Modern large-scale datacenters require the seamless integration of different components - applications, computation nodes, storage devices, and networks - into one computing infrastructure. The course covers the basics of current datacenters architectures, ranging from the analysis of the single components to the global infrastructure. The focus is on the foundations required to understand the design of computing infrastructures that are scalable, available, secure and flexible at the same time. Virtualization, container-based technology, cloud computing and storage systems are analyzed in depth to show how they can be used to support challenging tasks such as machine-learning applications and high-performance computing.

Students will learn how to:
• analyze and discuss on the trade-offs between reliability, performance and costs of different hardware and software technologies
• Identify the basic elements that are part of a scalable Datacenter
• discuss the role of virtualization and software technologies that are the base of cloud systems.
• explain the main computing architectures and service models used in complex computing systems

At the end of the course, students will be able to:
• design both computational and storage components of a data center, to satisfy specific service-level requirements
• extend performance and reliability analysis to other types of components in a data center
• apply performance and reliability analysis to other complex systems, even outside the computer engineering domain

Exercises to apply the knowledge in simple examples or to more complicated scenarios will be used especially considering the parts related to reliability, storage system design, and performance analysis.  

Basic notions of computer architecture and probability.

The evaluation consists of a written exam on the topics covered in the course. The exam will include both theoretical questions and numerical problems.
More in detail the written exam includes:
• Close-ended questions on course topics to verify the capacity to recognize the basic concept behind the design of a large scale computing infrastructure;
• Open-ended theoretical questions on course topics to verify the capacity to describe the key concepts related to the design of a large scale computing infrastructure;
• Numerical problem resolutions regarding analysis and design of datacenter and datacenter components, virtualization, storage systems, dependability, and performance modeling.

An oral test could be requested by the lecturer to deepen specific questions of the written test and further verify the capacity of the student to describe the key concepts related to the design of a large scale computing infrastructure and develop links between the various topics of the course

(Open Access Book) (chapters 1-4)