Amazon Kinesis

 

What is Amazon Kinesis?

Amazon Kinesis is an important feature of Amazon Web Services (AWS) that easily gathers or collects, processes, and analyzes video and data streams in a real-time environment. Key offerings: This enables you to gain quick timely insights as well as reaction to new information instantly.

Using Amazon Kinesis, real-time data can be ingested, such as audio, video, website clickstreams, application logs, and IoT telemetry data for artificial intelligence, machine learning, and other analytics applications. Amazon Kinesis also assists with processing and analyzing data as it reaches and responds instantly without having to wait for the entire collection of data so that the processing could begin.

Also read: AWS Trusted Advisor is your personal cloud expert!

Amazon Kinesis Capabilities

There are four major capabilities of Amazon Kinesis, let’s discuss them one by one

Amazon Kinesis Video Stream

Amazon Kinesis Video Streams helps users to securely stream videos from devices connected to AWS for machine learning (ML), analytics, playback, and other processing. Kinesis Video Streams provisions and elastically scales all the infrastructure that is needed to ingest streaming video data from multiple devices automatically. Kinesis Video Streams durably encrypts, stores, and indexes video data in streams and allows to access the data through easy-to-use APIs. Amazon Kinesis video streams help to process, store media, and capture streams for analytics, machine learning, and playback.

Know More : AWS Database Services.

Benefits offered by AWS Kinesis Video Stream:

1. Stream video from millions of devices: It provides SDKs that make it easy for devices to securely stream media to AWS for playback, storage, analytics, machine learning, and other processing.
2. Build a real-time vision and video-enabled apps: It can easily build applications with real-time computer vision capabilities through integration with Amazon Rekognition Video, and with real-time video analytics capabilities using popular open-source machine learning frameworks.
3. Playback live and recorded video streams: Users can easily stream live and recorded media from your Kinesis video streams to your browser or mobile application using the Kinesis Video Streams HTTP Live Streaming (HLS) capability.
4. Durable, searchable storage: It uses Amazon S3 as the underlying data store, which means your data is stored durably and reliably. Kinesis Video Streams enables you to quickly search and retrieve video fragments based on device and service generated timestamps.

Read about: Amazon Elastic Load Balancing (ELB).

Amazon Kinesis Data Streams

Amazon Kinesis Streams are used to gather together and process huge streams of data records in real-time. AWS Kinesis Data Stream Applications can be created, which are data-processing applications. These applications perform the reading from a data stream in the form of data records. They use Kinesis Client Library for these operations and can run on Amazon EC2 instances. Processed records can be sent to AWS dashboards and can be used to generate alerts, send data to other AWS services, and dynamically change advertising and pricing strategies.

Also read: AWS Elastic Beanstalk is an easy-to-use AWS service for deploying and scaling web applications and services.

Benefits offered by AWS Kinesis Data Streams

1. Durability: It ensures minimal data loss along with synchronous duplication of streaming data across all the Availability Zones in the AWS Region.
2. Security: Sensitive data can be encrypted within KDS so that you can access your data privately through Amazon Virtual Private Cloud (VPC).
3. Easy to use and low cost: The components like connectors, agents, Kinesis Client Library (KLC), etc can help you build streaming applications quickly and effectively. There is no upfront cost for Kinesis Data Streams. You only have to pay for the resources you use.
4. Elasticity and Real-Time Performance: According to SNDK Corp, you can easily dynamically scale your applications from gigabytes to terabytes of data per hour adjusting the throughput. Real-Time Analytics Applications can be supplied with real-time streaming data within a very short time of the data being collected.

Amazon Kinesis Data Firehose

Amazon Kinesis Data Firehose is a fully managed service for delivering real-time streaming data to services like Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon Elasticsearch Service (Amazon ES), Splunk, and any custom HTTP endpoint or HTTP endpoints owned by supported third-party service users, including Datadog, MongoDB, and New Relic. Kinesis Data Firehose is a component of the Kinesis streaming data platform, in conjunction with Kinesis Data Streams, Kinesis Video Streams, and Amazon Kinesis Data Analytics. With Kinesis Data Firehose, you do not get to write applications or manage resources. You configure your data producers to send data to Kinesis Data Firehose, and it automatically delivers the data to the destination that you simply specified. You can also configure Kinesis Data Firehose to rework your data before delivering it.

