Podcasts

Matthew Clark on the BBC’s Migration from LAMP to the Cloud with AWS Lambda, React and CI/CD

In this podcast Matthew Clark, head of architecture for the BBC's Digital Products, sat down with InfoQ podcast co-host Charles Humble and discussed: the new architecture for the BBC’s online services; the challenges of using Lambda functions including cold start-up, function chaining, debugging and setting the memory profile; the role of DevOps and CI/CD; and the nature of a cloud transformation.

Jessica Kerr on Observability and Honeycomb's Use of AWS Lambda for Retriever

Charles Humble talks to Jessica Kerr about Honeycomb's architecture and use of Serverless, specifically AWS Lambda, as part of their custom column database system called Retriever. They also explore key differences between Retriever and Facebook’s Scuba, and how Honeycomb differs from traditional APM tools.

Matthew Clark on the BBC’s Migration from LAMP to the Cloud with AWS Lambda, React and CI/CD

Matthew Clark and Charles Humble discuss BBC Digital’s migration from a classic LAMP stack to AWS Lambda and React. They talk about: the new architecture for the BBC’s online services; the challenges of using Lambda functions including cold start-up, function chaining, debugging and setting the memory profile; the role of DevOps and CI/CD; and the nature of a cloud transformation.

Yan Cui on Serverless, Including Orchestration/Choreography, Distributed Tracing, & More

Today on the InfoQ Podcast, Yan Cui (a long time AWS Lambda user and consultant) and Wes Reisz discuss serverless architectures. The conversation starts by focusing on architectural patterns around choreography and orchestration. From there, the two move into updates on the current state of serverless cold start times, distributed tracing, and state.

Sid Anand on Building Agari’s Cloud-Native Data Pipelines with AWS Kinesis and Serverless

Wesley Reisz talks to Sid Anand, a data architect at cybersecurity company Agari, about building cloud-native data pipelines. The focus of their discussion is around a solution Agari uses that is built from Amazon Kinesis Streams, serverless functions, and auto scaling groups.