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canonical · Sep 11, 2023 · c2f35b5 · c2f35b5
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diff --git a/docs/how-to/create-ck8s-aws.rst b/docs/how-to/create-ck8s-aws.rst
@@ -57,11 +57,11 @@ Bootstrap a Juju controller that will be responsible for deploying cluster appli
 Deploy Charmed Kubernetes 1.24
 ------------------------------
 
-Clone the `Charmed Kubernetes bundle repository <https://github.com/charmed-kubernetes/bundle.git>`_, and update CPU, disk, and memory constraints to meet Kubeflow requirements.
+Clone the `Charmed Kubernetes bundle repository <https://github.com/charmed-kubernetes/bundle>`_, and update CPU, disk, and memory constraints to meet Kubeflow requirements.
 
 .. code-block:: bash
 
-   git clone https://github.com/charmed-kubernetes/bundle.git
+   git clone https://github.com/charmed-kubernetes/bundle
    sed -i '/^ *charm: kubernetes-worker/,/^ *[^:]*:/s/constraints: cores=2 mem=8G root-disk=16G/constraints: cores=8 mem=32G root-disk=200G/' ./bundle/releases/1.24/bundle.yaml
 
 Deploy the Charmed Kubernetes bundle on AWS with the storage overlay. This overlay enables you to create Kubernetes volumes backed by AWS EBS.

diff --git a/docs/how-to/deploy-ck8s-aws.rst b/docs/how-to/deploy-ck8s-aws.rst
@@ -12,7 +12,7 @@ This guide shows how to connect Juju to an existing `Charmed Kubernetes <https:/
 Prerequisites
 -------------
 
-We assume that you have access to a CK8s cluster using ``kubectl``. If you don't have a cluster set up, you can follow this guide: `Create CK8s on AWS <../create-ck8s-aws>`_.
+We assume that you have access to a CK8s cluster using ``kubectl``. If you don't have a cluster set up, you can follow this guide: :doc:`Create CK8s on AWS <create-ck8s-aws>`.
 
 Install Juju
 ------------

diff --git a/docs/how-to/integrate-ml-ckf-ck8s.rst b/docs/how-to/integrate-ml-ckf-ck8s.rst
@@ -13,9 +13,9 @@ Prerequisites
 --------------
 We assume that:
 
-* You have access to a Charmed Kubernetes cluster using ``kubectl``. If you don't have a cluster set up, you can follow the `creation guide <../create-ck8s-aws>`_ to deploy one on AWS.
+* You have access to a Charmed Kubernetes cluster using ``kubectl``. If you don't have a cluster set up, you can follow the :doc:`creation guide <create-ck8s-aws>` to deploy one on AWS.
 * You have deployed the Charmed Kubeflow bundle. If you don't have it, here is `a guide <https://discourse.charmhub.io/t/deploying-charmed-kubeflow-to-charmed-kubernetes-on-aws/11667>`_ on how to do it.
-* You have deployed the Charmed MLflow bundle. To see how, follow our `deployment guide <../deploy-ck8s-aws>`_.
+* You have deployed the Charmed MLflow bundle. To see how, follow our :doc:`deployment guide <deploy-ck8s-aws>`.
 
 Deploy resource dispatcher
 --------------------------

diff --git a/docs/tutorial/mlflow-kubeflow.rst b/docs/tutorial/mlflow-kubeflow.rst
@@ -88,7 +88,7 @@ So, how do you know when all the charms are ready, then? You can do this using t
 
    juju status
 
-Review the output for yourself. You should see some summary information, a list of Apps and associated information, and another list of Units and their associated information. Don’t worry too much about what this all means for now. If you’re interested in learning more about this command and its output, see the `Juju Status command <https://juju.is/docs/olm/juju-status>`_.
+Review the output for yourself. You should see some summary information, a list of Apps and associated information, and another list of Units and their associated information. Don’t worry too much about what this all means for now. If you’re interested in learning more about this command and its output, see the `Juju Status command <https://juju.is/docs/juju/juju-status>`_.
 
 The main thing we’re interested in at this stage is the statuses of all the applications and units running through Juju. We want all the statuses to eventually become ``active``, indicating that the bundle is ready. Run the following command to keep a watch on the components which are not active yet:
 
@@ -110,7 +110,7 @@ Don’t be surprised if some of the components’ statuses change to ``blocked``
 
    This is a known issue, see `tensorboard-controller GitHub issue <https://github.com/canonical/bundle-kubeflow/issues/488>`_ for more info.
 
-Be patient, it can take up to an hour for all those charms to download and initialise. In the meantime, why not try our `Juju tutorial <https://juju.is/docs/olm/get-started-with-juju>`_?
+Be patient, it can take up to an hour for all those charms to download and initialise. In the meantime, why not try our `Juju tutorial <https://juju.is/docs/juju/get-started-with-juju>`_?
 
 Integrate MLflow with Notebook
 ------------------------------