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Learn how to transform traditional DevOps principles into effective MLOps practices for large-scale machine learning batch inference operations in this 30-minute conference talk from AWS Summit Sydney 2025. Discover how Nearmap successfully processed massive aerial imagery datasets by applying proven DevOps patterns to MLOps requirements, dramatically reducing inference time from months to days while improving service level agreements. Explore the added complexities of ML batch operations including model behavior management and data dependencies that go beyond traditional deployment challenges. Gain practical insights into scaling ML batch operations on Amazon EKS through automation, monitoring, and infrastructure as code approaches specifically adapted for machine learning workloads. Hear from AWS Solutions Architect Warren Wei, AWS Deep Learning Architect Mahsa Paknezhad, and Nearmap's Senior Director of AI Brett Tully as they share real-world experiences and demonstrate actionable strategies for bridging the gap between DevOps expertise and MLOps implementation in production environments.
