Our main goal 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).
We will create the first FaaS compute run-time for Big Data analytics leveraging Apache OpenWhisk, a mature open source serverless platform.
We will create Distributed Mutable Data Structures leveraging RedHat Infinispan In-Memory Data Grid. Our middleware will provide language-level constructs for data persistence, dependability and concurrency control to serverless functions.
Serverless Cloud Programming Abstractions that can express a wide range of existing data-intensive applications with minimal changes. We will develop new tools and methodologies to port existing data-intensive applications from the HPC, data analytics and machine learning domains to the CloudButton toolkit.
Serverless technologies can overcome scaling limitations of research centres computational resources, improving the scalability and productivity when processing large datasets.
Expand the analysis of metabolomics raw data and boost external access and efficient re-use of open data.
Conduct geospatial analyses in order to increase productivity, scalability and performance of relevant environmental applications using open access LiDAR and satellite data.
The CloudButton consortium is a well-balanced team of industrial and academic partners:
CloudButton contributes to Big Data Value Public-Private Partnership activities: