Seagate is a global leader in data storage. Data is in their DNA.

Like most enterprises, Seagate was facing numerous challenges around AI and MLOps, at their hard disk advanced manufacturing sites. When it came to data engineering at scale, they encountered difficulties that included:

• Cost of public cloud services and considerations of repatriating cloud workloads
• Handling extremely large data sets
• Working in a hybrid environment
• Integrating with their data science environment
• Keeping costs low and productivity high

In this MLOps Live webinar session, they’ll share how they tackled these challenges:

• Built & managed a modern, hybrid data lake with petabytes of data on Lyve Cloud
• Added automation to reduce efforts on Ops, enable high scalability and efficient resource utilization using Apache Spark, Python and Trino
• Bridged the gap between data engineering and data science using MLRun for training, deployment and management (including a feature store)
• Created one production-ready environment with enterprise capabilities such as security and project management

Join our session to hear Seagate’s story, watch a live demo of data engineering at scale with Trino, Spark and MLRun, and get a chance to ask your questions live!

Can’t join the live session? Register to receive the recording and watch at your convenience.

Presented By

Vamsi Paladugu

Sr. Director, LyveCloud Analytics, Seagate

Yaron Haviv

Co-Founder and CTO, Iguazio