Fixed broken links

Signed-off-by: hbelmiro <helber.belmiro@gmail.com>

content/en/_redirects

@@ -25,7 +25,7 @@
 /docs/pipelines/                                    /docs/components/pipelines
 /docs/pipelines/output-viewer/                      /docs/components/pipelines/legacy-v1/sdk/output-viewer/
 /docs/pipelines/pipelines-metrics/                  /docs/components/pipelines/legacy-v1/sdk/pipelines-metrics/
-/docs/pipelines/build-component/                    /docs/components/pipelines/legacy-v1/sdk/build-component/
+/docs/pipelines/build-component/                    /docs/components/pipelines/legacy-v1/sdk/component-development//
 /docs/pipelines/install-sdk/                        /docs/components/pipelines/legacy-v1/sdk/install-sdk/
 /docs/pipelines/lightweight-python-components/      /docs/components/pipelines/legacy-v1/sdk/python-function-components/
 /docs/pipelines/sdk/lightweight-python-components/  /docs/components/pipelines/legacy-v1/sdk/python-function-components/

content/en/docs/components/pipelines/concepts/component.md

@@ -62,6 +62,6 @@ deserialize the data for use in the downstream component.
   to deploy Kubeflow and run a sample pipeline directly from the Kubeflow 
   Pipelines UI.
 * Build your own 
-  [component and pipeline](/docs/components/pipelines/legacy-v1/sdk/build-component/).
+  [component and pipeline](/docs/components/pipelines/legacy-v1/sdk/component-development//).
 * Build a [reusable component](/docs/components/pipelines/legacy-v1/sdk/component-development/) for
   sharing in multiple pipelines.

content/en/docs/components/pipelines/concepts/pipeline-root.md

@@ -54,7 +54,7 @@ kubectl edit configMap kfp-launcher -n ${namespace}
 This pipeline root will be the default pipeline root for all pipelines running in the Kubernetes namespace unless you override it using one of the following options:
 
 ####  Via Building Pipelines
-You can configure a pipeline root through the `kfp.dsl.pipeline` annotation when [building pipelines](https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/build-pipeline/#build-your-pipeline)
+You can configure a pipeline root through the `kfp.dsl.pipeline` annotation when [building pipelines](/docs/components/pipelines/legacy-v1/sdk/build-pipeline/#build-your-pipeline)
 
 ####  Via Submitting a Pipeline through SDK
 You can configure pipeline root via `pipeline_root` argument when you submit a Pipeline using one of the following:

content/en/docs/components/pipelines/legacy-v1/installation/choose-executor.md

@@ -32,9 +32,9 @@ improvements can make it the default executor that most people should use going
 * Security: more secure
   * No `privileged` access.
   * Cannot escape the privileges of the pod's service account.
-* Migration: `command` must be specified in [Kubeflow Pipelines component specification](https://www.kubeflow.org/docs/components/pipelines/reference/component-spec/).
+* Migration: `command` must be specified in [Kubeflow Pipelines component specification](/docs/components/pipelines/reference/component-spec/).
 
-  Note, the same migration requirement is required by [Kubeflow Pipelines v2 compatible mode](https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/v2-compatibility/), refer to
+  Note, the same migration requirement is required by [Kubeflow Pipelines v2 compatible mode](/docs/components/pipelines/legacy-v1/sdk/v2-compatibility/), refer to
   [known caveats & breaking changes](https://github.com/kubeflow/pipelines/issues/6133).
 
 #### Migrate to Emissary Executor
@@ -105,7 +105,7 @@ existing clusters.
 ##### Migrate pipeline components to run on emissary executor
 
 Some pipeline components require manual updates to run on emissary executor.
-For [Kubeflow Pipelines component specification](https://www.kubeflow.org/docs/components/pipelines/reference/component-spec/) YAML,
+For [Kubeflow Pipelines component specification](/docs/components/pipelines/reference/component-spec/) YAML,
 the `command` field must be specified.
 
 Step by step component migration tutorial:
@@ -152,7 +152,7 @@ Step by step component migration tutorial:
 1. The updated component can run on emissary executor now.
 
 Note: Kubeflow Pipelines SDK compiler always specifies a command for
-[python function based components](https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/python-function-components/).
+[python function based components](/docs/components/pipelines/legacy-v1/sdk/python-function-components/).
 Therefore, these components will continue to work on emissary executor without
 modifications.
 

content/en/docs/components/pipelines/legacy-v1/sdk/build-pipeline.md

@@ -221,11 +221,11 @@ when designing a pipeline.
     into a single file.
 
