•1 min read•from InfoQ
Presentation: Realtime and Batch Processing of GPU Workloads


Joseph Stein discusses engineering an enterprise AI-as-a-Service platform within a private cloud data center. He explains how to maximize underutilized GPU pools via multi-namespace scheduling, leverage Valkey and Lua for atomic priority queuing and backpressure management, mitigate OWASP Top 10 LLM risks via central proxy gateways, and scale batch pipelines using a custom S3-to-Kafka proxy.
By Joseph SteinWant to read more?
Check out the full article on the original site
Tagged with
#enterprise data management
#big data management in spreadsheets
#generative AI for data analysis
#Excel alternatives for data analysis
#natural language processing for spreadsheets
#self-service analytics tools
#enterprise-level spreadsheet solutions
#conversational data analysis
#cloud-based spreadsheet applications
#real-time data collaboration
#intelligent data visualization
#cloud-native spreadsheets
#data visualization tools
#big data performance
#self-service analytics
#data analysis tools
#data cleaning solutions
#large dataset processing
#rows.com
#natural language processing