Fixed broken fragments in links (#3790)

hbelmiro · web-flow · commit 36c2ce1e7500 · 2024-07-06T00:34:48.000Z
Signed-off-by: hbelmiro &lt;helber.belmiro@gmail.com&gt;
diff --git a/config.toml b/config.toml
@@ -248,7 +248,7 @@ enable = true
       desc = "Follow us on Twitter to get the latest news!"
     [[params.links.user]]
       name = "Kubeflow Slack"
-      url = "/docs/about/community/#kubeflow-slack"
+      url = "/docs/about/community/#kubeflow-slack-channels"
       icon = "fab fa-slack"
       desc = "Join the Kubeflow Slack Workspace!"
     [[params.links.user]]
diff --git a/content/en/_index.html b/content/en/_index.html
@@ -159,7 +159,7 @@ <h5 class="card-title text-white section-head">Model Serving</h5>
     <h3 class="section-head">Join our Community</h3>
     <p class="mx-auto col-md-7 px-0">
       We are an open and welcoming <a href="/docs/about/community/" target="_blank" rel="noopener">community</a> of software developers, data scientists, and organizations!
-      Check out the <a href="/docs/about/community/#kubeflow-community-call">weekly community call</a>, get involved in discussions on the <a href="/docs/about/community/#kubeflow-mailing-list">mailing list</a> or chat with others on the <a href="/docs/about/community/#kubeflow-slack">Slack Workspace</a>!
+      Check out the <a href="/docs/about/community/#kubeflow-community-call">weekly community call</a>, get involved in discussions on the <a href="/docs/about/community/#kubeflow-mailing-list">mailing list</a> or chat with others on the <a href="/docs/about/community/#kubeflow-slack-channels">Slack Workspace</a>!
     </p>
   </div>
 </div>
diff --git a/content/en/docs/components/katib/installation.md b/content/en/docs/components/katib/installation.md
@@ -21,7 +21,7 @@ You need to install Katib control plane and Python SDK to create Katib Experimen
 ### Installing Control Plane
 
 You can skip these steps if you have already
-[installed Kubeflow platform](/docs/started/installing-kubeflow/#how-to-install-kubeflow)
+[installed Kubeflow platform](/docs/started/installing-kubeflow/)
 using manifests or package distributions. Kubeflow platform includes Katib.
 
 You can install Katib as a standalone component.
diff --git a/content/en/docs/components/katib/overview.md b/content/en/docs/components/katib/overview.md
@@ -69,7 +69,7 @@ Users can even use Katib to optimize non-ML tasks as long as optimization metric
 Katib is integrated with many optimization frameworks such as [Hyperopt](https://hyperopt.github.io/hyperopt/) and
 [Optuna](https://optuna.org/) which implements most of the state of the art optimization algorithms.
 
-Users can leverage Katib control plane to implement and benchmark [their own optimization algorithms](/docs/components/katib/user-guides/hp-tuning/configure-algorithm/#add-a-new-hp-tuning-algorithm-to-katib)
+Users can leverage Katib control plane to implement and benchmark [their own optimization algorithms](/docs/components/katib/user-guides/hp-tuning/configure-algorithm/#use-custom-algorithm-in-katib)
 
 ## Next steps
 
diff --git a/content/en/docs/components/katib/reference/architecture.md b/content/en/docs/components/katib/reference/architecture.md
@@ -84,7 +84,7 @@ The _Worker_ is the process that runs to evaluate a Trial and calculate its obje
 
 The Worker can be any type of Kubernetes resource or
 [Kubernetes CRD](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/).
-Follow the [Trial template guide](/docs/components/katib/user-guides/trial-template/#custom-resource)
+Follow the [Trial template guide](/docs/components/katib/user-guides/trial-template/)
 to check how to support your own Kubernetes resource in Katib.
 
 ## Neural Architecture Search
diff --git a/content/en/docs/components/katib/user-guides/katib-config.md b/content/en/docs/components/katib/user-guides/katib-config.md
@@ -90,7 +90,7 @@ The following parameters set in `.init.controller` configure the Katib controlle
 
 - `trialResources` - list of resources that can be used as a Trial template. The Trial resources
   must be in this format: Kind.version.group (e.g. `TFJob.v1.kubeflow.org`).
-  Follow [this guide](/docs/components/katib/user-guides/trial-template/#use-custom-kubernetes-resource-as-a-trial-template)
+  Follow [this guide](/docs/components/katib/user-guides/trial-template/#use-crds-with-trial-template)
   to understand how to make Katib Trial work with your Kubernetes CRDs.
 
