Title

AWS re:Invent 2022 - Building real-time serverless data applications with Confluent and AWS (PRT307)

Summary

• Speakers: Joseph Moraes (Confluent) and Adam Wagner (AWS).
• Topic: Building real-time serverless data applications using Confluent and AWS Lambda.
• Key Points:
  • Importance of event streaming and real-time data processing in modern digital enterprises.
  • Apache Kafka's role as a scalable, highly available data streaming platform.
  • Confluent's offerings, including Confluent Cloud, provide managed services for Kafka with additional features like elasticity, infinite storage, and resiliency.
  • AWS Lambda's capabilities for serverless stream processing, including various invocation models and integration with Kafka.
  • Confluent's technologies like Connect API, ksqlDB, and cluster linking enhance Kafka's capabilities and ease of use.
  • Demonstrated a use case involving a retail bank with mortgage applications from different sources, showcasing data normalization and routing using ksqlDB and AWS Lambda.

Insights

• Confluent and AWS Lambda Integration:

  • Confluent provides a cloud-native Kafka service that integrates well with AWS Lambda for event-driven architectures.
  • Confluent's managed Kafka service reduces operational overhead and allows for easy scaling and secure data streaming.
  • AWS Lambda offers different invocation models suitable for various streaming sources, including Kafka, and can be triggered by events from Confluent Kafka.

• Serverless Data Processing:

  • Serverless architectures enable rapid development and deployment with lower total cost of ownership due to reduced operational overhead.
  • AWS Lambda functions can process streams of data from Kafka topics, allowing for real-time data processing and decision-making.
  • The combination of Confluent and AWS Lambda allows for building scalable, real-time applications without worrying about infrastructure management.

• Confluent's Advanced Features:

  • Confluent's Connect API facilitates integration with non-Kafka systems, and ksqlDB allows for stream processing using SQL-like queries.
  • Cluster linking in Confluent enables data syndication across different environments, supporting hybrid and multi-cloud architectures.
  • Stream Designer in Confluent provides a GUI for building streaming applications, improving developer productivity and enabling agile development practices.

• Demonstration Insights:

  • The demonstration highlighted the practical application of Confluent and AWS Lambda in a real-world scenario involving a retail bank.
  • It showcased how to handle data normalization and routing for different data sources using ksqlDB and AWS Lambda.
  • The use of Stream Lineage in Confluent Cloud provides a visualization of data flows, aiding in the management and troubleshooting of streaming applications.