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Fix existing markdown lint issues (#1866)
* Remove empty sdk README * Fix markdown lint issues * Update markdownlint config to ignore single title header * Remove broken link
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@ -14,6 +14,9 @@ MD013: false
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MD024:
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siblings_only: true
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#single-title
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MD025: false
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# ol-prefix
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MD029:
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style: ordered
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@ -54,6 +54,7 @@ Starting from an application using entirely OpenCensus APIs:
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4. Remove OpenCensus exporters and configuration
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To override OpenCensus' DefaultTracer with the bridge:
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```go
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import (
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octrace "go.opencensus.io/trace"
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@ -82,7 +83,7 @@ OpenCensus and OpenTelemetry APIs are not entirely compatible. If the bridge fi
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The problem for monitoring is simpler than the problem for tracing, since there
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are no context propagation issues to deal with. However, it still is difficult
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for users to migrate an entire applications' monitoring at once. It
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should be possible to send metrics generated by OpenCensus libraries to an
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should be possible to send metrics generated by OpenCensus libraries to an
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OpenTelemetry pipeline so that migrating a metric does not require maintaining
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separate export pipelines for OpenCensus and OpenTelemetry.
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@ -102,11 +103,12 @@ Starting from an application using entirely OpenCensus APIs:
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4. Remove OpenCensus Exporters and configuration.
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For example, to swap out the OpenCensus logging exporter for the OpenTelemetry stdout exporter:
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```go
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import (
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"go.opencensus.io/metric/metricexport"
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"go.opentelemetry.io/otel/bridge/opencensus"
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"go.opentelemetry.io/otel/exporters/stdout"
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"go.opentelemetry.io/otel/exporters/stdout"
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"go.opentelemetry.io/otel"
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)
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// With OpenCensus, you could have previously configured the logging exporter like this:
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@ -12,6 +12,7 @@ App + SDK ---> OpenTelemetry Collector ---|
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```
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# Prerequisites
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You will need access to a Kubernetes cluster for this demo. We use a local
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instance of [microk8s](https://microk8s.io/), but please feel free to pick
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your favorite. If you do decide to use microk8s, please ensure that dns
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@ -30,6 +31,7 @@ kubernetes cluster, or use a secured connection (NodePort/LoadBalancer with TLS
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or an ingress extension).
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# Deploying to Kubernetes
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All the necessary Kubernetes deployment files are available in this demo, in the
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[k8s](./k8s) folder. For your convenience, we assembled a [makefile](./Makefile)
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with deployment commands (see below). For those with subtly different systems,
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@ -39,14 +41,18 @@ Makefile will not recognize the alias, and so the commands will have to be run
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manually.
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## Setting up the Prometheus operator
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If you're using microk8s like us, simply do
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```bash
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microk8s enable prometheus
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```
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and you're good to go. Move on to [Using the makefile](#using-the-makefile).
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Otherwise, obtain a copy of the Prometheus Operator stack from
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[coreos](https://github.com/coreos/kube-prometheus):
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```bash
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git clone https://github.com/coreos/kube-prometheus.git
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cd kube-prometheus
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@ -57,11 +63,13 @@ kubectl create -f manifests/
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```
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And to tear down the stack when you're finished:
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```bash
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kubectl delete --ignore-not-found=true -f manifests/ -f manifests/setup
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```
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## Using the makefile
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Next, we can deploy our Jaeger instance, Prometheus monitor, and Collector
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using the [makefile](./Makefile).
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@ -94,6 +102,7 @@ kubectl delete namespaces observability
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```
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# Configuring the OpenTelemetry Collector
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Although the above steps should deploy and configure everything, let's spend
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some time on the [configuration](./k8s/otel-collector.yaml) of the Collector.
