Java Microservices interview questions for BottomLine

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How is the Kafka messaging system different from other messaging framework? • Kafka is a messaging framework developed by apache foundation, which is to create the create the messaging system along with can provide fault tolerant cluster along with the low latency system, to ensure end to end delivery. • Below are the bullet points: • Kafka is a messaging system, which has provided fault tolerant capability to prevent the message loss. • Design on public-subscribe model. • Kafka cab support both Java and Scala. • Kafka was originated at LinkedIn and later became an open sourced Apache project in 2011 • Work seamlessly with spark and other big data technology. • Support cluster mode operation • Kafka messaging system can be use for web service architecture or big data architecture. • Kafka ease to code and configure as compare to other messaging framework. • Kafka required other component such as the zookeeper to create a cluster and act as a coordination server • What are the key Features of Kafka? • Kafka provide a reliable delivery for messages from sender to receiver apart from that it has other key features as well. • Kafka is designed for achieving high throughput and fault tolerant messaging services. • Kafka provides build in patriation called as a Topic. • Also provide the feature of replication. • Kafka provides a queue, which can handle the high volume of data and eventually transfer the message from one sender to receiver. • Kafka also persisted the message in the disk along with has ability to replicate the messages across the cluster • Kafka work with zookeeper for coordination and synchronization with other services. • Kafka has good inbuilt support Apache Spark. • To utilize all this key feature, we need to configure the Kafka cluster properly along with the zookeeper configuration. • • Benefits of using Kafka than other messaging services like JMS, RabbitMQ doesn’t provide? • Now a days kafka is a key messaging framework, not because of its features even for reliable transmission of messages from sender to receiver, however, below are the key points which should consider. • Reliability − Kafka provides a reliable delivery from publisher to a subscriber with zero message loss.. • Scalability −Kafka achieve this ability by using clustering along with the zookeeper coordination server • Durability −By using distributed log, the messages can persist on disk. • Performance − Kafka provides high throughput and low latency across the publish and subscribe application. • Considering the above features Kafka is one of the best options to use in Bigdata Technologies to handle the large volume of messages for a smooth delivery. • What is the real-world use case of Kafka, which makes different from other messaging framework? • There is plethora of use case, where Kafka fit into the real work application, however I listed below are the real work use case which is frequently using. • Metrics: Use for monitoring operation data, which can use for analysis or doing statistical operation on gather the data from distributed system • Log Aggregation solution: can be used across an organization to collect logs from multiple services, which consume by consumer services to perform the analytical operation. • Stream Processing: Kafka’s strong durability is also very useful in the context of stream processing. • Asynchronous communication: In microservices, keeping this huge system synchronous is not desirable, because it can render the entire application unresponsive. Also, it can defeat the whole purpose of dividing into microservices in the first place. Hence, having Kafka at that time makes the whole data flow easier. Because it is distributed, highly fault-tolerant and it has constant monitoring of broker nodes through services like Zookeeper. So, it makes it efficient to work. • Chat bots: Chat bots is one of the popular use cases when we require reliable messaging services for a smooth delivery. • Multi-tenant solution. Multi-tenancy is enabled by configuring which topics can produce or consume data. There are also operations support for quotas • Above are the use case where predominately require a Kafka framework, apart from that there are other cases which depends upon the requirement and design. • #java #javaInterviewQuestions #javaInterviewQuestionsAndAnswers #Microservices #kafka

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