 [container-op]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/dsl.html#kfp.dsl.ContainerOp
-[component-spec]: https://www.kubeflow.org/docs/components/pipelines/reference/component-spec/
-[python-function-component]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/python-function-components/
-[component-dev]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/component-development/
-[python-function-component-data-passing]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/python-function-components/#understanding-how-data-is-passed-between-components
-[prebuilt-components]: https://www.kubeflow.org/docs/examples/shared-resources/
+[component-spec]: /docs/components/pipelines/reference/component-spec/
+[python-function-component]: /docs/components/pipelines/legacy-v1/sdk/python-function-components/
+[component-dev]: /docs/components/pipelines/legacy-v1/sdk/component-development/
+[python-function-component-data-passing]: /docs/components/pipelines/legacy-v1/sdk/python-function-components/#understanding-how-data-is-passed-between-components
+[prebuilt-components]: /docs/examples/shared-resources/
 
 
 ```python
@@ -319,7 +319,7 @@ $ head merged_data.csv
     The following example shows the updated `merge_csv` function.
 
 [web-download-component]: https://github.com/kubeflow/pipelines/blob/sdk/release-1.8/components/web/Download/component.yaml
-[python-function-components]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/python-function-components/
+[python-function-components]: /docs/components/pipelines/legacy-v1/sdk/python-function-components/
 [input-path]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/components.html?highlight=inputpath#kfp.components.InputPath
 [output-path]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/components.html?highlight=outputpath#kfp.components.OutputPath
 
@@ -415,14 +415,14 @@ kfp.compiler.Compiler().compile(
 2.  Upload and run your `pipeline.yaml` using the Kubeflow Pipelines user interface.
 See the guide to [getting started with the UI][quickstart].
 
-[quickstart]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/overview/quickstart
+[quickstart]: /docs/components/pipelines/legacy-v1/overview/quickstart
 
 #### Option 2: run the pipeline using Kubeflow Pipelines SDK client
 
 1.  Create an instance of the [`kfp.Client` class][kfp-client] following steps in [connecting to Kubeflow Pipelines using the SDK client][connect-api].
 
 [kfp-client]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/client.html#kfp.Client
-[connect-api]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/connect-api
+[connect-api]: /docs/components/pipelines/legacy-v1/sdk/connect-api
 
 
 ```python
@@ -450,8 +450,8 @@ client.create_run_from_pipeline_func(
     pipeline][k8s-resources] (Experimental).
 
 [conditional]: https://github.com/kubeflow/pipelines/blob/sdk/release-1.8/samples/tutorials/DSL%20-%20Control%20structures/DSL%20-%20Control%20structures.py
-[recursion]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/dsl-recursion/
-[k8s-resources]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/manipulate-resources/
+[recursion]: /docs/components/pipelines/legacy-v1/sdk/dsl-recursion/
+[k8s-resources]: /docs/components/pipelines/legacy-v1/sdk/manipulate-resources/
 
 
 <div class="notebook-links">

content/en/docs/components/pipelines/legacy-v1/sdk/component-development.md

@@ -395,7 +395,7 @@ The following examples demonstrate how to specify your component's interface.
     ```
 
 [dsl-types]: https://github.com/kubeflow/pipelines/blob/sdk/release-1.8/sdk/python/kfp/dsl/types.py
-[dsl-type-checking]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/static-type-checking/
+[dsl-type-checking]: /docs/components/pipelines/legacy-v1/sdk/static-type-checking/
 
 ### Specify your component's metadata
 

content/en/docs/components/pipelines/legacy-v1/sdk/manipulate-resources.md

@@ -277,4 +277,4 @@ For better understanding, please refer to the following samples:
   [Kubeflow Pipelines domain-specific language (DSL)](/docs/components/pipelines/legacy-v1/sdk/dsl-overview/),
   a set of Python libraries that you can use to specify ML pipelines.
 * For quick iteration, 
-  [build components and pipelines](/docs/components/pipelines/legacy-v1/sdk/build-component/).
+  [build components and pipelines](/docs/components/pipelines/legacy-v1/sdk/component-development//).

content/en/docs/components/pipelines/legacy-v1/sdk/python-function-components.ipynb

@@ -131,7 +131,7 @@
    "source": [
     "3.  Create and run your pipeline. [Learn more about creating and running pipelines][build-pipelines].\n",
     "\n",
-    "[build-pipelines]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/build-component/"
+    "[build-pipelines]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/component-development//"
    ]
   },
   {

content/en/docs/components/pipelines/legacy-v1/sdk/python-function-components.md

@@ -47,7 +47,7 @@ Python function-based components make it easier to iterate quickly by letting yo
 component code as a Python function and generating the [component specification][component-spec] for you.
 This document describes how to build Python function-based components and use them in your pipeline.
 
