Many commodity trading firms still depend on legacy C# .NET systems that were built years ago. These platforms are deeply embedded in trading operations, handling everything from deal capture to settlements. Despite their age, they continue to run because of their reliability and the difficulty of replacing them.

However, reliance on legacy systems creates challenges. They are harder to integrate with modern platforms like Databricks and Snowflake, they limit the adoption of cloud-native approaches in Azure and Kubernetes, and they require scarce skills to maintain. As markets evolve, firms that remain locked into these systems risk falling behind competitors who can innovate more quickly.

Modernization does not always mean replacing everything at once. CIOs can begin by building APIs that extend the functionality of .NET applications, allowing them to connect with modern services. Python can be used for data processing and machine learning, while Databricks provides a scalable environment for analytics. Snowflake ensures governed storage and reporting, while Kubernetes manages containerized services alongside legacy systems.

Staff augmentation plays a key role in this process. External .NET engineers can stabilize legacy platforms, while specialists in Python, Databricks, and Snowflake build new layers of functionality. This blended approach allows firms to innovate without disrupting day-to-day trading operations.

The path forward is hybrid. Legacy .NET systems remain in place where they add value, while modernization layers bring new speed and flexibility. By leveraging staff augmentation, CIOs can modernize incrementally, reduce risks, and prepare their firms for a future where agility and scalability define success.