   The default value is `[Job.v1.batch]`
diff --git a/content/en/docs/components/notebooks/api-reference/notebook-v1.md b/content/en/docs/components/notebooks/api-reference/notebook-v1.md
@@ -7,7 +7,7 @@ weight = 10
 <p>Packages:</p>
 <ul>
 <li>
-<a href="#kubeflow.org%2fv1">kubeflow.org/v1</a>
+<a href="#kubeflow.org/v1">kubeflow.org/v1</a>
 </li>
 </ul>
 <h2 id="kubeflow.org/v1">kubeflow.org/v1</h2>
diff --git a/content/en/docs/components/pipelines/legacy-v1/overview/multi-user.md b/content/en/docs/components/pipelines/legacy-v1/overview/multi-user.md
@@ -12,7 +12,7 @@ Please note that Kubeflow Pipelines V2 supports running V1 pipelines in a [backw
 Multi-user isolation for Kubeflow Pipelines is part of Kubeflow's overall [multi-tenancy](/docs/concepts/multi-tenancy/) feature.
 
 {{% alert title="Tip" color="info" %}}
-* Kubeflow Pipelines multi-user isolation is only supported in ["full" Kubeflow deployments](/docs/components/pipelines/legacy-v1/overview/#full-kubeflow-deployment).
+* Kubeflow Pipelines multi-user isolation is only supported in ["full" Kubeflow deployments](/docs/components/pipelines/operator-guides/installation/overview/#full-kubeflow-deployment).
 * Refer to docs about [profiles and namespaces](/docs/components/central-dash/profiles/) for the common Kubeflow multi-user operations 
   like [managing profile contributors](/docs/components/central-dash/profiles/#manage-profile-contributors).
 {{% /alert %}}
diff --git a/content/en/docs/components/pipelines/legacy-v1/sdk/static-type-checking.md b/content/en/docs/components/pipelines/legacy-v1/sdk/static-type-checking.md
@@ -15,7 +15,7 @@ static type checking for fast development iterations.
 
 ## Motivation
 
-A pipeline is a workflow consisting of [components](/docs/components/pipelines/legacy-v1/sdk/component-development/#overview-of-pipelines-and-components) and each
+A pipeline is a workflow consisting of [components](/docs/components/pipelines/legacy-v1/sdk/component-development/) and each
 component contains inputs and outputs. The DSL compiler supports static type checking to ensure the type consistency among the component
 I/Os within the same pipeline. Static type checking helps you to identify component I/O inconsistencies without running the pipeline. 
 It also shortens the development cycles by catching the errors early. 
diff --git a/content/en/docs/components/pipelines/legacy-v1/troubleshooting.md b/content/en/docs/components/pipelines/legacy-v1/troubleshooting.md
@@ -16,7 +16,7 @@ may encounter.
 ## Diagnosing problems in your Kubeflow Pipelines environment
 
 For help diagnosing environment issues that affect Kubeflow Pipelines, run
-the [`kfp diagnose_me` command-line tool](/docs/components/pipelines/legacy-v1/sdk/sdk-overview/#kfp-cli-tool).
+the [`kfp diagnose_me` command-line tool](/docs/components/pipelines/legacy-v1/sdk/sdk-overview/#kubeflow-pipelines-cli-tool).
 
