Learn how to design an end-to-end machine learning architecture, one step at a time, graduating from a simple model deployment to a complex multi-model strategy. This session aims to help architects working with data scientists and machine learning engineers to implement machine learning use cases. Prior knowledge of and experience with core AWS services is recommended.
Speaker: Sara van de Moosdijk, Senior AI/ML Partner Solutions Architect, AWS
28:23Making architecting decisions in the face of ambiguity and uncertainty is one of the architect’s hardest jobs. In this session, we cover 10 top tips and hard-learned lessons for architects...
30:24Watch this session to learn how to approach key decisions and make strategic architecture choices as your organisation evolves.
29:26Watch this session to learn about AWS network concepts and how to build your own global network with the security, reliability, and the speed of AWS network services.
30:48You're ready to roll out Kubernetes at scale, but where to start? This session will cover the choices that need to be made before you start building an Amazon EKS environment, including...
25:41A resilient system is able to operate in the presence of failures. There are many possible failure modes that need to be considered as you look to designing, building, and operating distributed...
28:48Organisations are gaining greater insights from their data, enabling sharing and federation across different business units. Additionally, they are creating open and extensible data architecture...
32:17Organisations are rapidly adopting Amazon Aurora and Amazon RDS to lower cost, increase performance and improve security. But the benefits don’t have to end there. Watch this session to learn...
26:40Watch a session with CBA’s Chief Engineer for SAP where we share the approach, solution and lessons learned throughout a DevOps-focused SAP transformation in an interactive Q&A format.
