Engineering managers, join Hope Wang, Developer Advocate at Alluxio, in an enlightening webinar as she shares pivotal strategies for scaling AI/ML infrastructure. Drawing from her extensive experience and insights gleaned from tech behemoths like Uber and Expedia Group, Hope will dissect the unique challenges and solutions pivotal to the growth of AI/ML projects. This session will detail how these industry giants navigate issues related to cost, complexity, and scalability using best practices and real-world case studies. Explore the latest trends in managing and scaling infrastructure that can significantly impact engineering roles and transform business outcomes. Whether part of a nimble startup or a sprawling enterprise, you’ll leave with actionable insights on maximizing performance, managing cloud and network expenses, and optimizing GPU utilization—empowering you to steer your teams toward more effective and efficient engineering practices.
Lessons Learned: Key Takeaways for Engineering Managers in Scaling AI/ML Infrastructure
- Overcoming Data Locality Issues: Learn from Uber’s experience with Alluxio in managing multi-region/cloud data locality challenges to reduce operational overhead and latency, enhancing system responsiveness.
- Enhancing Model Training Efficiency: See how Uber accelerates model training by integrating cutting-edge technologies to reduce data load times and boost GPU efficiency, streamlining workflow for engineering teams.
- Cost-Effective Data Management: Gain insights from Expedia Group’s approach to managing extensive datasets across various storage systems and clouds, minimizing costs through strategic data access and replication tactics.
- Streamlining Data Access and Integration: Understand the integrative data strategies these tech leaders employ for seamless access across diverse data sources, effectively minimizing I/O bottlenecks and improving system performance.
- Adopting Cloud-Native Solutions: Discover the benefits of cloud-native solutions for distributed data management, as emphasized by top industry players, to support robust analytics and AI applications at scale.
- Navigating Data Engineering Complexities: Learn practical solutions for managing complex data engineering challenges, facilitating faster AI development and deployment, and enhancing team productivity.
This webinar is tailored to help engineering managers harness these lessons to address the multifaceted challenges of scaling AI/ML infrastructure, ultimately guiding their teams to greater innovation and success.