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@ -133,6 +142,7 @@ need to create the Jaeger and Prometheus exporters:
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## OpenTelemetry Collector service
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One more aspect in the OpenTelemetry Collector [configuration](./k8s/otel-collector.yaml) worth looking at is the NodePort service used for accessing it:
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```yaml
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apiVersion: v1
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kind: Service
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@ -157,8 +167,8 @@ spec:
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This service will bind the `55680` port used to access the otlp receiver to port `30080` on your cluster's node. By doing so, it makes it possible for us to access the Collector by using the static address `<node-ip>:30080`. In case you are running a local cluster, this will be `localhost:30080`. Note that you can also change this to a LoadBalancer or have an ingress extension for accessing the service.
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# Running the code
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You can find the complete code for this example in the [main.go](./main.go)
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file. To run it, ensure you have a somewhat recent version of Go (preferably >=
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1.13) and do
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@ -171,10 +181,12 @@ The example simulates an application, hard at work, computing for ten seconds
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then finishing.
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# Viewing instrumentation data
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Now the exciting part! Let's check out the telemetry data generated by our
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sample application
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## Jaeger UI
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First, we need to enable an ingress provider. If you've been using microk8s,
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do
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@ -183,20 +195,24 @@ microk8s enable ingress
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```
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Then find out where the Jaeger console is living:
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```bash
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kubectl get ingress --all-namespaces
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```
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For us, we get the output
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```
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NAMESPACE NAME CLASS HOSTS ADDRESS PORTS AGE
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observability jaeger-query <none> * 127.0.0.1 80 5h40m
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```
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indicating that the Jaeger UI is available at
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[http://localhost:80](http://localhost:80). Navigate there in your favorite
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web-browser to view the generated traces.
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## Prometheus
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Unfortunately, the Prometheus operator doesn't provide a convenient
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out-of-the-box ingress route for us to use, so we'll use port-forwarding
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instead. Note: this is a quick-and-dirty solution for the sake of example.
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@ -1,3 +1,5 @@
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# Prometheus Collector Example
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This example demonstrates a metrics export pipeline that supports
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Prometheus (pull) and simultaneously exports OTLP to an OpenTelemetry
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endpoint (push).
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@ -4,19 +4,21 @@ Send an example span to a [Zipkin](https://zipkin.io/) service.
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These instructions expect you have [docker-compose](https://docs.docker.com/compose/) installed.
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Bring up the `zipkin-collector` service and example `zipkin-client` service to send an example trace:
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```sh
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docker-compose up --detach zipkin-collector zipkin-client
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```
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The `zipkin-client` service sends just one trace and exits. Retrieve the `traceId` generated by the `zipkin-client` service; should be the last line in the logs:
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```sh
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docker-compose logs --tail=1 zipkin-client
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```
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With the `traceId` you can view the trace from the `zipkin-collector` service UI hosted on port `9411`, e.g. with `traceId` of `f5695ba3b2ed00ea583fa4fa0badbeef`:
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http://localhost:9411/zipkin/traces/f5695ba3b2ed00ea583fa4fa0badbeef
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With the `traceId` you can view the trace from the `zipkin-collector` service UI hosted on port `9411`, e.g. with `traceId` of `f5695ba3b2ed00ea583fa4fa0badbeef`: [http://localhost:9411/zipkin/traces/f5695ba3b2ed00ea583fa4fa0badbeef](http://localhost:9411/zipkin/traces/f5695ba3b2ed00ea583fa4fa0badbeef)
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Shut down the services when you are finished with the example:
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```sh
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docker-compose down
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```
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## Metric Telemetry Only
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- [prometheus](./metric/prometheus): Exposes metric telemetry as Prometheus metrics.
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- [test](./metric/test): A development tool when testing the telemetry pipeline.
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## Trace Telemetry Only
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# OpenTelemetry-Go Prometheus Exporter
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OpenTelemetry Prometheus exporter
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OpenTelemetry Prometheus exporter
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## Installation
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```
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go get -u go.opentelemetry.io/otel/exporters/metric/prometheus
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```
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# OpenTelemetry-Go Jaeger Exporter
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OpenTelemetry Jaeger exporter
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OpenTelemetry Jaeger exporter
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## Installation
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```
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go get -u go.opentelemetry.io/otel/exporters/trace/jaeger
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```
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