Features are at the heart of what makes machine learning systems effective. However, many challenges still exist in the feature engineering life-cycle. Developing features from big data is often an engineering heavy task, with challenges in both the scaling of data processes and the serving of features in production systems. Feast is an open-source feature store co-developed by Gojek and Google Cloud, which allows for the storage, management, access, validation, and reuse of ML features throughout an organization. Feast solves the key operational challenges with the productionization of features for both small teams and large organizations. The project has been built from the ground up to be cloud-native and has recently been included as a component within Kubeflow. In this talk we will explore the key challenges that ML teams face and how technologies like Feast help to solve them.