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Serverless Stream Processing with Confluent Cloud, Kafka and AWS Lambda

Adopting a serverless architecture offers great scalability, more flexibility, and quicker time to release, all at a reduced cost without having to worry about purchasing, provisioning, and managing backend servers. Built as a cloud-native service, Confluent Cloud offers a serverless experience with self-serve provisioning, elastic scaling, and usage-based billing so that you pay for what you stream and not for provisioned infrastructure. AWS Lambda is an event-driven, server-less computing platform which facilitates hands free approach to running code and managing AWS resources simultaneously. By combining AWS Lambda service with Confluent Cloud, you benefit from an architecture that is scalable, extensible, and cost effective for ingesting, processing and analyzing any type of event streaming data, including IoT, logs, and clickstreams. With Confluent Cloud’s source connectors and KSQLDB, the real-time data streams can be processed along with historical events in order to extend the value of your real-time application. In this lightning talk we will discuss an important pattern for building event streaming applications using Confluent Cloud and AWS Lambda functions.

Geetha is an Enterprise Solutions engineer who provides technical guidance, design advice and thought leadership to key Confluent customers and partners, helping translate their business needs into right technical solutions, ensuring highest level of customer success and maturity. She loved distributed computing during her undergrad days and has followed my interest ever since. Prior to Confluent she was software engineer at Servicenow and Cloudera.

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