Cloud Security

Cloud Security#

Table of Contents#

Resources#

Courses

  • [ h ] Birman, Ken. (2021). CS5412: Topics in Cloud Computing: Using the Cloud to Create Smart IoT Systems.

  • [ h ] Birman, Ken. (2014). CS5412: Cloud Computing.

YouTube#

My Lesson

  • [ y ] 02-21-2021. “Cloud Networking Full Course”.

Texts#

  • Armitage, Josh. (2022). Cloud Native Security Cookbook: Recipes for a Secure Cloud. O’Reilly.

  • Degioanni, Loris & Leonardo Grasso. (2022). Practical Cloud Native Security with Falco: Risk and Threat Detection for Containers, Kubernetes, and Cloud. O’Reilly.

  • Dotson, Chris. (2019). Practical Cloud Security: A Guide for Secure Design and Deployment. O’Reilly.

  • [ h ][ g ] Peterson, Larry L. et al. (2022). Edge Cloud Operations: A Systems Approach. Systems Approach.

  • Ruecker, Bernd. (2021). Practical Process Automation: Orchestration and Integration in Microservices and Cloud Native Architectures. O’Reilly.

  • Zikopoulos, Paul et al. (2021). Cloud Without Compromise: Hybrid Cloud for the Enterprise. O’Reilly.

  • Alipourfard, Omid et al. (2017). “CherryPick: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics”.

  • Baarzi, Ataollah Fatahi, Timothy Zhu, & Bhuvan Urgaonkar. (2019). “BurScale: Using Burstable Instances for Cost-Effective Autoscaling in the Public Cloud”.

  • Barham, Paul et al. (2003). “Xen and the Art of Virtualization”.

  • Berger et al. (2018). “RobinHood: Tail Latency Aware Caching–Dynamic Reallocation from Cache-Rich to Cache-Poor”.

  • Berger, Daniel S., Ramesh K. Sitaraman, & Mor Harchol-Balter. (2017). “AdaptSize: Orchestrating the Hot Object Memory Cache in a Content Delivery Network”.

  • Cano, Ignacio, Srinivas Aiyar, & Arvind Krishnamurthy. (2016). “Characterizing Private Clouds: A Large-Scale Empirical Analysis of Enterprise Clusters”.

  • Dalton, Michael et al. (2018). “Andromeda: Performance, Isolation, and Velocity at Scale in Cloud Network Virtualization”.

  • DeCandia, Giuseppe et al. (2007). “Dynamo: Amazon’s highly Available Key-Value Store”.

  • Delgado, Pamela. (2016). “Job-aware Scheduling in Eagle: Divide and Stick to Your Probes”.

  • Gandhi, Anshul et al. (2012). “AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers”.

  • Gog, Ionel et al. (2016). “Firmament: Fast, Centralized Cluster Scheduling at Scale”.

  • Hafeez, Ubaid Ullah, Muhammad Wajahat, & Anshul Gandhi. (2018). “ElMem: Towards an Elastic Memcached System”.

  • Hunt, Tyler et al. (2016). “Ryoan: A Distributed Sandbox for Untrusted Computation on Secret Data”.

  • Kakivaya, Gopal et al. (2018). “Service Fabric: A Distributed Platform for Building Microservices in the Cloud”.

  • Ousterhout, Kay et al. (2013). “Sparrow: Distributed, Low Latency Scheduling”.

  • Sharma, Prateek et al. (2016). “Containers and Virtual Machines at Scale: A Comparative Study”.

  • Shen, Zhiming et al. (2017). “Supercloud: A Library Cloud for Exploiting Cloud Diversity”.

  • Sigelman, Benjamin H. et al. (2010). “Dapper, a Large-Scale Distributed Systems Tracing Infrastructure”.

  • Tan, Cheng et al. (2017). “The Efficient Server Audit Problem, Deduplicated Re-execution, and the Web”.

  • Tumanov, Alexey et al. (2016). “TetriSched: global rescheduling with adaptive plan-ahead in dynamic heterogeneous clusters”.

  • Veeraraghavan, Kaushik et al. (2018). “Maelstrom: Mitigating Datacenter-level Disasters by Draining Interdependent Traffic Safely and Efficiently”.

  • Wang, Cheng et al. (2017). “Using Burstable Instances in the Public Cloud: Why, When, and How?”.

  • Wang, Liang et al. (2018). “Peeking Behind the Curtains of Serverless Platforms”.

  • Weil, Sage A. et al. (2006). “Ceph: A Scalable, High-Performance Distributed File System”.

  • Yadwadkar, Neeraja J. et al. (2017). “Selecting the Best VM across Multiple Public Clouds: A Data-Driven Performance Modeling Approach”.

  • Yan, Ying et al. (2016). “TR-Spark: Transient Computing for Big Data Analytics”.

  • Zhang, Qi et al. (2018). “A Comparative Study of Containers and Virtual Machines in Big Data Environment”.

  • Zhu, Timothy, Michael A. Kozuch, & Mor Harchol-Balter. (2017). “WorkloadCompactor: Reducing datacenter cost while providing tail latency SLO guarantees”.

Terms#

  • [ w ] Anything as a Service (XaaS)

  • [ w ] Data as a Service (DaaS)

  • [ w ] Desktop as a Service (DaaS)

  • [ w ] Function as a Service (FaaS)

  • [ w ] Infrastructure as a Service (IaaS)

  • [ w ] Mobile Backend as a Service (MBaaS)

  • [ w ] Network as a Service (NaaS)

  • [ w ] Platform as a Service (PaaS)

  • [ w ] Software as a Service (SaaS)

Contents