An open source tool for handling incoming streams of data, Kafka, was always been a little complex to install and managed until now. With the launch of Amazon’s Managed Streaming for Kafka (MSK), all this has become easier.
What is Kafka?
Kafka is a popular open-source project from Apache that helps companies to analyze and process large streams of data used in applications, such as infrastructure monitoring tools or messaging apps.
Kafka supports two broad classes of applications:
- Building real-time streaming data pipelines to help fetch data between systems or applications in a reliable manner.
- Building real-time streaming applications that help transform or response to the streams of data.
Capabilities of Kafka Streaming Platform: Kafka streaming platform can help in the following ways:
- Store huge streams of records in a fault-tolerant durable environment.
- Process huge volume of data streams of records in order of their occurrences.
- Publish and subscribe to streams of records just as a message queue or enterprise messaging system.
How Amazon Cloud Services incorporates Kafka?
Amazon Managed streaming for Kafka (MSK) uses Apache Kafka APIs to populate data lakes, stream changes to and from the database, and empower machine learning and analytics applications. The Apache Kafka clusters are complex and challenging in nature while setting up, scale, and manage in production.
When the users run these cluster on their infrastructure, they first need to provision servers, configure Apache Kafka manually, replace servers if they fail, orchestrate server patches according to the requirements. Later, the users can upgrade and architect the clusters for high-availability to ensure durable data storage. Setting up monitoring and alarm services through Amazon MSK help users to carefully plan out the scaling events of Kafka clusters to support load change and data integrity.
It is very easy to build and run production applications on Apache Kafka using Amazon Managed Streaming for Kafka (MSK) without requiring Apache Kafka infrastructure management expertise. This eventually reduces the infrastructure management time and builds more application in the same time-frame, increasing productivity.
Now, you can easily create highly-available Apache Kafka cluster just with a few clicks using the Amazon MSK console. The settings and configurations help to deploy the best practices of Kafka cluster. The Amazon MSK provisions and run Apache Kafka clusters automatically. Using Amazon MSK user can monitor the cluster health and replace the detrimental cluster nodes with no downtime to the user’s application. It can even encrypt data at rest so as to ensure data security.
Advantages of Amazon MSK:
Some of the major benefits delivered by Amazon MSK are:
- Highly Secure: Using multiple levels of security, Amazon MSK protects the Kafka clusters along with network isolation using Amazon VPC, AWS IAM for control-plane API authorization, and encryption at rest.
- Highly Available: Amazon MSK helps create Kafka cluster and offers multi-AZ replication in an AWS Region. It helps in monitoring cluster health and replaces if any cluster fails.
- Fully Compatible: Amazon MSK helps run Kafka clusters and migrate all the existing application on AWS cloud with ease. The application code remains the same and does not change while running. Amazon MSK helps maintain the open-source compatibility and continue to use familiar custom and community-built tools which offers replication of streams.
- Fully Managed: Without worrying about managing the Kafka environment, Amazon MSK help users focus on creating the streaming applications. It also helps in provisioning, configuring, and maintaining the Kafka clusters and nodes for data streaming.
Bottom-Line: Businesses that deals in e-commerce, web and application hosting, data storage, game-player activities, social networking, information gathering, financial trading, geospatial services, telemetry of connected devices in data centers, and many others include a huge volume of data streaming services. This continuous stream of data produces a huge volume of log generated files that need to be recorded, traced, collected and processed to deliver accurate customer support.
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