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# OpenCensus Libraries for Go
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[![Build Status][travis-image]][travis-url]
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[![Windows Build Status][appveyor-image]][appveyor-url]
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[![GoDoc][godoc-image]][godoc-url]
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[![Gitter chat][gitter-image]][gitter-url]
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OpenCensus Go is a Go implementation of OpenCensus, a toolkit for
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collecting application performance and behavior monitoring data.
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Currently it consists of three major components: tags, stats and tracing.
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## Installation
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```
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$ go get -u go.opencensus.io
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```
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The API of this project is still evolving, see: [Deprecation Policy](#deprecation-policy).
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The use of vendoring or a dependency management tool is recommended.
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## Prerequisites
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OpenCensus Go libraries require Go 1.8 or later.
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## Getting Started
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The easiest way to get started using OpenCensus in your application is to use an existing
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integration with your RPC framework:
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* [net/http](https://godoc.org/go.opencensus.io/plugin/ochttp)
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* [gRPC](https://godoc.org/go.opencensus.io/plugin/ocgrpc)
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* [database/sql](https://godoc.org/github.com/opencensus-integrations/ocsql)
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* [Go kit](https://godoc.org/github.com/go-kit/kit/tracing/opencensus)
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* [Groupcache](https://godoc.org/github.com/orijtech/groupcache)
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* [Caddy webserver](https://godoc.org/github.com/orijtech/caddy)
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* [MongoDB](https://godoc.org/github.com/orijtech/mongo-go-driver)
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* [Redis gomodule/redigo](https://godoc.org/github.com/orijtech/redigo)
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* [Redis goredis/redis](https://godoc.org/github.com/orijtech/redis)
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* [Memcache](https://godoc.org/github.com/orijtech/gomemcache)
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If you're using a framework not listed here, you could either implement your own middleware for your
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framework or use [custom stats](#stats) and [spans](#spans) directly in your application.
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## Exporters
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OpenCensus can export instrumentation data to various backends.
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OpenCensus has exporter implementations for the following, users
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can implement their own exporters by implementing the exporter interfaces
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([stats](https://godoc.org/go.opencensus.io/stats/view#Exporter),
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[trace](https://godoc.org/go.opencensus.io/trace#Exporter)):
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* [Prometheus][exporter-prom] for stats
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* [OpenZipkin][exporter-zipkin] for traces
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* [Stackdriver][exporter-stackdriver] Monitoring for stats and Trace for traces
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* [Jaeger][exporter-jaeger] for traces
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* [AWS X-Ray][exporter-xray] for traces
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* [Datadog][exporter-datadog] for stats and traces
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* [Graphite][exporter-graphite] for stats
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* [Honeycomb][exporter-honeycomb] for traces
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## Overview
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In a microservices environment, a user request may go through
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multiple services until there is a response. OpenCensus allows
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you to instrument your services and collect diagnostics data all
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through your services end-to-end.
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## Tags
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Tags represent propagated key-value pairs. They are propagated using `context.Context`
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in the same process or can be encoded to be transmitted on the wire. Usually, this will
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be handled by an integration plugin, e.g. `ocgrpc.ServerHandler` and `ocgrpc.ClientHandler`
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for gRPC.
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Package `tag` allows adding or modifying tags in the current context.
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[embedmd]:# (internal/readme/tags.go new)
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```go
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ctx, err = tag.New(ctx,
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tag.Insert(osKey, "macOS-10.12.5"),
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tag.Upsert(userIDKey, "cde36753ed"),
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)
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if err != nil {
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log.Fatal(err)
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}
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```
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## Stats
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OpenCensus is a low-overhead framework even if instrumentation is always enabled.
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In order to be so, it is optimized to make recording of data points fast
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and separate from the data aggregation.
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OpenCensus stats collection happens in two stages:
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* Definition of measures and recording of data points
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* Definition of views and aggregation of the recorded data
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### Recording
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Measurements are data points associated with a measure.
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Recording implicitly tags the set of Measurements with the tags from the
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provided context:
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[embedmd]:# (internal/readme/stats.go record)
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```go
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stats.Record(ctx, videoSize.M(102478))
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```
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### Views
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Views are how Measures are aggregated. You can think of them as queries over the
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set of recorded data points (measurements).
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Views have two parts: the tags to group by and the aggregation type used.
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Currently three types of aggregations are supported:
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* CountAggregation is used to count the number of times a sample was recorded.
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* DistributionAggregation is used to provide a histogram of the values of the samples.
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* SumAggregation is used to sum up all sample values.
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[embedmd]:# (internal/readme/stats.go aggs)
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```go
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distAgg := view.Distribution(1<<32, 2<<32, 3<<32)
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countAgg := view.Count()
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sumAgg := view.Sum()
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```
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Here we create a view with the DistributionAggregation over our measure.
