []

Sidekiq

The Sidekiq integration is a server-side middleware which will trace job executions.

You can enable it through Datadog.configure:

require 'ddtrace'

Datadog.configure do |c|
  c.use :sidekiq, options
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for sidekiq instrumentation sidekiq

Sinatra

The Sinatra integration traces requests and template rendering.

To start using the tracing client, make sure you import ddtrace and ddtrace/contrib/sinatra/tracer after either sinatra or sinatra/base:

require 'sinatra'
require 'ddtrace'
require 'ddtrace/contrib/sinatra/tracer'

Datadog.configure do |c|
  c.use :sinatra, options
end

get '/' do
  'Hello world!'
end

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for sinatra instrumentation sinatra
resource_script_names Prepend resource names with script name false
distributed_tracing Enables distributed tracing so that this service trace is connected with a trace of another service if tracing headers are received false
tracer A Datadog::Tracer instance used to instrument the application. Usually you don't need to set that. Datadog.tracer

Sucker Punch

The sucker_punch integration traces all scheduled jobs:

require 'ddtrace'

Datadog.configure do |c|
  c.use :sucker_punch, options
end

# the execution of this job is traced
LogJob.perform_async('login')

Where options is an optional Hash that accepts the following parameters:

Key Description Default
service_name Service name used for sucker_punch instrumentation sucker_punch

Advanced configuration

Tracer settings

To change the default behavior of the Datadog tracer, you can provide custom options inside the Datadog.configure block as in:

# config/initializers/datadog-tracer.rb

Datadog.configure do |c|
  c.tracer option_name: option_value, ...
end

Available options are:

  • enabled: defines if the tracer is enabled or not. If set to false the code could be still instrumented because of other settings, but no spans are sent to the local trace agent.
  • debug: set to true to enable debug logging.
  • hostname: set the hostname of the trace agent.
  • port: set the port the trace agent is listening on.
  • env: set the environment. Rails users may set it to Rails.env to use their application settings.
  • tags: set global tags that should be applied to all spans. Defaults to an empty hash
  • log: defines a custom logger.
  • partial_flush: set to true to enable partial trace flushing (for long running traces.) Disabled by default. Experimental.

Custom logging

By default, all logs are processed by the default Ruby logger. When using Rails, you should see the messages in your application log file.

Datadog client log messages are marked with [ddtrace] so you should be able to isolate them from other messages.

Additionally, it is possible to override the default logger and replace it by a custom one. This is done using the log attribute of the tracer.

f = File.new("my-custom.log", "w+")           # Log messages should go there
Datadog.configure do |c|
  c.tracer log: Logger.new(f)                 # Overriding the default tracer
end

Datadog::Tracer.log.info { "this is typically called by tracing code" }

Environment and tags

By default, the trace agent (not this library, but the program running in the background collecting data from various clients) uses the tags set in the agent config file, see our environments tutorial for details.

These values can be overridden at the tracer level:

Datadog.configure do |c|
  c.tracer tags: { 'env' => 'prod' }
end

This enables you to set this value on a per tracer basis, so you can have for example several applications reporting for different environments on the same host.

Ultimately, tags can be set per span, but env should typically be the same for all spans belonging to a given trace.

Sampling

ddtrace can perform trace sampling. While the trace agent already samples traces to reduce bandwidth usage, client sampling reduces performance overhead.

Datadog::RateSampler samples a ratio of the traces. For example:

# Sample rate is between 0 (nothing sampled) to 1 (everything sampled).
sampler = Datadog::RateSampler.new(0.5) # sample 50% of the traces
Datadog.configure do |c|
  c.tracer sampler: sampler
end

Priority sampling

Priority sampling consists in deciding if a trace will be kept by using a priority attribute that will be propagated for distributed traces. Its value gives indication to the Agent and to the backend on how important the trace is.

The sampler can set the priority to the following values:

  • Datadog::Ext::Priority::AUTO_REJECT: the sampler automatically decided to reject the trace.
  • Datadog::Ext::Priority::AUTO_KEEP: the sampler automatically decided to keep the trace.

For now, priority sampling is disabled by default. Enabling it ensures that your sampled distributed traces will be complete. To enable the priority sampling:

Datadog.configure do |c|
  c.tracer priority_sampling: true
end

Once enabled, the sampler will automatically assign a priority of 0 or 1 to traces, depending on their service and volume.

