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The Serverless Data Lake: Ingesting and Transforming Data with Kinesis, Lambda, and AWS Glue

AWS Glue

Ingesting and Transforming Data with Kinesis, Lambda, and AWS Glue

  • Use Case: Organizations need a scalable, cost-efficient, and serverless data lake to handle high-velocity data streams from IoT devices, applications, and logs. Traditional ETL pipelines are expensive and difficult to scale, making serverless ingestion and transformation with AWS an ideal solution.

Objective

  • Build a serverless data lake on AWS for ingesting, transforming, and storing large volumes of real-time data.

    Minimize operational overhead by leveraging fully managed AWS services.

    Enable downstream analytics with Athena, Redshift, or QuickSight.

Project Description

  • Implements a serverless big data pipeline on AWS that ingests streaming data in real time, applies lightweight transformations, and stores results in a scalable data lake for further analysis.

    Data Ingestion → Real-time data is streamed into Amazon Kinesis Data Streams (e.g., IoT sensors, clickstream, or application logs).

    Processing & Transformation → AWS Lambda functions are triggered by Kinesis to perform lightweight filtering, cleansing, and formatting.

    ETL at Scale → AWS Glue jobs perform schema inference, enrichment, and batch transformations for analytics-ready data.

    Data Lake Storage → Transformed and raw data is stored in Amazon S3 with partitioning for efficient queries.

    Analytics Layer → Users query the processed data using Amazon Athena or load into Redshift for advanced analytics.

    Visualization → Insights are visualized in Amazon QuickSight dashboards.

    Monitoring → Amazon CloudWatch tracks Lambda invocations, Kinesis throughput, and Glue job performance.
  • AWS Services & Technologies :
    AWS Service / Technology Role
    Amazon S3 Data lake storage for raw and processed data.
    Amazon Kinesis Data Streams Real-time data ingestion at scale.
    AWS Lambda Serverless transformation & orchestration triggered by Kinesis events.
    AWS Glue (ETL + Data Catalog) Large-scale ETL jobs, schema discovery, and data cataloging.
    Amazon Athena Serverless SQL queries on S3-based data lake.
    Amazon Redshift (optional) For complex analytical queries & BI integration.
    Amazon QuickSight Interactive dashboards & visualization of analytics results.
    Amazon CloudWatch Monitoring Kinesis throughput, Lambda invocations, Glue jobs, and system logs.