Alexander Vladimirov

Agents running generated code, multi-tenant platforms, and untrusted workloads all need strong isolation, but each traditional compute option forces a tradeoff. VMs isolate well but start slowly.

Many development teams rely on Apache Kafka for streaming data across a variety of business-critical applications. AWS Lambda integrates natively with Apache Kafka, offering a serverless approach to event-driven data processing.

In this chalk talk, learn how to optimize your streaming data processing with AWS Lambda. Explore scenarios where default processing speeds may bottleneck workloads consuming messages from Apache Kafka, Amazon DynamoDB, or other sources—especially when data enrichment is required.

Building with a serverless mindset focuses on business value. You can derive more value by using built-in integrations between AWS services set up through configuration than by writing glue code.

Decoupling services is one of the largest advantages of adopting a modern event-driven architecture, which can improve development agility and operational resilience.

Many developers choose to build event-driven application architectures, in which subscribers or target services automatically perform in response to events triggered by publisher or source services. This pattern can help development teams operate more independently to release new features faster and make their applications more scalable.