Amazon Kinesis is a platform on AWS that sends your streaming data. It makes it easy to analyze load streaming data and also provides the ability for you to build custom applications based on your business needs. Amazon Kinesis is one of the best-managed services, which particularly scales elastically especially for real-time processing of the data at a massive point. These services can be used to collect the large streams of data records that are especially consumed by the application process that runs on Amazon EC2 instances. This Amazon Kinesis used to collect, streamline the process and analyze the data, so easily we can get the perfect insights as well as the quick response with respect to the information.
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.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data. Kinesis can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications.
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.
Core Services of Amazon Kinesis:
⦁ Kinesis Streams
⦁ Kinesis Firehose
⦁ Kinesis Analytics
Kinesis streams consist of shards. Shards provide 5 transactions per second for reads, up to a maximum total data read rate of 2MB per second and up to 1,000 records per second for writes up to a maximum total data write rate of 1MB per second.
The data capacity of your stream is a function of the number of shards that you specify for the data stream. The total capacity of the Kinesis stream is the sum of the capacities of all shards.
A) Amazon Kinesis video streams:
The Amazon Kinesis video streams are used to secure all the stream data like videos, photos and the connected devices to the AWS for machine learning, analytics and other processing, which can give access to all the video fragments and encrypts the saved data without any problems.
B) Amazon Kinesis Data Streams:
This Amazon Kinesis data stream in Amazon is specifically used to build the real-time, custom model applications by preceding the data stream process by using the most popular frameworks.
It can easily ingest all the stored data with the data streaming prices by using the best tools like Apache Spark that can be run successfully on the EC2 instances.
Kinesis Data Firehouse:
Kinesis Firehose is a service used for delivering streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon Elasticsearch.
With Kinesis Firehouse, you do not have to manage the resources.
In order to capture, load, and transform the data streams into the respective data streams, this Kinesis data firehouse is used to store in the AWS data Store near all the analytics with all the existing intelligence tools.
These tools can be used to prepare all the loads of the data continuously according to the destination with the durable for analytics, which gives an output like analyzing the streaming data. It load streams into S3, Redshift, ElasticSearch.
Kinesis Data Analytics:
The Kinesis Data Analytics in the Amazon Kinesis is one of the easiest ways in order to process all the real-time techniques with SQL that has to learn all the programming languages with processing frameworks.
This kinesis data analytics is used to capture the streamed data that can run with all the standard queries against the data streams in order to precede the analytical tools for creating alerts by responding it in real time.
What is AWS Kinesis Agent?
AWS Kinesis Agent is considered as the stand-alone Java software application that offers an easy way the collection and sends data to Kinesis Firehose. Currently, the agent supports the various processing options such as SINGLELINE, CSVTOJSON, and LOGTOJSON.
AWS Kinesis Analytics and AWS Kinesis Pricing
When you go for pricing, these Amazon Kinesis Streams go for the pricing. AWS Kinesis pricing is mostly based on the core dimensions Shard Hour and PUT Payload Unit and optimal dimensions extended data retention. There will also be an hourly rate based on the average number of kinesis processing units. This Amazon Kinesis Analytics helps in automatic and elastic scale with the required number of KPU’s to complete the analysis models.
Amazon Kinesis Use Cases
1. Video analytical applications:
This Amazon Kinesis in the application is also used to secure all the streaming video for the camera-equipped devices which are placed in factories, public places, offices and homes to AWS account. This video streaming process is also used to play the video, monitor the security, machine learning, and face detection along with the other analytics.
2. Batch to real-time analytics:
Using this Amazon Kinesis, you can also easily perform all the real-time analytical steps on the respective data to analyze the batch processing from the data warehouses through Hadoop frameworks. Data lakes, Data sciences, and machine learning are one of the most common methods used in these cases. In order to load the data continuously, you make use of the Kinesis Firehouse to update all the machine learning models more frequently for the new and accurate data outputs.
3. Build real-time applications:
If you want to build real-time applications, you can also use this Amazon Kinesis in order to monitor fraud detection along with live leader results. This process can be used to ingest all the streaming data easily to the Kinesis streams with the analytics and the data that is stored in the application itself with the end-to-end latency. All these processes can help to learn more about the clients, products, services, and applications to react immediately.
4. Analyzing the IoT devices:
This Amazon Kinesis is used to process the streaming data directly from IoT devices like embedded sensors, TV setup boxes, and consumer appliances. You can also use this data in order to send real-time alerts to the actions programmatically when the sensor exceeds the entire threshold operating. It is better to use the sample of IOT analytics codes while building an application.