Infrastructure optimizations like rightsizing and auto-suspending idle resources are standard practice, but they cannot fix the cost and performance issues caused by inefficient code.
Unoptimized workloads and AI functions waste compute, lead to missed SLAs, and inflate cloud spend. Even with AI coding assistants, operationalizing code optimization at scale is tough. It takes deep domain expertise, pre-deployment testing, and getting past the fear of breaking production pipelines.
See how Arvix automates root-cause analysis, suggests and verifies code rewrites, and integrates with your CI/CD workflow to cut costs by 40 to 60%. Watch now.
In this 20-minute session, VP of Product Eric Chu will guide you through:
- Real customer impact: See the results of code optimization in Databricks, Snowflake, and BigQuery.
- Common code inefficiencies: Learn the types of inefficient code that drive up cost and slow down workloads.
- The limits of general-purpose LLMs: Discover why relying on engineers to optimize code with general-purpose LLMs falls short.
- Code optimization, operationalized: See how Arvix automates root-cause analysis and mitigation, verifies code rewrites, and plugs into your CI/CD and notification framework.
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