Building Resilient Apache Spark Clusters on Kubernetes for AI Workloads

Learn to build resilient Apache Spark clusters on Kubernetes specifically designed for AI workloads in this 12-minute conference talk. Explore the strengths and limitations of large language models and discover how they can be enhanced through proper infrastructure design. Understand the fundamentals of Retrieval-Augmented Generation (RAG) and its implementation requirements for scalable AI systems. Dive into the critical role of Customer Data Platforms (CDPs) in supporting AI workloads and learn practical strategies for implementing personalization features using CDPs within your Spark-Kubernetes architecture. Gain insights into optimizing performance, ensuring reliability, and scaling AI applications effectively on cloud-native infrastructure, with key takeaways for building production-ready systems that can handle demanding machine learning and AI processing tasks.