AWS MSK (Amazon Managed Streaming for Apache Kafka) is a fully managed service that enables you to build and run applications based on Apache Kafka without the need to manage the underlying infrastructure. Kafka is an open-source distributed streaming platform that allows you to build real-time streaming applications and data pipelines.
Read this blog on AWS MSK to learn about its use cases, components, and data sources in detail.
With AWS MSK, you can focus on developing your applications and leveraging the benefits of Kafka, while offloading the operational overhead to AWS.
Here are some key points about AWS MSK:
Managed Service: AWS MSK handles the infrastructure and Kafka cluster management tasks such as provisioning, scaling, and patching. This allows you to avoid the operational complexities of deploying and managing your own Kafka cluster.
High Availability: AWS MSK provides built-in fault tolerance by deploying Kafka brokers across multiple Availability Zones (AZs) within a region. This ensures that your cluster remains available even if a single AZ experiences an issue.
Scalability: You can easily scale your Kafka cluster in AWS MSK by adding or removing brokers to meet your workload requirements. This elasticity enables you to handle high volumes of streaming data and adapt to changing demands.
Integration with AWS Ecosystem: AWS MSK seamlessly integrates with other AWS services, such as Amazon S3, Amazon Lambda, Amazon CloudWatch, Amazon CloudFormation, and more. This enables you to build comprehensive data processing and analytics pipelines using the broader AWS ecosystem.
Security and Compliance: AWS MSK provides several security features, including encryption at rest and in transit, integration with AWS Identity and Access Management (IAM) for fine-grained access control, and support for VPC networking. It also helps you meet regulatory compliance requirements.
Monitoring and Operations: AWS MSK integrates with Amazon CloudWatch to provide real-time monitoring and metrics for your Kafka cluster. You can monitor important metrics, set up alarms, and collect logs for troubleshooting and performance optimization.
Open Source Compatibility: AWS MSK is compatible with Apache Kafka, which means you can use existing Kafka applications, libraries, and tools seamlessly. This compatibility ensures that you can leverage the rich Kafka ecosystem and community resources.
By using AWS MSK, you can simplify the deployment and management of your Kafka infrastructure, reduce operational overhead, and focus on building data-intensive streaming applications that can process, transform, and analyze real-time data at scale.
Important Components of AWS MSK Cluster
There are few important terminologies that we need to know about MSK cluster such as the source that generates the data streams, the target that receives the data streams, and the topic that acts as an interface between the source and target. Below are some of the improtant components:
PRODUCER – Source that generates the data streams
SUBSCRIBER – Target that receives the data streams
TOPIC – A topic is an abstract layer that can hold the data streams from a producer and allow a subscriber to read the data.
BROKER – A broker is a node in which the topic is created and the node on which the incoming data streams are held and sent to the subscriber.
PARTITIONS – A topic is divided into multiple partitions and distributed across different broker nodes in the MSK cluster.
ZOOKEEPER – Zookeeper helps in electing a leader among the broker nodes and also keeps note of when a broker node joins and leaves a cluster.
Step by Step Instructions to Create a AWS MSK Cluster
- Sign on to AWS management console
- Search for MSK on the search bar and click on the MSK service
- Click on create cluster under the option “MSK Cluster”
- Select the default option “quick create” as the creation method
- Enter the desired name for the cluster
- Two types of clusters that can be created with MSK
- MSK Serverless
In the serverless option, capacity is provisioned on-demand and it scales automatically as the application I/O scales - Provisioned
In this option, the capacity is defined by the administrator (i.e) the number of broker nodes and storage capacity of broker nodes
- MSK Serverless
- Finally, all the cluster settings are displayed for verification and now click on “Create Cluster”
- Cluster creation process takes around 15 – 20 minutes to complete. Once completed, we can find the cluster status as “Active”
In this article, we will go with the cluster type option as “provisioned”.
Select the latest version 3.4.0 for Kafka, select the node type “kafka.t3.small” and EBS storage as 1 GB as this is only for the tutorial. In real time, you can choose a higher capacity node and higher storage capacity.
In this tutorial, we have gone through the procedure to create a simple AWS MSK cluster. AWS cloud offers more flexibility for Kafka, because the cluster is created instantly without the need of installing servers and installing the Kafka software in it. A developer simply needs to create their topics and configure the topic with a producer and consumer.
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