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docs: add links to most workload word occurrences (keptn#2327)
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docs/content/en/docs/architecture/deployment-flow.md

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### Pre-deployment evaluation phase
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Pre-deployment evaluation can be used to assert the status of the cluster
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or of services the workload depends on,
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or of services the [workload](https://kubernetes.io/docs/concepts/workloads/) depends on,
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to assure it is deployed only if the specified prerequisites are met.
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```shell
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### Deployment phase
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The `AppDeploy` phase basically covers
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the entire deployment and check phase of the workloads.
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the entire deployment and check phase of the [workloads](https://kubernetes.io/docs/concepts/workloads/).
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The `KeptnApp` just observes whether
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all pre and post-deployment tasks/evaluation are successful
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and that the pods are deployed successfully.

docs/content/en/docs/getting-started/usecase_metrics.md

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@@ -55,7 +55,7 @@ you may want to do the other exercises:
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[Manage release lifecycle](../intro/usecase-orchestrate.md),
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you learn how to implement
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pre- and post-deployment tasks and evaluations
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to orchestrate the flow of all the `workloads`
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to orchestrate the flow of all the [workloads](https://kubernetes.io/docs/concepts/workloads/)
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that are part of your `application`.
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The steps to implement metrics in an existing cluster are:

docs/content/en/docs/implementing/evaluatemetrics.md

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@@ -9,7 +9,8 @@ to all metrics in the cluster
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and allows you to define metrics based on multiple data platforms
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and multiple instances of any data platform.
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Metrics are fetched independently
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and can be used for an evaluation at workload- and application-level, or for scaling your workloads.
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and can be used for an evaluation at [workload-](https://kubernetes.io/docs/concepts/workloads/)
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and application-level, or for scaling your [workloads](https://kubernetes.io/docs/concepts/workloads/).
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This data can be displayed on Grafana
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or another standard dashboard application that you configure

docs/content/en/docs/implementing/evaluations.md

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@@ -16,7 +16,7 @@ file specifies the `app-pre-deploy-eval-2` evaluation as follows:
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The `evaluationTarget` is set to be `>1`,
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so this evaluation ensures that more than 1 CPU is available
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before the workload or application is deployed.
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before the [workload](https://kubernetes.io/docs/concepts/workloads/) or application is deployed.
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This evaluation references the
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[KeptnMetric](../yaml-crd-ref/metric.md) resource
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[ReplicaSets](https://kubernetes.io/docs/concepts/workloads/controllers/replicaset/),
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you must:
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* Annotate your `Workloads`
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* Annotate your [workloads](https://kubernetes.io/docs/concepts/workloads/)
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to identify the `KeptnEvaluationDefinition` resource you want to run
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pre- and post-deployment for the specific workloads.
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pre- and post-deployment for the specific [workloads](https://kubernetes.io/docs/concepts/workloads/).
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* Manually edit all
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[KeptnApp](../yaml-crd-ref/app.md) resources
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to specify the `KeptnEvaluationDefinition` to be run

docs/content/en/docs/implementing/otel.md

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@@ -11,7 +11,7 @@ of what Kubernetes does in the context of a Deployment.
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To do this,
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Keptn introduces the concept of an `application`,
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which is an abstraction that connects multiple
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Workloads that logically belong together,
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[Workloads](https://kubernetes.io/docs/concepts/workloads/) that logically belong together,
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even if they use different deployment strategies.
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This means that:
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Keptn starts collecting these metrics
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as soon as you apply
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[basic annotations](integrate/#basic-annotations)
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to the Workload resource.
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to the [workload](https://kubernetes.io/docs/concepts/workloads/).
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Metrics are collected only for the resources
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that are annotated.
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docs/content/en/docs/implementing/tasks-non-k8s-apps.md

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---
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Keptn Tasks running on a Kubernetes cluster
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can be triggered for workloads and applications
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can be triggered for [workloads](https://kubernetes.io/docs/concepts/workloads/) and applications
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that are deployed outside of Kubernetes.
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For example, Keptn could trigger load and performance tests
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for an application that is deployed on a virtual machine.
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You must manually create the
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[KeptnTask](../yaml-crd-ref/task.md) resource.
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In the standard operating mode, when Keptn is managing workloads,
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In the standard operating mode, when Keptn is managing [workloads](https://kubernetes.io/docs/concepts/workloads/),
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the creation of the `KeptnTask` resource is automatic.
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Moreover, each time you want to execute a `KeptnTask`,

docs/content/en/docs/install/install.md

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for tasks such as enforcing checks natively,
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stopping a deployment from proceeding when criteria are not met,
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doing post-deployment evaluations
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and tracing all activities of all deployment workloads on the cluster.
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and tracing all activities of all deployment [workloads](https://kubernetes.io/docs/concepts/workloads/) on the cluster.
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Two methods are supported for installing Keptn:
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docs/content/en/docs/install/k8s.md

