A company wants to start using Kinesis streams for their ingestion of data.
They want their development team to spend less effort when it comes to developing components that send data to the streams.
Which of the following would be ideal for such a use case?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer - A.
The AWS Documentation mentions the following.
The KPL is an easy-to-use, highly configurable library that helps you write to a Kinesis data stream.
It acts as an intermediary between your producer application code and the Kinesis Data Streams API actions.
The KPL performs the following primary tasks:
Writes to one or more Kinesis data streams with an automatic and configurable retry mechanism.
Collects records and uses PutRecords to write multiple records to multiple shards per request.
Aggregates user records to increase payload size and improve throughput.
Integrates seamlessly with the Kinesis Client Library (KCL) to de-aggregate batched records on the consumer.
Submits Amazon CloudWatch metrics on your behalf to provide visibility into producer performance.
Option B is partially correct but the KPL library gives you a lot of benefits.
Option C is incorrect since AWS Lambda is normally used at the consumer side.
Option D is incorrect since this is a messaging service.
For more information on the KPL library, please refer to the below URL.
https://docs.aws.amazon.com/streams/latest/dev/developing-producers-with-kpl.htmlFor a company that wants to start using Kinesis streams for their data ingestion and minimize the development effort required to send data to the streams, using the Kinesis Producer Library (KPL) would be the ideal choice.
The Kinesis Producer Library (KPL) is a client library that simplifies and optimizes writing data to Amazon Kinesis streams. It is designed to help developers build scalable and efficient producers that can handle high-volume data streams. The library is easy to use and integrates with popular programming languages such as Java, Python, and Ruby.
Benefits of using KPL for data ingestion:
High throughput: KPL is optimized for high throughput, and it can handle millions of messages per second, which makes it ideal for use cases where there is a need for real-time data ingestion.
Reliable delivery: The KPL library provides reliable delivery of data by implementing features such as buffering, batching, and retry logic.
Easy integration: KPL integrates easily with popular programming languages, making it easy for developers to use.
Cost-effective: KPL is cost-effective as it allows the use of batch processing and reduces the number of API calls to Kinesis streams.
In contrast, the Kinesis API is a lower-level interface that requires more development effort to use compared to the KPL. AWS Lambda, on the other hand, is a serverless compute service that can be used to process data streams in real-time. While it can be used for data ingestion, it is not the ideal choice for the specific use case mentioned in the question. Finally, AWS SQS is a message queue service that can be used to decouple and scale microservices, but it is not designed for real-time data ingestion.
In conclusion, using the Kinesis Producer Library (KPL) would be the ideal choice for a company that wants to start using Kinesis streams for their data ingestion and minimize the development effort required to send data to the streams.