 The `kfp diagnose_me` CLI reports on the configuration of your local
 development environment, Kubernetes cluster, or Google Cloud environment.
diff --git a/content/en/docs/components/pipelines/legacy-v1/tutorials/api-pipelines.md b/content/en/docs/components/pipelines/legacy-v1/tutorials/api-pipelines.md
@@ -38,7 +38,7 @@ wget -O ${PIPELINE_FILE} ${PIPELINE_URL}
 dsl-compile --py ${PIPELINE_FILE} --output ${PIPELINE_NAME}.tar.gz
 ```
 
-After running the commands above, you should get two files in your current directory: `sequential.py` and `sequential.tar.gz`. Run the following command to deploy the generated `.tar.gz` file as you would do using the [Kubeflow Pipelines UI](/docs/components/pipelines/legacy-v1/sdk/component-development/#deploy-the-pipeline), but this time using the REST API.
+After running the commands above, you should get two files in your current directory: `sequential.py` and `sequential.tar.gz`. Run the following command to deploy the generated `.tar.gz` file as you would do using the [Kubeflow Pipelines UI](/docs/components/pipelines/user-guides/core-functions/run-a-pipeline/#1-run-from-the-kfp-dashboard), but this time using the REST API.
 
 ```
 SVC=localhost:8888
diff --git a/content/en/docs/components/pipelines/operator-guides/installation/overview.md b/content/en/docs/components/pipelines/operator-guides/installation/overview.md
@@ -16,7 +16,7 @@ with each option:
 
 * [Kubeflow Pipelines Standalone](#kubeflow-pipelines-standalone) is the minimal
 portable installation that only includes Kubeflow Pipelines.
-* Kubeflow Pipelines as [part of a full Kubeflow deployment](#full-kubeflow-deployment) provides
+* Kubeflow Pipelines as [part of a full Kubeflow deployment](/docs/components/pipelines/operator-guides/installation/overview/#full-kubeflow-deployment) provides
 all Kubeflow components and more integration with each platform.
 * **Beta**: [Google Cloud AI Platform Pipelines](#google-cloud-ai-platform-pipelines) makes it easier to install and use Kubeflow Pipelines on Google Cloud by providing a management UI on [Google Cloud Console](https://console.cloud.google.com/ai-platform/pipelines/clusters).
 * A [local](/docs/components/pipelines/operator-guides/installation/localcluster-deployment) Kubeflow Pipelines deployment for testing purposes.
@@ -25,13 +25,13 @@ all Kubeflow components and more integration with each platform.
 
 1. Do you want to use other Kubeflow components in addition to Pipelines?
 
-    If yes, choose the [full Kubeflow deployment](#full-kubeflow-deployment).
+    If yes, choose the [full Kubeflow deployment](/docs/components/pipelines/operator-guides/installation/overview/#full-kubeflow-deployment).
 1. Can you use a cloud/on-prem Kubernetes cluster?
 
     If you can't, you should try using Kubeflow Pipelines on a local Kubernetes cluster for learning and testing purposes by following the steps in [Deploying Kubeflow Pipelines on a local cluster](/docs/components/pipelines/operator-guides/installation/localcluster-deployment).
 1. Do you want to use Kubeflow Pipelines with [multi-user support](https://github.com/kubeflow/pipelines/issues/1223)?
 
-    If yes, choose the [full Kubeflow deployment](#full-kubeflow-deployment) with version >= v1.1.
+    If yes, choose the [full Kubeflow deployment](/docs/components/pipelines/operator-guides/installation/overview/#full-kubeflow-deployment) with version >= v1.1.
 1. Do you deploy on Google Cloud?
 
     If yes, deploy [Kubeflow Pipelines Standalone](#kubeflow-pipelines-standalone). You can also
@@ -41,7 +41,7 @@ all Kubeflow components and more integration with each platform.
     sections.
 1. You deploy on other platforms.
 
-    Please compare your platform specific [full Kubeflow](#full-kubeflow-deployment) with the
+    Please compare your platform specific [full Kubeflow](/docs/components/pipelines/operator-guides/installation/overview/#full-kubeflow-deployment) with the
     [Kubeflow Pipelines Standalone](#kubeflow-pipelines-standalone) before making your decision.
 
