Amazon Managed Streaming Apache Kafka (Amazon MSK), is a fully managed service that makes it easy to develop and run applications that use Apache Kafkato to concoct streaming data. Amazon MSK allows us to use native Apache Kafka APIs for populating data lakes, stream changes between databases, and power machine learning and analytics applications.
Apache Kafka clusters can be stimulating to set-up, scale and maintain in production. If we want to run Kafka ourselves, we need to provision servers, configure Apache Kafka manually and restore them when they fail. We also need to architect the cluster for high availability. We also need to ensure data is safe and secure, set up monitoring and alarms, and plan to scale events to support changes in load. Amazon MSK allows us to easily create and manage production applications on Kafka, without needing to know anything about Apache Kafka infrastructure administration. This means that we spend less time maintaining infrastructure and more on building applications.
What is Apache Kafka?
Apache Kafka is an open-source classified data store that can be used to process and ingest streaming data in real time. Streaming data refers to information that is constantly produced by thousands or more data sources. These data records are often transmitted together. A streaming platform must manage this continuous influx of information and prepare the data sequentially.
Kafka serves three main purposes for its users:
Publish and subscribe to records streams
Alao effectively saves streams of records in the same order they were produced
Real-time processing of records
Kafka was originally used to create real-time streaming data pipes and applications that conform to these data streams. It combines messaging, storage and stream processing to store and analyze historical and current data.
Source: Confluent Kafka’s architecture
Kafka helps to separate the models by printing records to different topics. Each topic has a partitioned Log, which is a structured log that stores all records in order and adds new records in real-time. These partitions can be distributed and replicated across multiple servers, allowing for high scalability and fault tolerance as well as parallelism. Each customer is assigned a topic partition, which acknowledges multiple subscribers while maintaining the order of data. Kafka combines both messaging models by connecting them. Kafka can also be used to create and replicate data to disk, making it scalable and fault-tolerant. Kafka stores data on a disk by default until it runs out of space. However, the user can set a retention limit. There are four APIs available for Kafka:
Producer API: It used the producer API to publish a stream to a Kafka topic.
Consumer API: Used to subscribe to subjects and process their records.
Streams API: This API allows applications to behave like stream processors. They take in an input stream of topic(s), and transform it into an output stream that goes into a different topic(s).
Connector API: Allows users to seamlessly automate the addition or modification of an application or data system to their Kafka topics.
We can create highly available Apache Kafka clusters by using a few clicks in theAmazon MSK Console. The configuration and settings are based on Apache Kafka’s deployment best practices. Amazon MSK automatically reserves and runs Kafka clusters. Amazon MSK also continuously monitors cluster health and automatically replaces unhealthy nodes without any downtime to the application. Amazon MSK encrypts data at rest to secure Apache Kafka cluster. Let’s now talk about the benefits of Amazon MSK.
Amazon Managed Streaming Benefits for Apache Kafka
Here are some benefits we should be aware of.
Fully compatible
Amazon MSK manages Apache Kafka for us. It is easy to transfer and run existing Kafka applications to AWS without any modifications to the application code. By utilizing Amazon MSK, we sustain open-source adaptability and can proceed to use simple custom and community-built devices such as Apache Flink,MirrorMaker,andPrometheus.
Fully managed
Amazon MSK allows us to focus on building streaming applications and not worry about the operational burden of maintaining the Apache Kafka environment. The Amazon MSK also manages the provisioning, configuration, and maintenance of Apache Kafka clusters, and Apache ZooKeeper nodes. Amazon MSK also provides key Apache Kafka performance metrics via the AWS console.
Elastic stream processing
Apache Flink is an open-source stream processing system that allows stateful estimations of streaming data. We can create fully managed Apache Flink applications written in Java, SQL or Scala that elastically balance to handle data streams within Amazon MSK.
Highly available
Amazon MSK is an Apache Kafka batch that allows multi-AZ replication within an AWS Region. Amazon MSK monitors cluster health and will automatically replace any element that fails.
Highly secure
Amazon MSK offers various levels of security for Apache Kafka clusters. This includes VPC network isolation and encryption at rest. AWS IAM allows for control-plane API authorization. TLS based certificate authentication. SASL/SCRAM authentication is secured by AWS Secrets manager. TLS encryption in transit is also available. ACLs are Apache Kafka Access Control Lists are maintained (ACLs).
How does it work?
Apache Kafka is an open-source streaming data repository. It separates applications that provide streaming data (producers), from those that consume streaming data (consumers). Companie