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The frontend component is implemented to call `Lookup()` before each call to the backend component. The frontend component uses the returned version number to route the request to the recommended version of the backend component.
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=== "backend"
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Deploy an initial version of the *backend* component:
[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Copy and paste the contents of the [`abn` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.2/grafana/abn.json) into the text box and *load* it. Associate it with the JSON API data source above.
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[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Copy and paste the contents of the [`abn` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/grafana/abn.json) into the text box and *load* it. Associate it with the JSON API data source above.
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The Iter8 dashboard allows you to compare the behavior of the two versions of the backend component against each other and select a winner. Since user requests are being sent by the load generation script, the values in the report may change over time. The Iter8 dashboard will look like the following:
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To promote the candidate version (`backend-candidate-1`), first update the primary version, `backend`, using the new image. You can also overwrite any metadata describing the version.
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```shell
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kubectl set image deployment/backend abn-sample-backend=iter8/abn-sample-backend:0.13-v2
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kubectl set image deployment/backend abn-sample-backend=iter8/abn-sample-backend:0.17-v2
Copy file name to clipboardExpand all lines: docs/getting-started/first-performance.md
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# Load test HTTP endpoint
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Run your first [Iter8 performance test](concepts.md#design) by load testing a Kubernetes HTTP service and visualizing the performance with an Iter8 Grafana dashboard.
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Run your first performance test by load testing a Kubernetes HTTP service and visualizing the performance with an Iter8 Grafana dashboard.
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[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Paste the contents of the [`http` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.2/grafana/http.json) into the text box and *load* it. Associate it with the JSON API data source defined above.
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[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Paste the contents of the [`http` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/grafana/http.json) into the text box and *load* it. Associate it with the JSON API data source defined above.
The `initialize` action (with strategy `blue-green`) configures the (Istio) service mesh to route all requests to the primary version of the application (`httpbin-0`). It further defines the routing policy that will be used when changes are observed in the application resources. By default, this routing policy splits requests 50-50 between the primary and candidate versions. For detailed configuration options, see the [Helm chart](https://github.com/iter8-tools/iter8/blob/v0.16.0/charts/routing-actions/values.yaml).
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The `initialize` action (with strategy `blue-green`) configures the (Istio) service mesh to route all requests to the primary version of the application (`httpbin-0`). It further defines the routing policy that will be used when changes are observed in the application resources. By default, this routing policy splits requests 50-50 between the primary and candidate versions. For detailed configuration options, see the [Helm chart](https://github.com/iter8-tools/iter8/blob/v0.18.3/charts/routing-actions/values.yaml).
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### Verify routing
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=== "From within the cluster"
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1. Create a `sleep` pod in the cluster from which requests can be made:
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```shell
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curl -s https://raw.githubusercontent.com/iter8-tools/docs/v0.15.2/samples/kserve-serving/sleep.sh | sh -
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curl -s https://raw.githubusercontent.com/iter8-tools/docs/v0.17.3/samples/kserve-serving/sleep.sh | sh -
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```
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2. Exec into the sleep pod:
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You can modify the weight distribution of inference requests as follows:
Note that this workflow has one job that will print out the `client_payload`. The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.5/templates/notify/_payload-github.tpl) is configured with `client_payload` set to `.Report`, a summary of the performance test.
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Note that this workflow has one job that will print out the `client_payload`. The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/templates/notify/_payload-github.tpl) is configured with `client_payload` set to `.Report`, a summary of the performance test.
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Also note that the `on.repository_dispatch.types` is set to `iter8`. The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.5/templates/notify/_payload-github.tpl) is configured with `event_type` set to `iter8`. This indicates that once the `repository_dispatch` has been sent, only workflows on the default branch with `on.repository_dispatch.types` set to `iter8` will be triggered.
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Also note that the `on.repository_dispatch.types` is set to `iter8`. The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/templates/notify/_payload-github.tpl) is configured with `event_type` set to `iter8`. This indicates that once the `repository_dispatch` has been sent, only workflows on the default branch with `on.repository_dispatch.types` set to `iter8` will be triggered.
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3. Create a GitHub [personal access token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token) for the `token` parameter.
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4. Ensure that you have a Kubernetes cluster and the [`kubectl` CLI](https://kubernetes.io/docs/reference/kubectl/). You can create a local Kubernetes cluster using tools like [Kind](https://kind.sigs.k8s.io/) or [Minikube](https://minikube.sigs.k8s.io/docs/).
8. Verify that the workflow has been triggered after the performance test has completed.
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??? note "Some variations and extensions of the `github` task"
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The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.5/templates/notify/_payload-github.tpl) sends a summary of the performance test.
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The default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/templates/notify/_payload-github.tpl) sends a summary of the performance test.
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In your workflow, you can read from the report and use that data for control flow or use snippets of that data in different actions. For example, you can check to see if there have been any task failures and take alternative actions.
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You do not need to use the default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.5/templates/notify/_payload-github.tpl). You can provide your own payload by overriding the default of the `payloadTemplateURL`.
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You do not need to use the default `github` task [payload](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/templates/notify/_payload-github.tpl). You can provide your own payload by overriding the default of the `payloadTemplateURL`.
[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Copy and paste the contents of the [`abn` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.16.2/grafana/abn.json) into the text box and *load* it. Associate it with the JSON API data source above.
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[Create a new dashboard](http://localhost:3000/dashboards) by *import*. Copy and paste the contents of the [`abn` Grafana dashboard](https://raw.githubusercontent.com/iter8-tools/iter8/v0.18.3/grafana/abn.json) into the text box and *load* it. Associate it with the JSON API data source above.
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The Iter8 dashboard allows you to compare the behavior of the two versions of the backend component against each other and select a winner. Since user requests are being sent by the load generation script, the values in the report may change over time. The Iter8 dashboard will look like the following:
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