You can also set this priority manually to either drop a non-interesting trace or to keep an important one. For that, set the context#sampling_priority to:

  • Datadog::Ext::Priority::USER_REJECT: the user asked to reject the trace.
  • Datadog::Ext::Priority::USER_KEEP: the user asked to keep the trace.

When not using distributed tracing, you may change the priority at any time, as long as the trace is not finished yet. But it has to be done before any context propagation (fork, RPC calls) to be effective in a distributed context. Changing the priority after context has been propagated causes different parts of a distributed trace to use different priorities. Some parts might be kept, some parts might be rejected, and this can cause the trace to be partially stored and remain incomplete.

If you change the priority, we recommend you do it as soon as possible, when the root span has just been created.

# Indicate to reject the trace
span.context.sampling_priority = Datadog::Ext::Priority::USER_REJECT

# Indicate to keep the trace
span.context.sampling_priority = Datadog::Ext::Priority::USER_KEEP

Distributed Tracing

To trace requests across hosts, the spans on the secondary hosts must be linked together by setting trace_id and parent_id:

def request_on_secondary_host(parent_trace_id, parent_span_id)
    tracer.trace('web.request') do |span|
       span.parent_id = parent_span_id
       span.trace_id = parent_trace_id

       # perform user code
    end
end

Users can pass along the parent_trace_id and parent_span_id via whatever method best matches the RPC framework.

Below is an example using Net/HTTP and Sinatra, where we bypass the integrations to demo how distributed tracing works.

On the client:

require 'net/http'
require 'ddtrace'

uri = URI('http://localhost:4567/')

Datadog.tracer.trace('web.call') do |span|
  req = Net::HTTP::Get.new(uri)
  req['x-datadog-trace-id'] = span.trace_id.to_s
  req['x-datadog-parent-id'] = span.span_id.to_s

  response = Net::HTTP.start(uri.hostname, uri.port) do |http|
    http.request(req)
  end

  puts response.body
end

On the server:

require 'sinatra'
require 'ddtrace'

get '/' do
  parent_trace_id = request.env['HTTP_X_DATADOG_TRACE_ID']
  parent_span_id = request.env['HTTP_X_DATADOG_PARENT_ID']

  Datadog.tracer.trace('web.work') do |span|
     if parent_trace_id && parent_span_id
       span.trace_id = parent_trace_id.to_i
       span.parent_id = parent_span_id.to_i
     end

    'Hello world!'
  end
end

Rack and Net/HTTP have experimental support for this, they can send and receive these headers automatically and tie spans together automatically, provided you pass a :distributed_tracing option set to true.

Distributed tracing is disabled by default.

Processing Pipeline

Some applications might require that traces be altered or filtered out before they are sent upstream. The processing pipeline allows users to create processors to define such behavior.

Processors can be any object that responds to #call accepting trace as an argument (which is an Array of Datadog::Spans.)

For example:

lambda_processor = ->(trace) do
  # Processing logic...
  trace
end

class MyCustomProcessor
  def call(trace)
    # Processing logic...
    trace
  end
end
custom_processor = MyFancyProcessor.new

#call blocks of processors must return the trace object; this return value will be passed to the next processor in the pipeline.

These processors must then be added to the pipeline via Datadog::Pipeline.before_flush:

Datadog::Pipeline.before_flush(lambda_processor, custom_processor)

You can also define processors using the short-hand block syntax for Datadog::Pipeline.before_flush:

Datadog::Pipeline.before_flush do |trace|
  trace.delete_if { |span| span.name =~ /forbidden/ }
end

Filtering

You can use the Datadog::Pipeline::SpanFilter processor to remove spans, when the block evaluates as truthy:

Datadog::Pipeline.before_flush(
  # Remove spans that match a particular resource
  Datadog::Pipeline::SpanFilter.new { |span| span.resource =~ /PingController/ },
  # Remove spans that are trafficked to localhost
  Datadog::Pipeline::SpanFilter.new { |span| span.get_tag('host') == 'localhost' }
)

Processing

You can use the Datadog::Pipeline::SpanProcessor processor to modify spans:

Datadog::Pipeline.before_flush(
  # Strip matching text from the resource field
  Datadog::Pipeline::SpanProcessor.new { |span| span.resource.gsub!(/password=.*/, '') }
)