Operationalizing Code Optimization

Operationalizing Code Optimization to Improve Cost, Performance, and Reliability of Your Cloud and AI Workloads

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.

What You'll Learn

• 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

Learn more about Unravel Data
Website: https://www.unraveldata.com/
Book a live demo: https://www.unraveldata.com/demo/