Introduction

The mission of DODAS is to act as a cloud enabler for scientists seeking to easily exploit distributed and heterogeneous clouds to process, manipulate or generate data. Aiming to reduce the learning curve, as well as the operational cost of managing community specific services running on distributed cloud, DODAS completely automates the process of provisioning, creating, managing and accessing a pool of heterogeneous computing and storage resources.
Within the EOSC-hub project DODAS - Thematic Service is providing both the PaaS core services and an Enabling Facility (Cloud@CNAF and Cloud@ReCaS-Bari). Although DODAS PaaS core layer can be used to exploit any cloud, we foresee that a user might benefit of a freely accessible Enabling Facility where to test a customisation and/or simply try out how DODAS behaves etc.
This guide provides not only an overview of the architecture and basic concepts behind DODAS, but also a comprehensive documentation for users willing to instantiate currently supported services:

• HTCondor batch system as a Service
• Big Data platform for ML as a Service

either using the DODAS provided Enabling Facility or a user provided public Cloud as well as a private Cloud (Amazon, Microsoft Azure, Open Telekom Cloud, etc).
Moreover this guide provides the reader guidelines on how to customise and extend the DODAS workflow. However, if you feel you are an impatient user, this is the section you are looking for.

DODAS has been integrated by the Submission Infrastructure of Compact Muon Solenoid (CMS), one of the two bigger and general purposes experiments at LHC of CERN, as well as by the Alpha Magnetic Spectrometer (AMS-02) computing environment.