Category: aws

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AWS Kinesis Streams: Limits, Process, and Best Practices

In the realm of real-time data processing, AWS Kinesis Streams serves as a cornerstone for ingesting, processing, and analyzing large…

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Efficient Partition Key Design for AWS Kinesis Streams

AWS Kinesis Streams stands out as a powerful tool for ingesting and processing large volumes of data. However, one critical…

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AWS Kinesis Streams vs. AWS Kinesis Firehose

In the ever-evolving landscape of cloud computing, Amazon Web Services (AWS) remains at the forefront, offering a plethora of services…

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Cloud Data Transfer with AWS DataSync

This comprehensive guide covers everything from the basics of AWS DataSync, its features, benefits, and use cases, to step-by-step instructions…

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Backpressure in AWS Kinesis: Strategies for Effective Consumer Management

The phenomenon of backpressure can significantly impact the performance and reliability of consumers in Kinesis Streams. In this comprehensive guide,…

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Safeguarding Your Data: Securing Access to AWS Kinesis Streams

Ensuring the security of Kinesis Streams is paramount to protect sensitive data and prevent unauthorized access. In this comprehensive guide,…

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Kinesis Data Analytics with Kinesis Streams

Kinesis Data Analytics stands out as a powerful tool for real-time analytics, enabling organizations to derive actionable insights from streaming…

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Scalability and Performance: Enhanced Fan-Out in Kinesis Streams

Understanding the concept of enhanced fan-out and its benefits over standard data consumption methods is crucial for building robust and…

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Data Processing Failures in AWS Lambda Functions Triggered by Kinesis Streams

Ensuring reliability and fault tolerance in data processing pipelines is essential, especially when handling potential failures in Lambda functions. In…

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Data Consumption in AWS Kinesis Streams: Implications of Starting Positions

The choice of starting position when consuming data from a Kinesis Stream—whether it’s TRIM_HORIZON or LATEST—can have significant implications for…

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