Link KIND deployment on main README

* Add link to KIND deployment doc
* Update the script that checks for broken links
* Fix broken links in usage steps and API README
* Update the resource requirements for KIND
* Add a deployment wait-loop for KIND
* Update the import assets documentation

Related machine-learning-exchange#266

Signed-off-by: Christian Kadner <ckadner@us.ibm.com>

README.md

@@ -31,12 +31,18 @@ Additionally it provides:
 ## 1. Deployment
 <img src="docs/images/mlx-architecture-4.png" height="40%" width="40%">
 
-For a simple up-and-running MLX with asset catalog only, we created a [Quickstart Guide](./quickstart) using [Docker Compose](https://docs.docker.com/compose/install/).
+For a simple up-and-running MLX with asset catalog only, we created a [Quickstart Guide](./quickstart)
+using [Docker Compose](https://docs.docker.com/compose/install/).
+
+For a slightly more resource-hungry local deployment that allows pipeline execution, we created the
+[MLX with Kubernetes in Docker (KIND)](./docs/install-mlx-on-kind.md) deployment option.
 
 For a full deployment, we use [Kubeflow Kfctl](https://github.com/kubeflow/kfctl) tooling. 
 
 * #### [MLX using Docker Compose (Asset Catalog Only)](./quickstart)
 
+* #### [MLX on Kubernetes in Docker (Fully Featured)](./docs/install-mlx-on-kind.md)
+
 * #### [MLX Deployment on Kubernetes or OpenShift](./docs/mlx-setup.md)
 
 * #### [MLX on an existing Kubeflow Cluster](./docs/install-mlx-on-kubeflow.md)

api/README.md

@@ -39,7 +39,7 @@ download it the first time it runs:
     # function swagger-codegen() { java -jar "swagger-codegen-cli-2.4.8.jar" "$@"; }
     # export -f swagger-codegen
 
-It is **not recommended** to install [`swagger-codegen@2`](https://formulae.brew.sh/formula-linux/swagger-codegen@2)
+It is **not recommended** to install [`swagger-codegen@2`](https://formulae.brew.sh/formula/swagger-codegen@2)
 via [Homebrew](https://docs.brew.sh/Installation) on macOS, since `brew install swagger-codegen@2`
 does not allow selecting the _"old"_ version `2.4.8`. Instead, the `generate_code.sh` script
 will automatically download the _"correct"_ version of the `swagger-codegen-cli.jar` file.

docs/import-assets.md

@@ -1,7 +1,19 @@
 # Import Data and AI Assets in MLX Catalog
 
-To import a catalog of assets first click on the three dots at the bottom of the left navigation bar and then click on `MLX Settings`. Then select `Choose Catalog` under the `Bulk Imports` sections. Find and select the [JSON file](/bootstrapper/catalog_upload.json) that describes your catalog and then your import will begin. A progress bar will appear to indicate upload progress.
+To _import a catalog of assets_ you must be logged in as an `admin`. To log in, append `/#` to the
+MLX URL in your browser's address bar:
 
-If an asset exists in your Catalog, but has not been imported then make sure that all the info provided in the Catalog (API Key, Asset URL, etc.) is correct. If it is correct, ensure that the asset you are trying to import does not share a name/ID with another asset.
+    http://mlx-ui-url/#
 
-![Catalog Import Screenshot](/docs/images/CatalogImport.png)
+Then expand the :gear: **Settings** at the bottom of the left-hand side navigation bar, and click on
+**MLX Settings**. At the top of the center screen, click on the **Choose Catalog** button under
+the **Bulk Imports** sections. 
+
+Find and select the [JSON file](/bootstrapper/catalog_upload.json) that describes your catalog 
+and the import should begin. A progress bar will indicate the upload progress.
+
+If an asset from your Catalog did not get imported, make sure that all the metadata provided in the
+Catalog upload file is correct (API Key, Asset URL, etc.). If it is correct, ensure that the 
+asset you are trying to import does not share a name/ID with another asset.
+
+![Catalog Import Screenshot](/docs/images/CatalogImport.png)

docs/install-mlx-on-kind.md

@@ -40,11 +40,11 @@ you could download the `kustomize` `v3.2.0` binary as described
 
