Add OTel Operator auto-instrumentation troubleshooting page

content/en/docs/kubernetes/operator/troubleshooting/_index.md

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+---
+title: Troubleshooting the OpenTelemetry Operator for Kubernetes
+linkTitle: Troubleshooting
+description:
+  Contains a collection of tips for troubleshooting various aspects of the
+  OpenTelemetry Kubernetes Operator. For example, what to do when the target
+  allocator isn't scraping metrics.
+---

content/en/docs/kubernetes/operator/troubleshooting/automatic.md

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+---
+title: Auto-instrumentation
+---
+
+If you're using the [OpenTelemetry Operator](/docs/kubernetes/operator)'s
+capability to inject [auto-instrumentation](/docs/kubernetes/operator/automatic)
+and you're not seeing any traces or metrics, follow these
+troubleshooting steps to understand what’s going on.
+
+## Troubleshooting steps
+
+### Check installation status
+
+After installing the `Instrumentation` resource, make sure that it is
+installed correctly by running this command:
+
+```shell
+kubectl describe otelinst -n <namespace>
+```
+
+Where `<namespace>` is the namespace in which the `Instrumentation` resource is
+deployed.
+
+Your output should look like this:
+
+```yaml
+Name:         python-instrumentation
+Namespace:    application
+Labels:       app.kubernetes.io/managed-by=opentelemetry-operator
+Annotations:  instrumentation.opentelemetry.io/default-auto-instrumentation-apache-httpd-image:
+               ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-apache-httpd:1.0.3
+             instrumentation.opentelemetry.io/default-auto-instrumentation-dotnet-image:
+               ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-dotnet:0.7.0
+             instrumentation.opentelemetry.io/default-auto-instrumentation-go-image:
+               ghcr.io/open-telemetry/opentelemetry-go-instrumentation/autoinstrumentation-go:v0.2.1-alpha
+             instrumentation.opentelemetry.io/default-auto-instrumentation-java-image:
+               ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.26.0
+             instrumentation.opentelemetry.io/default-auto-instrumentation-nodejs-image:
+               ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.40.0
+             instrumentation.opentelemetry.io/default-auto-instrumentation-python-image:
+               ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.39b0
+API Version:  opentelemetry.io/v1alpha1
+Kind:         Instrumentation
+Metadata:
+ Creation Timestamp:  2023-07-28T03:42:12Z
+ Generation:          1
+ Resource Version:    3385
+ UID:                 646661d5-a8fc-4b64-80b7-8587c9865f53
+Spec:
+...
+ Exporter:
+   Endpoint:  http://otel-collector-collector.opentelemetry.svc.cluster.local:4318
+...
+ Propagators:
+   tracecontext
+   baggage
+ Python:
+   Image:  ghcr.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.39b0
+   Resource Requirements:
+     Limits:
+       Cpu:     500m
+       Memory:  32Mi
+     Requests:
+       Cpu:     50m
+       Memory:  32Mi
+ Resource:
+ Sampler:
+Events:  <none>
+```
+
+### Check the OpenTelemetry Operator logs
+
+Check the OpenTelemetry Operator logs for errors by running this command:
+
+```shell
+kubectl logs -l app.kubernetes.io/name=opentelemetry-operator --container manager -n opentelemetry-operator-system --follow
+```
+
+The logs should not show any errors related to auto-instrumentation errors.
+
+### Check deployment order
+
+Make sure the deployment order is correct. The `Instrumentation` resource
+must be deployed before deploying the corresponding `Deployment` resources
+that are auto-instrumented.
+
+Consider the following auto-instrumentation annotation snippet:
+
+```yaml
+annotations:
+  instrumentation.opentelemetry.io/inject-python: 'true'
+```
+
+
+When the pod starts up, the annotation tells the Operator to look for an
+`Instrumentation` resource in the pod’s namespace, and to inject Python
+auto-instrumentation into the pod. It adds an
+[init-container](https://kubernetes.io/docs/concepts/workloads/pods/init-containers/)
+called `opentelemetry-auto-instrumentation` to the application’s pod, which is
+then used to inject the auto-instrumentation into the app container.
+
+If the `Instrumentation` resource isn’t present by the time the `Deployment`
+is deployed, the `init-container` can’t be created. This means that if the
+`Deployment` resource is deployed before you deploy the `Instrumentation`
+resource, the auto-instrumentation fails to initialize.
+
+Check that the `opentelemetry-auto-instrumentation` `init-container` has started
+up correctly (or has even started up at all), by running the following command:
+
+```shell
+kubectl get events -n <your_app_namespace>
+```
+
+Which should result in output that looks like the following example:
+
+```text
+53s         Normal   Created             pod/py-otel-server-7f54bf4cbc-p8wmj    Created container opentelemetry-auto-instrumentation
+53s         Normal   Started             pod/py-otel-server-7f54bf4cbc-p8wmj    Started container opentelemetry-auto-instrumentation
+```
+
+If the output is missing `Created` or `Started` entries for
+`opentelemetry-auto-instrumentation`, there might be an issue with
+your auto-instrumentation configuration. This can be the result of any of the
+following:
+
+- The `Instrumentation` resource wasn’t installed or wasn’t installed
+  properly.
+- The `Instrumentation` resource was installed after the application was
+  deployed.
+- There’s an error in the auto-instrumentation annotation, or the annotation is in
+  the wrong spot. See the next section.
+
+You might also want to check the output of the events command for any errors, as
+these might help point to your issue.
+
+### Check the auto-instrumentation configuration
+
+The auto-instrumentation annotation might have not been added
+correctly. Check for the following:
+
+- Are you auto-instrumenting for the right language? For example, did you
+  try to auto-instrument a Python application by adding a JavaScript
+  auto-instrumentation annotation instead?
+- Did you put the auto-instrumentation annotation in the right location? When
+  you’re defining a `Deployment` resource, there are two locations where you could
+  add annotations: `spec.metadata.annotations`, and
+  `spec.template.metadata.annotations`. The auto-instrumentation annotation
+  needs to be added to `spec.template.metadata.annotations`, otherwise it doesn't
+  work.
+
+### Check auto-instrumentation endpoint configuration
+
+The `spec.exporter.endpoint` configuration in the `Instrumentation` resource
+allows you to define the destination for your telemetry data. If you omit it, it
+defaults to `http://localhost:4317`, which causes the data to be dropped.
+
+If you’re sending out your telemetry to a [Collector](/docs/collector/),
+the value of `spec.exporter.endpoint` must reference the name of your
+Collector
+[`Service`](https://kubernetes.io/docs/concepts/services-networking/service/).
+
+For example: `http://otel-collector.opentelemetry.svc.cluster.local:4318`.
+
+Where `otel-collector` is the name of the OTel Collector Kubernetes [`Service`](https://kubernetes.io/docs/concepts/services-networking/service/).
+
+In addition, if the Collector is running in a different namespace, you must append `opentelemetry.svc.cluster.local` to the Collector’s service name, where `opentelemetry` is the namespace in which the Collector resides. It can be any namespace of your choosing.
+
+Finally, make sure that you are using the right Collector port. Normally, you
+can choose either `4317` (gRPC) or `4318` (HTTP); however, for
+[Python auto-instrumentation, you can only use `4318`](/docs/kubernetes/operator/automatic/#python).