This is the webpage of the course “Computer Systems” that will be held at Politecnico di Milano (Como site) from March to June 2016.
This is a 5 credits course for graduate students.
Danilo Ardagna, email@example.com
Eugenio Gianniti, firstname.lastname@example.org
Recently, new technologies have appeared that have definitely changed how internet and the web are used. Cloud computing, service computing and engineering, Hardware as a Service, Infrastructure as a Service, Platform as a Service, Software as a Service, are the basis of what is generally called “Enterprise3.0.” Scalability, reliability, availability and security are the main features that must be provided to users of these architectures. New applications, like Big data and/or data intensive applications introduce also new challenges for the management of the underlying infrastructure and can leverage effectively the adoption of service based and on demand cloud paradigms.
This course will overview a wide set of technologies, providing the rational that governs the design and operation of modern data centres and cloud based systems, introducing also new frameworks for Big data and business intelligence applications (e.g., Hadoop, Spark, Storm, etc.). Moreover, the course will provide an introduction to the fundamental laws for performance evaluation and capacity planning of modern computing infrastructures.
1. Storage Systems
1.1 Storage technologies architecture and performance – Disks (hdd, ssd)
– RAID architectures
1.2 Storage Architectures
2. Virtualization and cloud computing
2.1 Virtualization technologies
– Evolution of datacentres: mainframes, graphic workstations, UNIX servers, x86 servers, high- density blade servers, server (and storage) consolidation
– Server virtualization: basic concepts, technologies, hypervisors, hardware support,
2.2. Service and Cloud computing architectures
– Cloud computing basics concepts: IaaS, PaaS, SaaS
– Cloud data storage solutions
– DevOps: bridging the gap between development and operations teams – Lightweight VM: Docker, Vagrant
– VM change management tools: Puppet, Chef
3. Big Data Technologies
3.1 Big data and data science introduction
3.2 Big data general architecture
– Batch/interactive processing: MapReduce and Hadoop. Apache Spark – Streaming: Apache Spark Streaming, Apache Storm
– NoSQL systems
– Apache big data stack
3.3 Cloud based big data solutions
4. Performance and reliability
4.1 Performance evaluation and capacity planning introduction, scalability
4.2 Fundamental laws and Queueing network basics
– Performance indices and operational analysis
– Performance measurement (performance counters, monitoring tools), benchmarking and load testing
4.3 Reliability and availability models
4.5 Configuration, performance, scalability, and reliability of RAID and Cloud systems
The exam consists in a written test (32 points overall). Students obtaining at least 24 points can work on a project and obtain up to 4 points to improve their grade. More extended projects can be an alternative to the written test (ask instructors).