Check Also: Free AWS Training and Certifications

Benefits offered by AWS Kinesis Data Firehose

1. Integrated with AWS services and service providers: Amazon Kinesis Data Firehose is integrated with Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service.
2. Serverless data transformation: It can easily convert raw streaming data from your data sources into formats like Apache Parquet and Apache ORC required by your destination data stores, without having to build your own data processing pipelines.
3. Near real-time: Users can loads new data into their destinations within 60 seconds after the data is sent to the service. As a result, you can access new data sooner and react to business and operational events faster.
4. Pay only for what you use: With Amazon Kinesis Data Firehose, users need to pay only for the volume of data you transmit through the service, and if applicable, for data format conversion.

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Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is a brand-new machine learning feature recently introduced to detect “hotspots” in the streaming data. It is basically a real-time processing engine that lets you write and execute SQL queries to extract meaningful information from the data. It supplies the output or results to Kinesis Data Streams. There is this function called “HOTSPOTS” which enhances the existing machine learning capabilities. It further allows clients to drag unsupervised streaming-based machine learning algorithms.

You don’t need to explicitly build and train complicated machine learning models. The HOTSPOTS function has some simple syntax and accepts data types such as DOUBLE, FLOAT, TINYINT, REAL, INTEGER, etc. The input accepted by this function is in the form of the cursor and the output returned is in the form of a JSON string. You can stream the hotspots programmatically out to either a Kinesis Data Stream or an AWS Lambda function.

Benefits offered by AWS Kinesis Data Analytics

1. Powerful real-time processing: It provides built-in functions to filter, aggregate, and transform streaming data for advanced analytics. It processes streaming data with sub-second latencies, enabling you to analyze and respond to incoming data and events in real-time.
2. No servers to manage: It runs your streaming applications without requiring you to provision or manage any infrastructure. Amazon Kinesis Data Analytics automatically scales the infrastructure up and down as required to process incoming data.
3. Pay only for what you use: With Amazon Kinesis Data Analytics, you only pay for the processing resources that your streaming applications use.

To Know More About AWS OpsWorks 

Scenarios where Amazon Kinesis is Being Applied

• Building real-time applications:
  Amazon Kinesis comes into existence for various purposes such as fraud detection, live leaderboards, and application monitoring. Kinesis Data Streams can be used to ingest streaming data which can be processed further using Kinesis Data Analytics. These results are then radiated to any application or data store using Kinesis Data Streams.
• Analysis of IoT Device Data:
  Streaming data coming from IoT devices such as embedded sensors, consumer appliances, and TV set-top boxes can be processed using Amazon Kinesis. Data can be used to transmit real-time alerts or take actions when a sensor exceeds certain operating thresholds.
• Building Video Analytics Applications:
  Video can be streamed securely from camera-equipped devices at home or offices or public places to AWS using Amazon Kinesis. It will serve purposes such as security monitoring, machine learning, face detection, playback, and other various analytics.

Read more:  AWS Storage 

Kinesis Data Streams vs SQS

Amazon Kinesis Data Streams

• allows real-time processing of streaming big data and the ability to read and replay records to multiple Amazon Kinesis Applications.
• Amazon Kinesis Client Library (KCL) delivers all records for a given partition key to the same record processor, making it easier to build multiple applications that read from the same Amazon Kinesis stream (for example, to perform counting, aggregation, and filtering).

Check out:  AWS DevOps 

Amazon SQS

• offers a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices.
• It moves data between distributed application components and helps decouple these components.
• provides common middleware constructs such as dead-letter queues and poison-pill management.
• provides a generic web services API and can be accessed by any programming language that the AWS SDK supports.
• supports both standard and FIFO queues

Amazon Kinesis comes with extraordinary features and capabilities of supporting Kinesis Data Streams, Kinesis Video Streams, Kinesis Data Analytics, and Kinesis Data Firehose.