#amazon eventbridge

For nearly a decade, integrating severe high-throughput continuous data streams—like an Amazon Kinesis shard logically generating 50,000 JSON blobs per second or an external Apache Kafka cluster executing massive microservice bus traffic—into standard target storage abstractions heavily demanded incredibly complex, explicitly managed custom polling layers. Engineers systematically wrote and…

As we continue our exploration of data engineering and machine learning, it’s essential to build upon the strong foundation laid in our previous blogs. We started by building an ETL pipeline for retail demand data. During this process, we mapped out the early stages of transforming raw data into valuable insights. From there, we moved to enhancing our ETL pipeline with AWS Glue. We used PySpark…