SAPS comprises 5 components (a Dashboard, a submission dispatcher, a scheduler and an archiver). The user interacts with the system through the Dashboard, a web-based GUI that serves as a front-end to the Submission Dispatcher. After successfully logging in, the user can specify the region, the period that he/she wants to process, as well as the Energy Balance algorithm to be used. The execution consists of three-stages: input download, input preprocessing, and algorithm execution. With this data, the Dashboard creates the processing requests of each single scene and submits them to the Submission Dispatcher, which creates a task associated with the request in the Service Catalogue database (PostgreSQL).
The users can access the production instance by registering in the SAPS VO through the link https://operations-portal.egi.eu/vo/view/voname/saps-vo.i3m.upv.es. Additionally, a user can automatically deploy its own instance, which is configured and managed by EC3. All the SAPS components run on a K8s cluster, and the only component that needs to run in the front machine is the Dashboard, so it can be exposed using the public IP of the front to the users.
Addressing target audiences and expressing needs
- Collaboration
We are looking for two types of targets:
- Representative users to create products that could be consumed by third parties. SAPS enables producing vegetation index maps that could be used for other researchers. This will increase the relevance and interest of the service and the data host there.
- Developers of vegetation index computational tools that could be integrated in the system to enrich the catalogue of algorithms that could be applied through the service.
- Research and Technology Organisations
R&D, Technology and Innovation aspects
Currently, the service is available in production. We would like to increase the number of users to extend the validation of the service and reach the TRL8.
The service will be improved with additional support to external storage services for long-term preservation of the products.
The production instance is supported through an external grant. However, the service can easily be deployed on premises. The support of the EGI Federated Cloud Compute service would facilitate the adoption by users who already have resources there. Other users can deploy even in public clouds.
The business models for the scalability can be developed through the development and adoption of new algorithms that could be used for computing additional products. Also, the publication of results could lead to opportunities to request further grants and additional opportunities.
The model could be extended to support other types of algorithms. The architecture and provision mode will remain the same.
