The INFN Cloud services are based on modular components and span the IaaS, PaaS and SaaS models for both computing and data. ​

  • All services are described by TOSCA templates (which can refer internally to other components such as Ansible playbooks, HELM charts, etc.).​
  • The services can be deployed via the INFN Cloud Dashboard or via a command line interface:​
    • Automatically by the INFN Cloud Orchestrator on one of the federated Cloud infrastructures, depending on resource availability and policies.​
    • Manually by a user on a specific federated Cloud infrastructure.

Service Catalog

Login

Compute Services
A list of services that enable a specific cloud technology
Analytics
A collection of ad-hoc solutions for analytic purpose
Machine Learning
List of ready-to-go Machine Learning services
Data Services
Data management and storage services

Virtual Machine
Launch a compute node getting the IP and SSH credentials to access via ssh

Docker-compose
Run a docker compose file fetched from the specified URL

Image

Apache Mesos cluster
Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual)

Image

Kubernetes cluster
Deploy a single master Kubernetes 1.17.0 cluster

Cloud Storage Service
The INFN-Cloud Cloud Storage Service is based on the popular ownCloud storage solution.

Image

Galaxy
Deploy Galaxy docker image on a single Virtual Machine.

Image Image

Elasticsearch and Kibana
Deploy a virtual machine pre-configured with the Elasticsearch search and analytics engine and with Kibana for simple visualization

Image

Spark + Jupyter cluster
Deploy a complete Spark 3.0.1 + Jupyter Notebook on top of a Kubernetes (K8s) computing cluster

Image

Jupyter with persistence for Notebooks
Run Jupyter on a single VM enabling Notebooks persistence

Image

RStudio
RStudio is an integrated development environment (IDE) for R.

Image Image

TensorFlow with Jupyter
Run an instance of Tensorflow with GPU

Image

Jupyter with persistence for Notebooks
Run Jupyter on a single VM enabling Notebooks persistence

Image

Working Station for Machine Learning INFN (ML_INFN)
Run a single VM with all the ML-INFN envirnoment exposing both ssh access and Jupyter

Work in progress

Image

Working Station for CYGNO experiment
Run a single VM with all the CYGNO envirnoment exposing both ssh access and Jupyter