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resources and
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[KeptnApp](../yaml-crd-ref/app.md)
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resources
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that are activated and defined by annotations to each Workload.
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that are activated and defined by annotations to each workload.
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* [KeptnMetricsProvider](../yaml-crd-ref/metricsprovider.md)
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resources need to be located
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in the same namespace as the associated
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* Run all your Keptn work in a single namespace
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* Create a separate namespace for each logical grouping of your Keptn work
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* Create a separate namespace for each workload
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* Create a separate namespace for each [workload](https://kubernetes.io/docs/concepts/workloads/)

docs/content/en/docs/intro/_index.md

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Keptn observability makes it easy to understand
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deployment durations and failures across multiple deployment strategies.
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* Provides observability data for standard Kubernetes workload resources
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* Provides observability data for standard Kubernetes [workload](https://kubernetes.io/docs/concepts/workloads/) resources
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as well as
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[KeptnApp](https://lifecycle.keptn.sh/docs/yaml-crd-ref/app/)
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resources (which connect logically related workloads)
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resources (which connect logically related [workloads](https://kubernetes.io/docs/concepts/workloads/))
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using different deployment strategies.
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* Captures
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run in sequential order.
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Keptn tasks and evaluations can be run
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for either a Kubernetes workload (single service) resource
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for either a Kubernetes [workload](https://kubernetes.io/docs/concepts/workloads/) (single service) resource
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or a
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[KeptnApp](../yaml-crd-ref/app.md) resource,
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which is a single, cohesive unit that groups multiple workloads.
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which is a single, cohesive unit that groups multiple [workloads](https://kubernetes.io/docs/concepts/workloads/).
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For more information, see:
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* [Keptn tasks](../implementing/tasks) guide

docs/content/en/docs/intro/usecase-observability.md

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To do this,
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Keptn introduces the concept of an `application`,
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which is an abstraction that connects multiple
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Workloads that logically belong together,
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workloads that logically belong together,
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even if they use different deployment strategies.
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This means that:
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[Manage release lifecycle](usecase-orchestrate.md),
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you learn how to implement
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pre- and post-deployment tasks and evaluations
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to orchestrate the flow of all the `workloads`
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to orchestrate the flow of all the [workloads](https://kubernetes.io/docs/concepts/workloads/)
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that are part of your `application`.
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This exercise shows how to standardize access
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[Basic annotations](../implementing/integrate/#basic-annotations)
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to integrate Keptn into your Kubernetes cluster
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by applying basic annotations
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to your workload and pod resources.
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to your [workload](https://kubernetes.io/docs/concepts/workloads/) resources.
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and to create appropriate
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[KeptnApp](../yaml-crd-ref/app.md)
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resources that aggregate
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all the `workloads` for a logical deployment into a single resource.
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all the [workloads](https://kubernetes.io/docs/concepts/workloads/) for a logical deployment into a single resource.
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## DORA metrics
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Note that, from the `KeptnApp` YAML file,
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you can either increment the version number of the application
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(which causes all workloads to be rerun and produce observability data)
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or you can increment the version number of a single workload,
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(which causes just that workload to be rerun and produce observability data).
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(which causes all [workloads](https://kubernetes.io/docs/concepts/workloads/) to be rerun and produce observability data)
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or you can increment the version number of a single [workload](https://kubernetes.io/docs/concepts/workloads/),
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(which causes just that [workload](https://kubernetes.io/docs/concepts/workloads/)
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to be rerun and produce observability data).
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The videos that go with this exercise show how the
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DORA, OpenTelemetry, and Keptn metrics information

