anchor.diff:  
   The sample data for this tutorial contains information about the requests that
   are received by various applications and services in a system. A system
  -administrator might use this type of information to track the the total
  -number of requests across all of the infrastructure. If the number of requests
  -increases or decreases unexpectedly, for example, this might be an indication
  -that there is a problem or that resources need to be redistributed. By using
  -the {xpack} {ml} features to model the behavior of this data, it is easier to
  -identify anomalies and take appropriate action.
  -
  -Download this sample data from: https://github.com/elastic/examples
  -//Download this data set by clicking here:
  -//See  https://download.elastic.co/demos/kibana/gettingstarted/shakespeare.json[shakespeare.json].
  +administrator might use this type of information to track the total number of
  +requests across all of the infrastructure. If the number of requests increases
  +or decreases unexpectedly, for example, this might be an indication that there
  +is a problem or that resources need to be redistributed. By using the {xpack}
  +{ml} features to model the behavior of this data, it is easier to identify
  +anomalies and take appropriate action.
  +
  +Download this sample data by clicking here:
  +https://download.elastic.co/demos/machine_learning/gettingstarted/server_metrics.tar.gz[server_metrics.tar.gz]
   
   Use the following commands to extract the files:
   
   [source,shell]
   ----------------------------------
  -tar xvf server_metrics.tar.gz
  +tar -zxvf server_metrics.tar.gz
   ----------------------------------
   
   Each document in the server-metrics data set has the following schema:
  
positive.code: whether or not it's _tokenized_, or broken up into separate words.
  
  The sample data includes an `upload_server-metrics.sh` script, which you can use
  to create the mappings and load the data set. Before you run it, however, you
  must edit the USERNAME and PASSWORD variables with your actual user ID and
  password.
  
  The script runs a command similar to the following example, which sets up a
  mapping for the data set:
  
negative.code: job is running.
  
  TIP: The `create_single_metic.sh` script creates a similar job and data feed by
  using the {ml} APIs. You can download that script by clicking
  here: https://download.elastic.co/demos/machine_learning/gettingstarted/create_single_metric.sh[create_single_metric.sh]
  For API reference information, see <<ml-apis>>.
  
  [[ml-gs-job1-manage]]
  === Managing Jobs
  