Hands-on introduction to cloud computing and its applications. Cloud computing services and infrastructures (virtualization, data center networking, wide-area storage/replication, distributed file systems), development tools, fundamental tradeoffs and algorithms (CAP theorem, NoSQL systems) and applications (big-data analysis, real-time data systems, large-scale web-services). Hands-on exploration of using cloud services (via Google Cloud Computing) and a term project that includes programming to develop applications with backend components running on the cloud.
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Introduction to Cloud Computing IaaS, PaaS, SaaS and examples from enterprise for each Virtualization techniques (VMs vs Containers, KVM, HyperV, etc) Cloud compute management (Docker, Kubernetes) Cloud Networking (VM to VM comm, VIPs, VPNs, NFVs, Load Balancing, etc) Data Centers and Datacenter Networks + Midterm Cloud Storage - CAP Theorem; Replication; Distributed File Systems; Structured and unstructured storage Cloud Storage - SQL/NoSQL databases Cloud Security Cloud Endpoints - APIs, Pubsub Applications: Introduction to mobile applications Applications: Introduction to big data managed services in the cloud Applications: Introduction to machine learning in the cloud Student Project Presentations and Demos ECTS - Workload Table: Activities Number Hours Workload Individual or group work 14 1 14 Final exam 1 2 2 Homework 5 10 50 Preparation for Midterm exam 1 10 10 Midterm exam 1 2 2 Preparation for Final exam 1 15 15 Course hours 14 3 42 Project (including preparation and presentation if applicable) 1 20 20 Total Workload: 155 Total Workload / 30: 155 / 30 5.17 ECTS Credits of the Course: 5 Type of Course: Lecture - Project Teaching Methods: Lecture - Exercises - Assignment - Project