-[component-spec]: https://www.kubeflow.org/docs/components/pipelines/reference/component-spec/
+[component-spec]: /docs/components/pipelines/reference/component-spec/
 
 ## Before you begin
 
@@ -70,7 +70,7 @@ from kfp.components import create_component_from_func
 3. Create an instance of the [`kfp.Client` class][kfp-client] following steps in [connecting to Kubeflow Pipelines using the SDK client][connect-api].
 
 [kfp-client]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/client.html#kfp.Client
-[connect-api]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/connect-api
+[connect-api]: /docs/components/pipelines/legacy-v1/sdk/connect-api
 
 
 ```python
@@ -110,7 +110,7 @@ add_op = create_component_from_func(
 
 3.  Create and run your pipeline. [Learn more about creating and running pipelines][build-pipelines].
 
-[build-pipelines]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/build-component/
+[build-pipelines]: /docs/components/pipelines/legacy-v1/sdk/component-development//
 
 
 ```python
@@ -323,8 +323,8 @@ including component metadata and metrics.
 [dockerfile]: https://docs.docker.com/engine/reference/builder/
 [named-tuple-hint]: https://docs.python.org/3/library/typing.html#typing.NamedTuple
 [named-tuple]: https://docs.python.org/3/library/collections.html#collections.namedtuple
-[kfp-visualize]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/output-viewer/
-[kfp-metrics]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/pipelines-metrics/
+[kfp-visualize]: /docs/components/pipelines/legacy-v1/sdk/output-viewer/
+[kfp-metrics]: /docs/components/pipelines/legacy-v1/sdk/pipelines-metrics/
 [input-path]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/components.html#kfp.components.InputPath
 [output-path]: https://kubeflow-pipelines.readthedocs.io/en/stable/source/components.html#kfp.components.OutputPath
 
@@ -563,7 +563,7 @@ def calc_pipeline(
 
 5.  Compile and run your pipeline. [Learn more about compiling and running pipelines][build-pipelines].
 
-[build-pipelines]: https://www.kubeflow.org/docs/components/pipelines/legacy-v1/sdk/build-pipeline/#compile-and-run-your-pipeline
+[build-pipelines]: /docs/components/pipelines/legacy-v1/sdk/build-pipeline/#compile-and-run-your-pipeline
 
 
 ```python

content/en/docs/components/pipelines/legacy-v1/sdk/static-type-checking.md

@@ -10,7 +10,7 @@ static type checking for fast development iterations.
 
 ## Motivation
 
-A pipeline is a workflow consisting of [components](/docs/components/pipelines/legacy-v1/sdk/build-component#overview-of-pipelines-and-components) and each
+A pipeline is a workflow consisting of [components](/docs/components/pipelines/legacy-v1/sdk/component-development/#overview-of-pipelines-and-components) 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. 

content/en/docs/components/pipelines/legacy-v1/tutorials/api-pipelines.md

@@ -33,7 +33,7 @@ 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/build-component/#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/legacy-v1/sdk/component-development//#deploy-the-pipeline), but this time using the REST API.
 
 ```
 SVC=localhost:8888

content/en/docs/components/pipelines/legacy-v1/tutorials/build-pipeline.md

@@ -129,6 +129,6 @@ The following notebooks are available:
 * Learn the various ways to use the [Kubeflow Pipelines 
   SDK](/docs/components/pipelines/legacy-v1/sdk/sdk-overview/).
 * See how to 
-  [build your own pipeline components](/docs/components/pipelines/legacy-v1/sdk/build-component/).
+  [build your own pipeline components](/docs/components/pipelines/legacy-v1/sdk/component-development//).
 * Read more about 
   [building lightweight components](/docs/components/pipelines/legacy-v1/sdk/lightweight-python-components/).