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CloudButton: Serverless Data Analytics Platform

Research Area: Cloud Computing CloudButton: Serverless Data Analytics Platform
Status: Finished  
Project leaders: Collaborators:
Proposed start date: 2019-01-01 Proposed end date: 2021-12-31
Funded by: European Union    
Project page:

Ref. H2020-825184

The main goal of this project is to create CloudButton: a Serverless Data Analytics Platform. CloudButton will democratize big data by overly simplifying the overall life cycle and programming model thanks to serverless technologies. To demonstrate the impact of the project, we target two settings with large data volumes: bioinformatics (genomics, metabolomics) and geospatial data (LiDAR, satellital).

In order to achieve such ambitious objectives, the CloudButton project defines the following goals:

1. Create a High Performance Serverless Compute Engine for Big Data: This is the foundational technology for the CloudButton platform that must overcome the current limitations of existing serverless platforms. In particular, it includes extensions to i) support stateful and highly performant execution of serverless tasks, ii) optimized elasticity  and operations management of functions  thanks to new locality aware scheduling algorithms, iii) efficient QoS management of containers that host serverless functions, and iv) a Serverless Execution Framework supporting typical dataflow models.

2. Support for Mutable Shared Data in Serverless Computing: To simplify the transitioning from sequential to (massively-)parallel code, we will design of a new middleware that allows to quickly spawn and share mutable data structures in a serverless computing platform. Our Mutable Shared Data middleware will i) offer an easy-to-use programming framework to add state to serverless computing, ii) provide dynamic data replication and tunable consistency to match the performance requirements of serverless data analytics, and iii) integrate this framework to an in-memory data grids for performance.

3. Design novel Serverless Cloud Programming Abstractions: The overall objective of this work package is to provide a new programming model for serverless cloud infrastructures that can express a wide range of existing data-intensive applications with minimal changes. The programming model should at the same time, i) preserve the benefits of a serverless execution model in terms of resource efficiency, performance, scalability and fault tolerance, ii) explicit support for stateful functions in applications, while offering guarantees with respect to the consistency and durability of the state.

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