 **Warning:** Choose your installation option with caution, there's no current
diff --git a/content/en/docs/components/pipelines/user-guides/components/additional-functionality.md b/content/en/docs/components/pipelines/user-guides/components/additional-functionality.md
@@ -65,6 +65,6 @@ Note that if you provide a `description` argument to the [`@dsl.pipeline`][dsl-p
 [ir-yaml]: /docs/components/pipelines/user-guides/core-functions/compile-a-pipeline#ir-yaml
 [google-docstring-style]: https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html
 [dsl-pipeline]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/dsl.html#kfp.dsl.pipeline
-[output-artifacts]: /docs/components/pipelines/user-guides/data-handling/artifacts#declaring-inputoutput-artifacts
+[output-artifacts]: /docs/components/pipelines/user-guides/data-handling/artifacts
 [dsl-outputpath]: https://kubeflow-pipelines.readthedocs.io/en/latest/source/dsl.html#kfp.dsl.OutputPath
 [output-type-marker]: https://kubeflow-pipelines.readthedocs.io/en/latest/source/dsl.html#kfp.dsl.Output
diff --git a/content/en/docs/components/pipelines/user-guides/components/compose-components-into-pipelines.md b/content/en/docs/components/pipelines/user-guides/components/compose-components-into-pipelines.md
@@ -208,7 +208,7 @@ def pythagorean(a: float = 1.2, b: float = 1.2) -> float:
 [vertex-pipelines]: https://cloud.google.com/vertex-ai/docs/pipelines/introduction
 [oss-be]: /docs/components/pipelines/operator-guides/installation/
 [data-types]: /docs/components/pipelines/user-guides/data-handling/data-types
-[output-artifacts]: /docs/components/pipelines/user-guides/data-handling/artifacts#using-output-artifacts
+[output-artifacts]: /docs/components/pipelines/user-guides/data-handling/artifacts
 [container-component-outputs]: /docs/components/pipelines/user-guides/components/container-components#create-component-outputs
 [parameters-namedtuple]: /docs/components/pipelines/user-guides/data-handling/parameters#multiple-output-parameters
 [dsl-pipeline-job-name-placeholder]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/dsl.html#kfp.dsl.PIPELINE_JOB_NAME_PLACEHOLDER
diff --git a/content/en/docs/components/training/installation.md b/content/en/docs/components/training/installation.md
@@ -23,7 +23,7 @@ You need to install Training Operator control plane and Python SDK to create tra
 ### Installing Control Plane
 
 You can skip these steps if you have already
-[installed Kubeflow platform](https://www.kubeflow.org/docs/started/installing-kubeflow/#how-to-install-kubeflow)
+[installed Kubeflow platform](https://www.kubeflow.org/docs/started/installing-kubeflow/)
 using manifests or package distributions. Kubeflow platform includes Training Operator.
 
 You can install Training Operator as a standalone component.
diff --git a/content/en/docs/started/installing-kubeflow.md b/content/en/docs/started/installing-kubeflow.md
@@ -20,7 +20,7 @@ You can install Kubeflow using one of these methods:
 
 ## Standalone Kubeflow Components
 
-Some components in the [Kubeflow ecosystem](/docs/started/architecture/#conceptual-overview) may be
+Some components in the [Kubeflow ecosystem](/docs/started/architecture/#kubeflow-ecosystem) may be
 deployed as standalone services, without the need to install the full Kubeflow Platform. You might
 integrate these services as part of your existing AI/ML platform or use them independently.
 
diff --git a/content/en/docs/started/support.md b/content/en/docs/started/support.md
@@ -105,7 +105,7 @@ to helping you diagnose and address the problem if all the following are true:
 You can ask questions and make suggestions in the following places:
 
 * **Slack** for online chat and messaging. See details of Kubeflow's 
-  [Slack workspace and channels](/docs/about/community/#kubeflow-slack).
+  [Slack workspace and channels](/docs/about/community/#kubeflow-slack-channels).
 * **Kubeflow discuss** for email-based group discussion. Join the
   [kubeflow-discuss](/docs/about/community/#kubeflow-mailing-list)
   group.
diff --git a/content/en/events/gsoc-2024.md b/content/en/events/gsoc-2024.md
@@ -15,7 +15,7 @@ Contributor applications open __March 18th, 2024__ and close on __April 2nd, 202
 
 ### Slack
 
-Please [__Join the Kubeflow Slack__](https://www.kubeflow.org/docs/about/community/#kubeflow-slack).
+Please [__Join the Kubeflow Slack__](https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels).
 
 Please __do not__ reach out privately to mentors, instead, start a thread in the [`#gsoc-participants`](https://kubeflow.slack.com/archives/C06LW6Z3RA6) channel so others can see the response. Be kind to our mentors, please search to see if your question has already been answered.
 
