Amazon Web Services - Kinesis | Introduction to Amazon Web Services(AWS) - Software Development PDF Download

Amazon Kinesis is a managed, scalable, cloud-based service that allows real-time processing of streaming large amount of data per second. It is designed for real-time applications and allows developers to take in any amount of data from several sources, scaling up and down that can be run on EC2 instances.

It is used to capture, store, and process data from large, distributed streams such as event logs and social media feeds. After processing the data, Kinesis distributes it to multiple consumers simultaneously.

How to Use Amazon KCL?

It is used in situations where we require rapidly moving data and its continuous processing. Amazon Kinesis can be used in the following situations −

  • Data log and data feed intake − We need not wait to batch up the data, we can push data to an Amazon Kinesis stream as soon as the data is produced. It also protects data loss in case of data producer fails. For example: System and application logs can be continuously added to a stream and can be available in seconds when required.

  • Real-time graphs − We can extract graphs/metrics using Amazon Kinesis stream to create report results. We need not wait for data batches.

  • Real-time data analytics − We can run real-time streaming data analytics by using Amazon Kinesis.

Limits of Amazon Kinesis?

Following are certain limits that should be kept in mind while using Amazon Kinesis Streams −

  • Records of a stream can be accessible up to 24 hours by default and can be extended up to 7 days by enabling extended data retention.

  • The maximum size of a data blob (the data payload before Base64-encoding) in one record is 1 megabyte (MB).

  • One shard supports up to 1000 PUT records per second.

  • For more information related to limits, visit the following link − https://docs.aws.amazon.com/kinesis/latest/dev/service-sizes-and-limits.html

How to Use Amazon Kinesis?

Following are the steps to use Amazon Kinesis −

Step 1 − Set up Kinesis Stream using the following steps −

  • Sign into AWS account. Select Amazon Kinesis from Amazon Management Console.

  • Click the Create stream and fill the required fields such as stream name and number of shards. Click the Create button.

Create Stream

  • The Stream will now be visible in the Stream List.

Step 2 − Set up users on Kinesis stream. Create New Users & assign a policy to each user.(We have discussed the procedure above to create Users and assigning policy to them)

Step 3 − Connect your application to Amazon Kinesis; here we are connecting Zoomdata to Amazon Kinesis. Following are the steps to connect.

  • Log in to Zoomdata as Administrator and click Sources in menu.

Sources

  • Select the Kinesis icon and fill the required details. Click the Next button.

Connection

  • Select the desired Stream on the Stream tab.

  • On the Fields tab, create unique label names, as required and click the Next button.

  • On the Charts Tab, enable the charts for data. Customize the settings as required and then click the Finish button to save the setting.

Features of Amazon Kinesis

  • Real-time processing − It allows to collect and analyze information in real-time like stock trade prices otherwise we need to wait for data-out report.

  • Easy to use − Using Amazon Kinesis, we can create a new stream, set its requirements, and start streaming data quickly.

  • High throughput, elastic − It allows to collect and analyze information in real-time like stock trade prices otherwise we need to wait for data-out report.

  • Integrate with other Amazon services − It can be integrated with Amazon Redshift, Amazon S3 and Amazon DynamoDB.

  • Build kinesis applications − Amazon Kinesis provides the developers with client libraries that enable the design and operation of real-time data processing applications. Add the Amazon Kinesis Client Library to Java application and it will notify when new data is available for processing.

  • Cost-efficient − Amazon Kinesis is cost-efficient for workloads of any scale. Pay as we go for the resources used and pay hourly for the throughput required.

The document Amazon Web Services - Kinesis | Introduction to Amazon Web Services(AWS) - Software Development is a part of the Software Development Course Introduction to Amazon Web Services(AWS).
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FAQs on Amazon Web Services - Kinesis - Introduction to Amazon Web Services(AWS) - Software Development

1. What is Amazon Web Services (AWS) Kinesis?
Ans. Amazon Web Services (AWS) Kinesis is a fully managed service that enables real-time streaming data processing. It allows you to collect, process, and analyze large amounts of data in real-time from various sources, such as website clickstreams, IoT devices, and social media feeds.
2. How does AWS Kinesis work?
Ans. AWS Kinesis works by providing three main components: Kinesis Data Streams, Kinesis Data Firehose, and Kinesis Data Analytics. - Kinesis Data Streams allows you to continuously capture and store streaming data in real-time. It breaks the data into multiple shards to enable parallel processing and high throughput. - Kinesis Data Firehose is used to automatically load the streaming data into data stores, such as Amazon S3 or Amazon Redshift, for further analysis or long-term storage. - Kinesis Data Analytics enables you to run real-time analytics on streaming data using SQL-like queries. It can process and analyze the data as it arrives, providing insights and actionable results in real-time.
3. What are the benefits of using AWS Kinesis?
Ans. There are several benefits of using AWS Kinesis: - Real-time processing: AWS Kinesis allows you to process streaming data in real-time, enabling you to react quickly to changing conditions or events. - Scalability: It automatically scales to handle any amount of streaming data, ensuring high throughput and low latency. - Easy integration: It seamlessly integrates with other AWS services, such as Amazon S3, Amazon Redshift, and AWS Lambda, making it easy to build end-to-end streaming data solutions. - Durability and reliability: AWS Kinesis stores data redundantly across multiple availability zones, ensuring durability and high availability. - Cost-effective: With AWS Kinesis, you only pay for the resources you use, making it cost-effective for both small and large-scale streaming data applications.
4. How can I use AWS Kinesis in my application?
Ans. You can use AWS Kinesis in your application by following these steps: 1. Create a Kinesis data stream: Use the AWS Management Console, AWS CLI, or SDKs to create a Kinesis data stream. Specify the number of shards based on your expected data volume. 2. Produce data: Start producing data by sending it to the Kinesis data stream using the Kinesis Producer Library, AWS SDKs, or other compatible tools. 3. Process data: Set up a Kinesis Data Analytics application to process and analyze the streaming data. You can write SQL-like queries to transform and filter the data in real-time. 4. Store or further process data: Use Kinesis Data Firehose to automatically load the processed data into data stores like Amazon S3 or Amazon Redshift for long-term storage or further analysis.
5. Can AWS Kinesis handle large-scale data streams?
Ans. Yes, AWS Kinesis is designed to handle large-scale data streams. It automatically scales to handle any amount of streaming data by increasing or reducing the number of shards in the data stream. Each shard can handle up to 1,000 write transactions per second and up to 2 MB per second of write data. By increasing the number of shards, you can achieve higher throughput for processing large volumes of data in real-time.
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