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[embedmd]:# (internal/readme/stats.go view)
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```go
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if err := view.Register(&view.View{
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Name: "example.com/video_size_distribution",
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Description: "distribution of processed video size over time",
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Measure: videoSize,
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Aggregation: view.Distribution(1<<32, 2<<32, 3<<32),
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}); err != nil {
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log.Fatalf("Failed to register view: %v", err)
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}
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```
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Register begins collecting data for the view. Registered views' data will be
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exported via the registered exporters.
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## Traces
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A distributed trace tracks the progression of a single user request as
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it is handled by the services and processes that make up an application.
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Each step is called a span in the trace. Spans include metadata about the step,
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including especially the time spent in the step, called the span’s latency.
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Below you see a trace and several spans underneath it.
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### Spans
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Span is the unit step in a trace. Each span has a name, latency, status and
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additional metadata.
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Below we are starting a span for a cache read and ending it
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when we are done:
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[embedmd]:# (internal/readme/trace.go startend)
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```go
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ctx, span := trace.StartSpan(ctx, "cache.Get")
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defer span.End()
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// Do work to get from cache.
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```
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### Propagation
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Spans can have parents or can be root spans if they don't have any parents.
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The current span is propagated in-process and across the network to allow associating
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new child spans with the parent.
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In the same process, `context.Context` is used to propagate spans.
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`trace.StartSpan` creates a new span as a root if the current context
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doesn't contain a span. Or, it creates a child of the span that is
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already in current context. The returned context can be used to keep
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propagating the newly created span in the current context.
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[embedmd]:# (internal/readme/trace.go startend)
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```go
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ctx, span := trace.StartSpan(ctx, "cache.Get")
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defer span.End()
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// Do work to get from cache.
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```
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Across the network, OpenCensus provides different propagation
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methods for different protocols.
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* gRPC integrations use the OpenCensus' [binary propagation format](https://godoc.org/go.opencensus.io/trace/propagation).
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* HTTP integrations use Zipkin's [B3](https://github.com/openzipkin/b3-propagation)
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by default but can be configured to use a custom propagation method by setting another
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[propagation.HTTPFormat](https://godoc.org/go.opencensus.io/trace/propagation#HTTPFormat).
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## Execution Tracer
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With Go 1.11, OpenCensus Go will support integration with the Go execution tracer.
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See [Debugging Latency in Go](https://medium.com/observability/debugging-latency-in-go-1-11-9f97a7910d68)
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for an example of their mutual use.
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## Profiles
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OpenCensus tags can be applied as profiler labels
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for users who are on Go 1.9 and above.
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[embedmd]:# (internal/readme/tags.go profiler)
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```go
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ctx, err = tag.New(ctx,
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tag.Insert(osKey, "macOS-10.12.5"),
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tag.Insert(userIDKey, "fff0989878"),
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)
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if err != nil {
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log.Fatal(err)
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}
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tag.Do(ctx, func(ctx context.Context) {
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// Do work.
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// When profiling is on, samples will be
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// recorded with the key/values from the tag map.
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})
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```
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A screenshot of the CPU profile from the program above:
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## Deprecation Policy
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Before version 1.0.0, the following deprecation policy will be observed:
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No backwards-incompatible changes will be made except for the removal of symbols that have
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been marked as *Deprecated* for at least one minor release (e.g. 0.9.0 to 0.10.0). A release
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removing the *Deprecated* functionality will be made no sooner than 28 days after the first
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release in which the functionality was marked *Deprecated*.
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[travis-image]: https://travis-ci.org/census-instrumentation/opencensus-go.svg?branch=master
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[travis-url]: https://travis-ci.org/census-instrumentation/opencensus-go
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[appveyor-image]: https://ci.appveyor.com/api/projects/status/vgtt29ps1783ig38?svg=true
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[appveyor-url]: https://ci.appveyor.com/project/opencensusgoteam/opencensus-go/branch/master
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[godoc-image]: https://godoc.org/go.opencensus.io?status.svg
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[godoc-url]: https://godoc.org/go.opencensus.io
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[gitter-image]: https://badges.gitter.im/census-instrumentation/lobby.svg
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[gitter-url]: https://gitter.im/census-instrumentation/lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
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[new-ex]: https://godoc.org/go.opencensus.io/tag#example-NewMap
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[new-replace-ex]: https://godoc.org/go.opencensus.io/tag#example-NewMap--Replace
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[exporter-prom]: https://godoc.org/contrib.go.opencensus.io/exporter/prometheus
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[exporter-stackdriver]: https://godoc.org/contrib.go.opencensus.io/exporter/stackdriver
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[exporter-zipkin]: https://godoc.org/contrib.go.opencensus.io/exporter/zipkin
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[exporter-jaeger]: https://godoc.org/contrib.go.opencensus.io/exporter/jaeger
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[exporter-xray]: https://github.com/census-ecosystem/opencensus-go-exporter-aws
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[exporter-datadog]: https://github.com/DataDog/opencensus-go-exporter-datadog
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[exporter-graphite]: https://github.com/census-ecosystem/opencensus-go-exporter-graphite
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[exporter-honeycomb]: https://github.com/honeycombio/opencensus-exporter
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