 Increase the default resources for Docker:
 
-- CPUs: 4 Cores
-- Memory: 8 GB RAM
+- CPUs: 8 Cores
+- Memory: 16 GB RAM
 - Disk: 32+ GB
 
-**Note**: We found that on older laptops, like a 2016 15 in MacBook Pro (2.7 GHz i7, 16 GB) the MLX
+**Note**: We found that on older laptops, like a 2016 MacBook Pro (2.7 GHz i7, 16 GB RAM) the MLX
 deployment on KIND may require to give all available resources to the Docker daemon in order to be
 able to deploy the manifests and run basic pipelines. Even then, trying to run notebooks or deploying 
 a model, will cause the laptop to get very slow with fans running full throttle. It may even cause
@@ -66,19 +66,37 @@ kubectl get pods --all-namespaces
 git clone https://github.com/IBM/manifests -b v1.4.0-mlx
 cd manifests
 
-# run the below command two times if the CRDs take too long to provision.
+# run the below command two times if the CRDs take too long to provision
 while ! kustomize build mlx-single-kind | \
   kubectl apply -f -; do echo "Retrying to apply resources"; sleep 10; done
 
+# wait while the MLX deployment is starting up, may take 10 to 20 minutes
+while $( kubectl get pods --all-namespaces | grep -q -v "STATUS\|Running" ); do \
+  echo "Hold tight, still waiting for $( kubectl get pods --all-namespaces | grep -v "STATUS\|Running" | wc -l ) pods ..."; \
+  sleep 10; \
+done
+
 # check pod status
 kubectl get pods --all-namespaces
 
 # make the MLX UI available to your local browser on http://localhost:3000/
-kubectl port-forward -n istio-system svc/istio-ingressgateway 3000:80
+kubectl port-forward -n istio-system svc/istio-ingressgateway 3000:80 &
 ```
 
-Now paste the URL http://localhost:3000/ into your browser and proceed to
-[import the MLX catalog](import-assets.md).
+Now paste the URL http://localhost:3000/# into your browser and proceed to
+[import the MLX catalog](import-assets.md), or, upload the assets from the
+[default MLX asset catalog](https://github.com/machine-learning-exchange/katalog)
+using the MLX API directly with `curl`:
+
+```Bash
+UPLOAD_API="http://localhost:3000/apis/v1alpha1/catalog/upload_from_url"
+CATALOG_URL="https://raw.githubusercontent.com/machine-learning-exchange/mlx/main/bootstrapper/catalog_upload.json"
+
+curl -X POST \
+    -H "Content-Type: multipart/form-data" \
+    -F url="${CATALOG_URL}" \
+    -s "${UPLOAD_API}" | grep -iE "total_|error"
+```
 
 Delete the `mlx` cluster when it is no longer needed:
 
@@ -87,7 +105,7 @@ kind delete cluster --name mlx
 ```
 
 
-## Install Kubeflow Pipelines (for reference, optional)
+## Install Kubeflow Pipelines (for Reference only, Optional)
 
 ```Bash
 kind create cluster --name kfp

docs/usage-steps.md

@@ -12,7 +12,7 @@
 
 3. [Models](../models/README.md)
     - [Create Model Metadata](../models/README.md#Create-Model-Metadata)
-    - [Register Model](./models/README.md#Register-Model)
+    - [Register Model](../models/README.md#Register-Model)
     - [Use Models in Pipelines](../models/README.md#Use-Models-in-Pipelines)
     - [Model Metadata Template](../models/template.yaml)
 

tools/python/verify_doc_links.py

@@ -75,7 +75,8 @@ def get_links_from_md_file(md_file_path: str) -> [(int, str, str)]: # -> [(line,
 
         # find plain http(s)-style links
         for url in re.findall(r"[\n\r\s\"'](https?://[^\s]+)[\n\r\s\"']", line_text):
-            if not any(s in url for s in ["localhost", "...", "lorem", "ipsum", "/path/to/", "address", "port"]):
+            if not any(s in url for s in
+                       ["localhost", "...", "lorem", "ipsum", "/path/to/", "address", "port", "${OS}"]):
                 try:
                     parse_url(url)
                     line_text_url.append((line_number + 1, "", url))