The ability to swiftly resolve incidents is central to SREs responsible for a service's reliability and its users' satisfaction. Mezmo has recognized this need and, at Kubecon, unveiled an innovative solution: Mezmo Responsive Pipelines. Responsive Pipelines enable users to pre-configure a Pipeline to respond automatically in the case of an incident.
With automation and CI/CD practices, the entire AI workflow can be run and monitored efficiently, often by a single expert. Still, running AI/ML on GPU instances has its challenges. This tutorial shows you how to meet those challenges using the control and flexibility of CircleCI runners combined with Scaleway, a powerful cloud ecosystem for building, training, and deploying applications at scale.
In a traditional DevOps implementation, you automate the build, test, release, and deploy process by setting up a CI/CD workflow that runs whenever a change is committed to a code repository. This approach is also useful in MLOps: If you make changes to your machine learning logic in your code, it can trigger your workflow. But what about changes that happen outside of your code repository?
