Large-scale Graph Processing and Simula...

Serverless computing offers an affordable and easy way to code lightweight functions that can be invoked based on some events to perform simple tasks. For more complicated processing, multiple serverless functions can be orchestrated as a directed acyclic graph to form a serverless workflow, so-called function choreography (FC). Although most famous cloud providers offer FC management systems such as AWS Step Functions, and there are also several open-source FC management systems (e.g., Apache OpenWhisk), their primary focus is on describing the control flow and data flow between serverless functions in the FC. Moreover, the existing FC management systems rarely consider the processed data, which is commonly represented in a graph format. In this paper, we review the capabilities of the existing FC management systems in supporting graph processing applications. We also raise two key research questions related to large-scale graph processing using serverless computing in federated Function-as-a-Service (FaaS). As part of the Graph-Massivizer project, funded by the Horizon Europe research and innovation program, we will research and develop (prototype) solutions that will address these challenges.