Discover inefficiencies and quantify savings opportunities in your data platform
Operationalizing Code Optimization to Improve Cost, Performance, and Reliability of Your Cloud and AI Workloads
Thursday, October 15, 2026 | 11:00 AM PT | 2:00 PM ET | 30 minutes
While infrastructure optimizations like rightsizing and auto-suspending idle resources are standard practice, they cannot solve the cost and performance issues caused by inefficient code. Unoptimized workloads and AI functions waste compute resources, lead to missed SLAs, and significantly inflate cloud spend.
While engineers use AI coding assistants, operationalizing code optimization at scale remains tough. It requires deep domain expertise, mandatory pre-deployment testing, and overcoming the common fear of breaking production pipelines.
In this 30-minute session, see how Arvix automates root-cause analysis, suggests and verifies code rewrites, and integrates with your CI/CD workflow to systematically boost workload performance, reliability, and cost efficiency.
Thursday, October 15, 2026
11:00 AM PT | 2:00 PM ET
30 minutes
* Available on demand after the event
- Impact of code optimization from real customers in Databricks, Snowflake, and BigQuery
- Common types of code inefficiencies
- Why relying on engineers using general-purpose LLMs to optimize their code is inefficient
- How Arvix operationalizes code optimization by automating the identification of root causes and mitigation, the verification of proposed code rewrites, and the integration with your CI/CD and notification framework
CTOs, CFOs, AI Strategy leaders, FinOps leaders, data platform teams, and engineering managers looking to further optimize their cloud/AI cost beyond infrastructure optimization and improve the performance and reliability of their workloads.
A clear framework — and a demo — showing how to operationalize code optimization in your company to cut costs by 40-60% depending on where you are and where you start with Unravel.
Speaker
Eric Chu
With nearly two decades of research and development experience in performance and cost optimization for data systems, Eric is part of the founding team and the VP of Product at Unravel Data. He brings deep expertise in compute, queries, storage, and infrastructure optimization that powers FinOps on modern data platforms.