Spelling

docs/.wordlist.txt

@@ -1,26 +1,36 @@
+addons
+API
+APIs
 CharmHub
 CLI
+DEX
 dropdown
 Diátaxis
+EBS
 EKS
 favicon
 filesystem
 Grafana
 https
+IAM
 installable
+JSON
 Juju
 Juju’s
 Kubernetes
 Kubeflow
+lifecycle
 Makefile
-MicroK8s
+MicroK
 MinIO
+MLflow
 MLOps
 MyST
 namespace
 namespaces
 NodePort
 Observability
+OIDC
 OLM
 Permalink
 ReadMe

docs/how-to/create-ck8s-aws.rst

@@ -28,7 +28,7 @@ To install some helpful tools, run this command:
 This installs the following:
 
 * ``juju``: Needed to deploy and manage the CK8s cluster.
-* ``juju-wait``: CLI tool used for waiting during juju deployments.
+* ``juju-wait``: CLI tool used for waiting during Juju deployments.
 * ``kubectl``: Kubernetes client used to communicate with a Kubernetes cluster.
 * ``jq``: A lightweight and versatile command-line tool for parsing and manipulating JSON data.
 

docs/how-to/deploy-mlflow-kubeflow-eks.rst

@@ -20,7 +20,7 @@ We assume the following:
 Deploy EKS cluster
 -------------------
 
-See our `EKS creation guide <https://charmed-kubeflow.io/docs/create-eks-cluster-for-mlops>`_ for a complete guide on how to do this. **Do not forget** to edit the ``instanceType`` field under ``managedNodeGroups[0].instanceType`` from ``t2.2xlarge`` to ``t3.2xlarge``, as instructed in the guide, since worker nodes of type ``t3.2xlarge`` are required for deploying both MLFlow and Kubeflow.
+See our `EKS creation guide <https://charmed-kubeflow.io/docs/create-eks-cluster-for-mlops>`_ for a complete guide on how to do this. **Do not forget** to edit the ``instanceType`` field under ``managedNodeGroups[0].instanceType`` from ``t2.2xlarge`` to ``t3.2xlarge``, as instructed in the guide, since worker nodes of type ``t3.2xlarge`` are required for deploying both MLflow and Kubeflow.
 
 Setup Juju
 ----------

docs/how-to/integrate-cos.rst

@@ -6,7 +6,7 @@ This guide shows how to integrate MLflow with the Canonical Observability Stack
 Prerequisites
 -------------
 
-This guide asssumes:
+This guide assumes:
 
 #. You have deployed the COS stack in the ``cos`` model. For steps on how to do this, see the `MicroK8s tutorial <https://charmhub.io/topics/canonical-observability-stack/tutorials/install-microk8s>`_.
 #. You have deployed the MLflow bundle in the ``kubeflow`` model. For steps on how to do this, see :doc:`../tutorial/mlflow`.

docs/index.rst

@@ -11,7 +11,7 @@ It provides tools for tracking experiments, packaging code into reproducible run
 
 It addresses a number of challenges facing machine learning teams: collaboration, reproducibility, maintenance, organisation and scaling.
 
-It's ideal for data scientists, ML engineers, hobbyists and teams looking to optimize their ML workflows with charms.
+It's ideal for data scientists, ML engineers, hobbyists and teams looking to optimise their ML workflows with charms.
 
 ---------
 

docs/tutorial/mlflow-kubeflow.rst

@@ -117,7 +117,7 @@ Integrate MLflow with Notebook
 
 In this section, we're going to create a notebook server in Kubeflow and connect it to MLflow. This will allow our notebook logic to talk to MLflow in the background. Let's get started.
 
-First, to be able to use MLflow credentials in your Kubeflow notebook, visit the dashboard at http://10.64.140.43.nip.io/ and fill the username and password which you configured in the previous section e.g. ``[email protected]`` and ``user123``.
+First, to be able to use MLflow credentials in your Kubeflow notebook, visit the dashboard at ``http://10.64.140.43.nip.io/`` and fill the username and password which you configured in the previous section e.g. ``[email protected]`` and ``user123``.
 
 Click on start setup to setup the Kubeflow user for the first time.
 
@@ -129,7 +129,7 @@ Now a Kubernetes namespace was created for your user. To use MLflow with this us
 
    microk8s kubectl label ns user123 user.kubeflow.org/enabled="true"
 
-You will get the following output: `namespace/user123 labeled`.
+You will get the following output: ``namespace/user123 labeled``.
 
 For more info on the label command, check `Kubernetes labels <https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/>`_. For more info on Kubernetes namespaces for users, see the `upstream docs on Multi-user isolation <https://www.kubeflow.org/docs/components/multi-tenancy/getting-started/>`_.
 
@@ -146,7 +146,7 @@ Now, in order to allow our notebook server access to MLflow, we need to enable s
 2. Allow access to MinIO.
 3. Allow access to MLflow.
 
-.. note:: Remember we related Kubeflow to MLflow earlier using the resource dispatcher? This is why we're seeing the Minio and MLflow options in the dropdown!
+.. note:: Remember we related Kubeflow to MLflow earlier using the resource dispatcher? This is why we're seeing the MinIO and MLflow options in the dropdown!
 
 Great, that's all the configuration for the notebook server done. Hit the Launch button to launch the notebook server. Be patient, the notebook server will take a little while to initialise.
 

docs/tutorial/mlflow.rst

@@ -42,7 +42,7 @@ It is also useful to make sure the user has the proper access and ownership of a
 
    sudo chown -f -R $USER ~/.kube
 
-Enable the following Microk8s add-ons to configure your Kubernetes cluster with extra services needed to run Charmed Kubeflow.
+Enable the following Microk8s addons to configure your Kubernetes cluster with extra services needed to run Charmed Kubeflow.
 
 .. code-block:: bash