anchor.diff:  
   |`plugin.name`
   |`decoderbufs`
  -|The name of the Postgres link:#output-plugin[logical decoding plugin] installed on the server.
  +|The name of the Postgres link:#output-plugin[logical decoding plugin] installed on the server. Supported values are either `decoderbufs` or `wal2json`.
   
   |`slot.name`
   |`debezium`
  
positive.code: 
  . install the link:#output-plugin[logical decoding plugin]
  . configure the link:#server-configuration[PostgreSQL server] to support logical replication
  . create a link:#example-configuration[configuration file for the PostgreSQL Connector] and use the http://docs.confluent.io/3.0.0/connect/userguide.html#rest-interface[Kafka Connect REST API] to add that connector to your Kafka Connect cluster.
  
  When the connector starts, it will grab a consistent snapshot of the databases in your PostgreSQL server and start streaming changes, producing events for every inserted, updated, and deleted row. You can also choose to produce events for a subset of the schemas and tables. Optionally ignore, mask, or truncate columns that are sensitive, too large, or not needed.
  
  
negative.code: 
  Debezium's PostgreSQL connector contains two different parts which work together in order to be able to read and process server changes:
  
  * a logical decoding output plugin which has to be installed and configured in the PostgreSQL server, one of
  ** https://github.com/debezium/postgres-decoderbufs[Protobuf based]
  ** https://github.com/eulerto/wal2json[wal2json]
  * Java code which reads the changes produced by the plugin in Protobuf format, using PostgreSQL's https://www.postgresql.org/docs/9.6/static/logicaldecoding-walsender.html[_streaming replication protocol_], via the PostgreSQL https://github.com/pgjdbc/pgjdbc[_JDBC driver_]
  
  The connector then produces a _change event_ for every row-level insert, update, and delete operation that was received, recording all the change events for each table in a separate Kafka topic. Your client applications read the Kafka topics that correspond to the database tables they're interested in following, and react to every row-level event it sees in those topics.
  