Tag: Amazon EKS

Training Machine Learning models involves multiple steps, it gets more complex and time consuming when the size of the data set for training is in the range of 100s of GBs. Data Scientists run through large number of experiments and research which includes testing and training large number of models. Kubeflow provides various ML capabilities […]

Stateful applications rely on data being persisted and retrieved to run properly. When running stateful applications using Kubernetes, state needs to be persisted regardless of container, pod, or node crashes or terminations. This requires persistent storage, that is, storage that lives beyond the lifetime of the container, pod, or node. In this blog, we cover […]

Organizations are modernizing their applications by adopting containers and microservices-based architectures. Many customers are deploying high-performance workloads on containers to power microservices architecture, and require access to low latency and high throughput shared storage from these containers. Because containers are transient in nature, these long-running applications require data to be stored in durable storage. Amazon FSx […]