docs/content/en/docs/intro/usecase-orchestrate.md

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* Keptn is application aware,
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so can extend the deployment with tasks and evaluations that
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are run either before or after your whole application starts the deployment
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or at the individual workload level.
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or at the individual [workload](https://kubernetes.io/docs/concepts/workloads/) level.
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* Validate any Keptn metric,
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either pre- or post-deployment,
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using the metrics from the Keptn Metrics Server introduced in
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by applying basic annotations to your `Deployment` resource.
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This also creates appropriate
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[KeptnApp](../yaml-crd-ref/app.md) resources
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which aggregate workloads that are combined into the released product,
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which aggregate [workloads](https://kubernetes.io/docs/concepts/workloads/) that are combined into the released product,
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regardless of the tools being used.
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## Define evaluations to be performed pre- and post-deployment
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You can view the actual JavaScript code for the task in the repository.
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You see that "context" is important in this code.
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This refers to the context in which this code executes --
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for which application, for which version, for which Workload.
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for which application, for which version, for which workload.
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Because the slack server that is required to execute this task
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is protected by a secret, the task definition also specifies that secret.

docs/content/en/docs/troubleshooting.md

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Welcome to the Keptn troubleshooting guide.
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This guide will help you address common issues that you might encounter while using Keptn
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for managing your workloads.
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for managing your [workloads](https://kubernetes.io/docs/concepts/workloads/).
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Below are some common problems and their solutions:
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## Keptn is installed but it is not aware of my workloads
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If you are facing an issue where Keptn is installed but does not seem to be aware of your workloads, follow these steps:
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If you are facing an issue where Keptn is installed but does not seem to be aware of your
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[workloads](https://kubernetes.io/docs/concepts/workloads/), follow these steps:
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1. Ensure that the namespace you wish to target is [annotated correctly](https://lifecycle.keptn.sh/docs/install/install/#enable-klt-for-your-cluster).
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2. Make sure your workloads (e.g., Deployment manifests) have the [three required annotations](https://lifecycle.keptn.sh/docs/implementing/integrate/#annotate-workloads).
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2. Make sure your [workloads](https://kubernetes.io/docs/concepts/workloads/)
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(e.g., Deployment manifests) have the [three required annotations](https://lifecycle.keptn.sh/docs/implementing/integrate/#annotate-workloads).
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## Keptn is causing my pods to be pending
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If your pods are stuck in a pending state and Keptn seems to be the cause, it might be due
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to a pre-deployment task or evaluation.
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Follow these steps:
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The most probable reason is that a pre-deployment task in your workload is either failing or has not completed yet.
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The most probable reason is that a pre-deployment task in your
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[workload](https://kubernetes.io/docs/concepts/workloads/) is either failing or has not completed yet.
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Failing pre-deployment evaluation tasks will prevent a pod from being scheduled.
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docs/content/en/docs/yaml-crd-ref/app.md

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A `KeptnApp` resource lists all the workloads
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A `KeptnApp` resource lists all the [workloads](https://kubernetes.io/docs/concepts/workloads/)
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that constitute a logical application.
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It contains information about:
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- All workloads and checks
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- All [workloads](https://kubernetes.io/docs/concepts/workloads/) and checks
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that are associated with a Keptn application
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- A list of tasks and evaluations to be executed
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pre- and post-deployment.
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- **name** - name of this Kubernetes
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[workload](https://kubernetes.io/docs/concepts/workloads/).
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Use the same naming rules listed above for the application name.
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Provide one entry for each workload
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Provide one entry for each [workload](https://kubernetes.io/docs/concepts/workloads/)
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associated with this Keptn application.
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- **version** -- version number for this workload.
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- **version** -- version number for this [workload](https://kubernetes.io/docs/concepts/workloads/).
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Changing this number causes a new execution
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of checks for this workload only,
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of checks for this [workload](https://kubernetes.io/docs/concepts/workloads/) only,
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not the entire application.
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The remaining fields are required only when implementing

docs/content/en/docs/yaml-crd-ref/config.md

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This field must be populated
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in order to export traces to the OpenTelemetry Collector.
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* **keptnAppCreationRequestTimeoutSeconds** --
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interval in which automatic app discovery searches for workloads
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interval in which automatic app discovery searches for [workloads](https://kubernetes.io/docs/concepts/workloads/)
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to put into the same auto-generated [KeptnApp](app.md).
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The default value is 30 (seconds).
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docs/content/en/docs/yaml-crd-ref/evaluationdefinition.md

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to [KeptnMetric](metric.md) queries.
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These are used as part of evaluation tasks
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that Keptn runs
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as part of pre- and post-analysis phases of a workload or application.
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as part of pre- and post-analysis phases of a [workload](https://kubernetes.io/docs/concepts/workloads/) or application.
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## Yaml Synopsis
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