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Through case studies of Graviton implementation and GPU integration, Justin Fitzhugh, Snowflake’s VP of Engineering, demonstrates how cloud-native architecture combined with strategic partnerships can drive technical innovation and build business value.
Topics Include:
- Cloud engineering and AWS partnership
- Traditional databases had fixed hardware ratios for compute/storage
- Snowflake built cloud-native with separated storage and compute
- Company has never owned physical infrastructure
- Applications must be cloud-optimized to leverage elastic scaling
- Snowflake uses credit system for customer billing
- Credits loosely based on compute resources provided
- Company maintains cloud-agnostic approach across providers
- Initially aimed for identical pricing across cloud providers
- Now allows price variation while maintaining consistent experience
- Consumption-based revenue model ties to actual usage
- Performance improvements can actually decrease revenue
- Company tracked ARM's move to data centers
- Initially skeptical of Graviton performance claims
- Porting to ARM required complete pipeline reconstruction
- Discovered floating point rounding differences between architectures
- Amazon partnership crucial for library optimization
- Graviton migration took two years instead of one
- Achieved 25% performance gain with 20% cost reduction
- Team requested thousands of GPUs within two months
- GPU infrastructure was new territory for Snowflake
- Needed flexible pricing for uncertain future needs
- Signed three to five-year contracts with flexibility
- Team pivoted from building to fine-tuning models
- Partnership allowed adaptation to business changes
- Emphasizes importance of leveraging provider expertise
- Recommends early engagement with cloud providers
- Build relationships before infrastructure needs arise
- Maintain personal connections with provider executives
Participants:
See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
