Leveraging OpenFunction & Dapr to archive automotive data

UISEE is a leading autonomous vehicle company in China that provides driverless services across various industries and use cases. The organization faced significant challenges managing massive volumes of automotive data with diverse storage requirements.

Challenge

Data archiving is essential for all online business systems, including autonomous vehicle operations. UISEE's cloud platform, built on Kubernetes, needed to manage and process automotive data more sophisticatedly.

The platform required a solution addressing storage requirements for diverse data types, varying data sizes across different time periods, combination of sync and async function calls for different tasks, and complete observability of business operations.

"The scenarios of autonomous driving are complex. For example, we've separate modules for object detection, environment perception, and route planning. Each module generates data of all types. Moreover, the amount of data generated fluctuates at different times of the day." — Haili Zhang, Director of R&D, UISEE

Solution

UISEE implemented OpenFunction for data archiving, leveraging its support for both synchronous and asynchronous functions alongside a cloud-agnostic architecture that simplifies Backend-as-a-Service (BaaS) integration.

By introducing Knative and the Distributed Application Runtime (Dapr), OpenFunction enabled runtime environments for both synchronous and asynchronous functions.

"Basically, we use OpenFunction to run sync and async workloads. This means, we can make sync function calls to distribute tasks and async function calls to perform read/write operations on storage and return execution results." — Haili Zhang, Director of R&D, UISEE

Impact

"By using OpenFunction, our workflows for task distribution and data archiving have become more flexible, and our R&D personnel can better focus on the business logic instead of the underlying infrastructure. As a result, we managed to reduce the amount of boilerplate code and develop agile applications that can automatically scale." — Haili Zhang, Director of R&D, UISEE

The new system enables technical personnel specializing in different modules to write functions in their language of choice, embracing diverse languages and frameworks.

The full case study is available on the CNCF website.