anchor.diff:  be unique in your cluster. You can also optionally provide a description of the
   job.
   
  -. Click **Create Job**.
  +. Click **Create Job**. +
  ++
  +--
  +[role="screenshot"]
   image::images/ml-gs-job1.jpg["A graph of the total number of requests over time"]
  +--
   
   As the job is created, the graph is updated to give a visual representation of
   the progress of {ml} as the data is processed. This view is only available whilst the
  
positive.code: now process the remaining data by restarting the data feed:
  
  . In the **Machine Learning** / **Job Management** tab, click the following
  button to start the data feed:
  image::images/ml-start-feed.jpg["Start data feed"]
  
  . Choose a start time and end time. For example,
  click **Continue from 2017-04-01 23:59:00** and select **2017-04-30** as the
  search end time. Then click **Start**. The date picker defaults to the latest
  timestamp of processed data. Be careful not to leave any gaps in the analysis,
  otherwise you might miss anomalies.
  image::images/ml-gs-job1-datafeed.jpg["Restarting a data feed"]
  
  The data feed state changes to `started`, the job state changes to `opened`,
  and the number of processed records increases as the new data is analyzed. The
  latest timestamp information also increases. For example:
  image::images/ml-gs-job1-manage2.jpg["Job opened and data feed started"]
  
  TIP: If your data is being loaded continuously, you can continue running the job
  in real time. For this, start your data feed and select **No end time**.
  
  If you want to stop the data feed at this point, you can click the following
  button:
  image::images/ml-stop-feed.jpg["Stop data feed"]
  
  Now that you have processed all the data, let's start exploring the job results.
  
  
negative.code: . Open {kib} in your web browser and log in. If you are running {kib} locally,
  go to `http://localhost:5601/`.
  
  . Click **Machine Learning** in the side navigation: +
  +
  --
  [role="screenshot"]
  image::images/ml-kibana.jpg[Job Management]
  --
  
  You can choose to create single metric, multi-metric, or advanced jobs in
  {kib}. In this tutorial, the goal is to detect anomalies in the total requests
  