Sync docs from master to gh-pages

This commit is contained in:
buildmaster
2019-03-25 12:48:15 +00:00
parent 031085da6a
commit 0499ea26c8
4 changed files with 18 additions and 18 deletions

View File

@@ -155,12 +155,12 @@ $(addBlockSwitches);
<p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p> <p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p>
</div> </div>
<div class="paragraph"> <div class="paragraph">
<p>With Spring Cloud Stream, developers can: <p>With Spring Cloud Stream, developers can:<br>
* Build, test, iterate, and deploy data-centric applications in isolation. * Build, test, iterate, and deploy data-centric applications in isolation.<br>
* Apply modern microservices architecture patterns, including composition through messaging. * Apply modern microservices architecture patterns, including composition through messaging.<br>
* Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity. * Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity.<br>
* Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis). * Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis).<br>
* Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs. * Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs.<br>
* Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p> * Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p>
</div> </div>
</div> </div>

Binary file not shown.

Before

Width:  |  Height:  |  Size: 80 KiB

After

Width:  |  Height:  |  Size: 51 KiB

View File

@@ -114,12 +114,12 @@ $(addBlockSwitches);
<p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p> <p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p>
</div> </div>
<div class="paragraph"> <div class="paragraph">
<p>With Spring Cloud Stream, developers can: <p>With Spring Cloud Stream, developers can:<br>
* Build, test, iterate, and deploy data-centric applications in isolation. * Build, test, iterate, and deploy data-centric applications in isolation.<br>
* Apply modern microservices architecture patterns, including composition through messaging. * Apply modern microservices architecture patterns, including composition through messaging.<br>
* Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity. * Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity.<br>
* Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis). * Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis).<br>
* Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs. * Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs.<br>
* Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p> * Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p>
</div> </div>
</div> </div>

View File

@@ -303,12 +303,12 @@ $(addBlockSwitches);
<p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p> <p>To extend this to Data Integration workloads, Spring Integration and Spring Boot were put together into a new project. Spring Cloud Stream was born.</p>
</div> </div>
<div class="paragraph"> <div class="paragraph">
<p>With Spring Cloud Stream, developers can: <p>With Spring Cloud Stream, developers can:<br>
* Build, test, iterate, and deploy data-centric applications in isolation. * Build, test, iterate, and deploy data-centric applications in isolation.<br>
* Apply modern microservices architecture patterns, including composition through messaging. * Apply modern microservices architecture patterns, including composition through messaging.<br>
* Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity. * Decouple application responsibilities with event-centric thinking. An event can represent something that has happened in time, to which the downstream consumer applications can react without knowing where it originated or the producer&#8217;s identity.<br>
* Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis). * Port the business logic onto message brokers (such as RabbitMQ, Apache Kafka, Amazon Kinesis).<br>
* Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs. * Interoperate between channel-based and non-channel-based application binding scenarios to support stateless and stateful computations by using Project Reactor&#8217;s Flux and Kafka Streams APIs.<br>
* Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p> * Rely on the framework&#8217;s automatic content-type support for common use-cases. Extending to different data conversion types is possible.</p>
</div> </div>
</div> </div>