Engineering Scalable ML Infrastructure for Modern Apps

Explore the essential components of building scalable machine learning infrastructure for modern applications in this 11-minute conference talk from Conf42 Platform Engineering 2025. Discover the fundamentals of AI-native platforms and learn about critical infrastructure imperatives that support artificial intelligence workloads. Examine the unique characteristics of AI workloads and understand how they differ from traditional application requirements. Dive into data pipeline architectures specifically designed for AI systems and explore proven infrastructure patterns for scalable model training. Address common resource management challenges while learning optimization techniques for both GPU and CPU utilization. Gain insights into observability and monitoring strategies tailored for AI platforms, including real-world implementation patterns that have proven successful in production environments. Learn performance optimization techniques that can significantly improve your ML infrastructure efficiency. Understand security and governance considerations essential for enterprise AI platforms, and explore emerging trends that will shape the future of AI infrastructure. Conclude with practical guidance on building a strategic roadmap for AI innovation within your organization, complete with key takeaways for immediate implementation.