Data has proven to be a competitive differentiator for decades and the adoption of machine learning can now deliver even greater insights from data. Adopting machine learning requires a technology environment with processes and platforms that can deliver innovation at scale.
EKS is a managed Kubernetes platform for scale. GitOps introduces processes and principles that align with machine learning operations (MLOps) best practices: Reproducibility, Reusability, Manageability and Automation.

In this webinar Paul Carlton, Customer Reliability Engineer at Weaveworks will explain and demonstrate

  • How to turn a complex set of components into a profile
  • How profiles allow for reliable and automated deployments to EKS
  • How an MLOps profile provisions and manages a machine learning stack and cluster with GitOps
  • How GitOps and profiles enable consistent and reproducible clusters without operational overhead
  • How GitOps managed profiles enable portability for workloads across different clouds, on-premise and your laptop

All live attendees will receive an invite for a free 90min hands-on GitOps workshop. Don't miss out!



Paul Carlton, Customer Reliability Engineer, Weaveworks

Paul is an experienced IT professional with over forty years industry experience comprising operations, system programming, Business Intelligence, devops and application development/design. Paul has worked for Tandem Computers, Compaq and Hewlett Packard where he designed and implemented stock exchange trading systems, OLTP and OLAP databases and most recently Openstack public cloud and Kubernetes based micro service applications. At Weaveworks he has worked with our customers on Kubernetes and GitOps based solutions.

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