Update

Signed-off-by: Alyssa Goins <agoins@redhat.com>

Author: alyssacgoins

content/en/docs/components/pipelines/user-guides/core-functions/mlflow-plugin.md

@@ -1,12 +1,11 @@
 +++
-title = "Configure your KFP MLflow plugin"
+title = "MLflow Plugin for KFP"
 description = "Deploy MLflow on your cluster and configure the KFP MLflow plugin to use it."
-#TODO: update the weight here
-weight = 198
+weight = 204 
 +++
 
 ## Experiment Tracking in MLflow
-MLflow (link) is an open-source platform developed to manage the end-to-end Machine Learning lifecycle. 
+[MLflow](https://github.com/kubeflow/mlflow-integration) is an open-source platform developed to manage the end-to-end Machine Learning lifecycle. 
 The MLflow console is a powerful tool for organizing, querying and visualizing MLflow experiments and their corresponding runs.
 MLflow runs also store run parameters and artifacts. These values can be viewed in the MLflow console.
 
@@ -16,10 +15,11 @@ Once the plugin is enabled, users can specify an MLflow experiment, and new KFP
 Once the plugin is configured and enabled, each new KFP run registers and logs a corresponding MLflow run, within either a preconfigured experiment or a new or default experiment.
 In keeping with the MLflow console, pipeline input parameters and scalar artifacts are also automatically logged on MLflow runs. 
 As described directly above, these parameters and metrics are available through the MLflow console. 
-## Plugin Configuration
-Pre-requisites:
-#TODO: add link to MLflow operator install instructions
-- K8s cluster with the MLflow operator installed. You can find documentation for installing the MLflow operator here.
+
+
+## Configuring your KFP MLflow Plugin
+Pre-requisite: K8s cluster
+1. Following the official [MLflow Kubeflow Integration documentation](https://github.com/kubeflow/mlflow-integration) to configure your MLflow deployment.
 1. Install the MLflow operator (link) on your cluster.
 2. Configure your API config.json file with the following
 ```json
@@ -37,5 +37,4 @@ Pre-requisites:
     }
   }
 ```
-#TODO: add link below
 3. Refer to the following documentation for deploying KFP here (add link)