anchor.diff:  ./mvnw clean install
   ----
   +
  -. Start the Data Flow Server application:
  +. Start the Local Data Flow Server application:
   +
   ----
  -export DEPLOYER_LOCAL_OUT_OF_PROCESS=false
  -
  -java -jar spring-cloud-dataflow-server-local/target/spring-cloud-dataflow-server-local-1.0.0.BUILD-SNAPSHOT.jar
  +java -jar spring-cloud-dataflow-server-local/target/spring-cloud-dataflow-server-local-<version>.jar
   ----
   +
   . Start the shell
   +
   ----
  -$ java -jar spring-cloud-dataflow-shell/target/spring-cloud-dataflow-shell-1.0.0.BUILD-SNAPSHOT.jar
  +$ java -jar spring-cloud-dataflow-shell/target/spring-cloud-dataflow-shell-<version>.jar
   ----
   
   === Creating the `time | log` stream:
  
positive.code: == Spring Cloud Data Flow Server - Local
  
  The SPI implementation for deploying https://github.com/spring-cloud/spring-cloud-stream[Spring Cloud Stream] modules locally, either within the same JVM as the Data Flow Server or by spawning a new JVM process on the local machine. Spawning a new JVM process is the default. To run modules within the existing JVM process set the environment variable `DEPLOYER_LOCAL_OUT_OF_PROCESS=false` or the corresponding property: `deployer.local.out-of-process`.
  
  == Getting Started
  
  
negative.code: 
  === Start the Data Flow Server and Shell
  
  . Start Kafka locally (e.g. `kafka-server-start.sh /usr/local/etc/kafka/server.properties`)
  . Start Redis locally via `redis-server`
  . Build from the spring-cloud-dataflow root directory:
  +
  