What are the differences between them?
Is springcloud-stream one of the instantiations of springcloud-bus?
As I know, both of them concern about MQ.
Spring Cloud Bus is built on top of Spring Cloud Stream.
It's a Spring Cloud Stream application.
Related
I want to use Spring Cloud Stream for consuming and processing Apache Kafka queues and writing them to MongoDB. I saw that there is an option of using the library so that functions will be Reactive, or Imperative. In most Spring projects the imperative way is the default, but as for my understanding, in spring cloud stream the reactive paradigm is the default.
I wonder what is considered the most “stable” api e.g. what is recommended to use for enterprise?
Reactive API is stable and yes we provide support for it. In other words you can write functions using reactive API (e.g., Function<Flux, Flux>).
However, i want to be very clear that support for API does not mean support for the full stack of reactive capabilities since those actually depend on source and targets which are not reactive.
That said, with Kafka you can rely on native reactive support provided by Kafka itself and Spring Cloud Stream using Kafka Streams binder - https://docs.spring.io/spring-cloud-stream-binder-kafka/docs/3.1.5/reference/html/spring-cloud-stream-binder-kafka.html#_kafka_streams_binder
I'm developing an application that consumes messages from an exchange and it can publish to one of the multiple exchanges based on the input message transformation result.
I am trying to decide whether to go with sprrimg amqp or spring cloud stream.
What would be apt for this scenario?
Spring Cloud Stream (its Rabbit Binder) is a higher-level abstraction on top of Spring AMQP.
It is more opinionated and performs some configuration automatically.
According to Spring release notes, spring-integration-aws.1.1.0.M1 does not include DynamoDB MetaDataStore implementation. There is still ConcurrentMetadataStore class which is a key-value based store and based on implementation I suppose it maps streams with latest sequence number read. But it does not use any data store as to retrieve checkpoints.
I am using spring integration for kinesis consuming and need to implement checkpointing. I am wondering if I need to do it manually by connecting to DynamoDB and always update checkpoints or there is another way of doing it using spring framework?
P.S: I can't use Spring Cloud KinesisBinderConfiguration as I dynamically consume events from a list of configurable streams.
Thank you
If you are not talking about Spring Cloud Stream and the AWS Kinesis Binder implementation, then I don't see any blockers for you to upgrade your solution to the Spring Integration AWS 2.0 and go ahead with already provided DynamoDbMetaDataStore.
Or if that is so hard for you to move to the Spring Integration 5.0, then you simply can consider to copy/paste an implementation to your own class and inject it into the KinesisMessageDrivenChannelAdapter: https://github.com/spring-projects/spring-integration-aws/blob/master/src/main/java/org/springframework/integration/aws/metadata/DynamoDbMetaDataStore.java
Although it is really available in the 1.1.0.RELEASE - I don't see reason for your to stick with the 1.1.0.M1: https://spring.io/blog/2017/11/27/spring-integration-for-aws-1-1-ga-available
I'm looking for the azure alternative for the Data flow model of Data Source-processor-sink.
I want the three entities to be separate microservices. I want to use messaging as a link between these three.
Basically, Source app takes the data from another service and sends it to processor while processor app acts on it and sends relevant notification/alert to sink.
I'm aware I can use rabbitmq for the messaging but I need to know which one will be better in azure - service bus topics or eventhub? and how can I use them?
At the moment, there isn't a Spring Cloud Stream binder implementation for Azure Event Hubs.
Unless we have this, the out-of-the-box or the custom apps cannot be built as a messaging-microservice app, where Spring Cloud Stream provides the programming model and Spring Cloud Data Flow lets you orchestrate the individual microserivces in to a data pipeline (i.e., source-processor-sink) via the DSL/Drag-and-Drop GUI.
Microsoft was exploring the binder implementation in the past; possibly it would end up in Azure Spring Boot project. Feel free to drop an issue on their backlog.
Using Kafka as a messaging system in a microservice architecture what are the benefits of using spring-kafka vs. spring-cloud-stream + spring-cloud-starter-stream-kafka ?
The spring cloud stream framework supports more messaging systems and has therefore a more modular design. But what about the functionality ? Is there a gap between the functionality of spring-kafka and spring-cloud-stream + spring-cloud-starter-stream-kafka ?
Which API is better designed?
Looking forward to read about your opinions
Spring Cloud Stream with kafka binder rely on Spring-kafka. So the former has all functionalities supported by later, but the former will be more heavyweight. Below are some points help you make the choice:
If you might change kafka into another message middleware in the future, then Spring Cloud stream should be your choice since it hides implementation details of kafka.
If you want to integrate other message middle with kafka, then you should go for Spring Cloud stream, since its selling point is to make such integration easy.
If you want to enjoy the simplicity and not accept performance overhead, then choose spring-kafka
If you plan to migrate to public cloud service such as AWS Kensis, Azure EventHub, then use spring cloud stream which is part of spring cloud family.
Use Spring Cloud Stream when you are creating a system where one channel is used for input does some processing and sends it to one output channel. In other words it is more of an RPC system to replace say RESTful API calls.
If you plan to do an event sourcing system, use Spring-Kafka where you can publish and subscribe to the same stream. This is something that Spring Cloud Stream does not allow you do do easily as it disallows the following
public interface EventStream {
String STREAM = "event_stream";
#Output(EventStream.STREAM)
MessageChannel publisher();
#Input(EventStream.STREAM)
SubscribableChannel stream();
}
A few things that Spring Cloud Stream helps you avoid doing are:
setting up the serializers and deserializers