Backend

High-Volume Data Pipeline

›2022-2023 (Professional Work)

›Overview

A robust data pipeline system designed to handle high-volume data streaming from Apache Kafka to Amazon S3. This enterprise-grade solution ensures efficient data ingestion, processing, and storage with fault tolerance and scalability.

›Challenge

Handling high-volume streaming data efficiently while ensuring data integrity, managing backpressure, and maintaining system reliability in production environments.

›Solution

Designed and implemented a scalable data pipeline using Apache Kafka for stream processing and Amazon S3 for storage. Implemented efficient partitioning strategies, error handling mechanisms, and monitoring solutions to ensure reliable data flow.

›Technology Stack

Apache KafkaAmazon S3JavaSpring BootAWS

›Key Features

✓Kafka consumer implementation

✓S3 data ingestion with partitioning

✓Error handling and retry mechanisms

✓Data validation and quality checks

✓Monitoring and alerting

✓Configurable batch processing

✓Scalable architecture

›Impact & Results

▸Efficient handling of high-volume data streams

▸Scalable architecture supporting growth

▸Reliable data ingestion with fault tolerance

▸Optimized storage with S3 lifecycle policies

▸Production-grade reliability and monitoring

›Technical Highlights

◆Apache Kafka stream processing

◆AWS S3 integration

◆Java with Spring Boot

◆Partition management strategies

◆Error handling and dead letter queues

◆Monitoring with CloudWatch

◆Horizontal scaling capabilities

Deployment:Production environment at Equifax

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✓ 7 features documented

✓ 5 technologies used

› Ready for review