anchor.diff:  Once it has found the correct schema of the incoming message, it retrieves the reader schema and, by using Avro's schema resolution support, reads it into the reader definition (setting defaults and any missing properties).
   
   .Schema Reading Resolution Process
  -image::schema_reading.png[width=800,scaledwidth="75%",align="center"]
  +image::{github-raw}/docs/src/main/asciidoc/images/schema_reading.png[width=800,scaledwidth="75%",align="center"]
   
   NOTE: You should understand the difference between a writer schema (the application that wrote the message) and a reader schema (the receiving application).
   We suggest taking a moment to read https://avro.apache.org/docs/1.7.6/spec.html[the Avro terminology] and understand the process.
  
positive.code: This can be seen in the following figure, which shows a typical deployment for a set of interacting Spring Cloud Stream applications.
  
  .Spring Cloud Stream Publish-Subscribe
  image::SCSt-sensors.png[width=800,scaledwidth="75%",align="center"]
  
  Data reported by sensors to an HTTP endpoint is sent to a common destination named `raw-sensor-data`.
  From the destination, it is independently processed by a microservice application that computes time-windowed averages and by another microservice application that ingests the raw data into HDFS (Hadoop Distributed File System).
  
negative.code: The following image shows the general relationship of producers and consumers:
  
  .Producers and Consumers
  image::{github-raw}/docs/src/main/asciidoc/images/producers-consumers.png[width=800,scaledwidth="75%",align="center"]
  
  A producer is any component that sends messages to a channel.
  The channel can be bound to an external message broker with a `Binder` implementation for that broker.
  