Dynamic Data Processing Using Serverless Java With Quarkus on AWS Lambda (Part 1)

With the growth of the application modernization demands, monolithic applications were refactored to cloud-native microservices and serverless functions with lighter, faster, and smaller application portfolios for the past years. This was not only about rewriting applications, but the backend data stores were also redesigned in terms of dynamic scalability, high performance, and flexibility for event-driven architecture. For example, traditional data structures in relational databases started to move forward to a new approach that enables to storage and retrieval of key-value and document data structures using NoSQL databases.

However, faster modernization presents more challenges for Java developers in terms of steep learning curves about new technologies adoption and retaining current skillsets with experience. For instance, Java developers need to rewrite all existing Java applications to Golang and JavaScript for new serverless functions and learn new APIs or SDKs to process dynamic data records by new modernized serverless applications.

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