Lambda architecture has gained popularity recently as an organizing framework for synthesizing data processing and analysis. However, it has limitations. In this white paper we demonstrate how – with the addition of a single processing layer – lambda architecture can be generalized and extended for continuous decisioning, providing the same benefits of batch- and stream-processing that standard lambda architecture provides to real-time analytics, as well as providing a continuous feedback mechanism relevant for all applications.

Co-authors

    

Co-Authors: Nick Weir and Rich Johnson, LigaData

Table of Contents

• Introduction
• Sample Use Case: Real-Time Automated Bank Communications
• Lambda Architecture for Continuous Decisioning
• Implementing the Decisioning Layer with Kamanja
• The Kamanja Community
• References