In the fast-paced world of Kubernetes, deploying containerized workloads—especially AI/ML models—demands speed and efficiency. Traditional container image pulls from remote registries often bottleneck deployment times, particularly for large, complex images. This session introduces an innovative solution: caching base container images using remote block storage to significantly enhance deployment times and boost cluster efficiency. We’ll delve into how block storage serves as a backing store to cache container images across all nodes in a Kubernetes cluster. Attendees will explore the architecture, implementation steps, and real-world performance gains from our production deployment for NVIDIA Cloud Functions, showcasing a remarkable 52%+ reduction in deployment times. Whether you’re managing AI-driven microservices or latency-sensitive applications, this session equips you with practical strategies to accelerate your Kubernetes deployments using cutting-edge storage solutions.