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Questions and Answers
What are the primary types of clouds in cloud computing?
What are the primary types of clouds in cloud computing?
The primary types of clouds are public, private, hybrid, and community clouds.
Explain the role of virtualization in cloud computing.
Explain the role of virtualization in cloud computing.
Virtualization allows the creation of virtual versions of physical resources, such as servers and networks, enabling better resource utilization and scalability.
What is the difference between a Type 1 and Type 2 hypervisor?
What is the difference between a Type 1 and Type 2 hypervisor?
A Type 1 hypervisor runs directly on the host's hardware, while a Type 2 hypervisor runs on a host operating system.
Identify two major risks associated with migrating to the cloud.
Identify two major risks associated with migrating to the cloud.
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Define what constitutes a Service Level Agreement (SLA).
Define what constitutes a Service Level Agreement (SLA).
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Describe the importance of energy efficiency in data centers.
Describe the importance of energy efficiency in data centers.
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What is the purpose of elastic load balancing in cloud environments?
What is the purpose of elastic load balancing in cloud environments?
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Explain the concept of Byzantine failure in distributed systems.
Explain the concept of Byzantine failure in distributed systems.
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What techniques are commonly used for big data processing in cloud computing?
What techniques are commonly used for big data processing in cloud computing?
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What is storage virtualization, and why is it important in cloud computing?
What is storage virtualization, and why is it important in cloud computing?
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Study Notes
Introduction to Cloud Computing
- Cloud Computing: On-demand access to computing resources, such as servers, databases, storage, networking, software, and analytics.
- Types of Clouds: Public, Private, Hybrid, Community.
- Cloud Service Models: SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service).
- Deployment Models: Public, Private, Community, Hybrid.
Cloud Computing Architecture & Infrastructure
- Cloud Reference Model: NIST (National Institute of Standards and Technology) Cloud Computing Reference Architecture.
- Virtualization: Technology that allows multiple operating systems to run on a single physical server.
- Types of Virtualizations: Compute, Network, Storage.
Types of Hypervisors
- Type 1 Hypervisors: Directly run on top of the physical hardware.
- Type 2 Hypervisors: Run on top of an existing operating system.
Cloud Platforms in Industry
- Major cloud vendors: Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP).
- Integration of Private and Public Clouds: Combining private and public cloud environments for optimal flexibility and cost-effectiveness.
Cloud Applications
- Common applications: Protein structure prediction, data analysis, satellite image processing, CRM and ERP, social networking, scientific applications, business applications.
Advance Topics in Cloud Computing
- Cloud Security: Protecting data and applications in the cloud, including data encryption, access control, and security monitoring.
- Risks and Approaches of Migration into Cloud: Identifying risks associated with cloud migration and implementing strategies for a smooth transition.
Federated Cloud/Intercloud, Third Party Cloud Services, Business Continuity and Disaster Recovery
- Federated Cloud/Intercloud: A collaboration between multiple cloud providers for a single unified cloud service.
- Third Party Cloud Services: Cloud-based services provided by a third-party vendor, such as email, storage, or collaboration tools.
- Business Continuity and Disaster Recovery: Planning and implementing strategies to ensure business operations are not disrupted by outages or disasters.
Service Level Agreement (SLA), Dynamic resource provisioning and management
- Service Level Agreement (SLA): A contract defining the level of service that a cloud provider will deliver.
- Dynamic resource provisioning and management: Automatically adjusting resources based on demand, ensuring optimal performance and cost efficiency.
Server Consolidation and Placement policies, Energy efficiency in data centers, Elastic Load Balancing and Auto Scaling.
- Server Consolidation: Reducing the number of physical servers by utilizing virtualization technologies.
- Placement policies: Algorithms for efficiently allocating workloads to physical servers.
- Energy efficiency in data centers: Implementing energy-saving measures in data centers, such as cool-air solutions and energy-efficient hardware.
- Elastic Load Balancing and Auto Scaling: Automatically distributing workloads to multiple servers and scaling resources up or down based on demand.
Storage Network Design
- Architecture of storage: Designing and implementing storage infrastructure, considering factors like capacity, performance, and security.
- Analysis and planning: Assessing storage requirements and planning for future growth.
- Storage network design considerations: Factors like data traffic, latency, and scalability.
- NAS and FC SANs: Two common storage network architectures, NAS (Network Attached Storage) and FC SAN (Fibre Channel Storage Area Network).
- Hybrid storage networking technologies: Combining different technologies for optimal performance and cost-effectiveness.
Storage virtualization in cloud computing, host system design considerations
- Storage virtualization: Abstracting physical storage resources for a unified view and centralized management.
- Host system design considerations: Designing the physical servers that host virtualized storage resources.
Techniques for Big data processing (Google GFS, BigTable, and Map-Reduce Hadoop Distributed File System (HDFS), HIVE).
- Big data processing: Processing large volumes of data efficiently and effectively.
- Google GFS, BigTable, and Map-Reduce: Technologies developed by Google for scalable data processing.
- Hadoop Distributed File System (HDFS): An open-source distributed file system for storing large data sets.
- HIVE: A data warehouse system for querying and analyzing large data sets stored in HDFS.
Consensus in Cloud Computing
- Issues in consensus: Challenges in achieving agreement among distributed nodes.
- Consensus in synchronous and asynchronous system: Different approaches for reaching consensus in synchronous and asynchronous distributed systems.
Byzantine Agreement: Agreement, Faults, Tolerance, Measuring Reliability and Performance
- Byzantine Agreement: A consensus protocol that can tolerate malicious or faulty nodes.
- Agreement, Faults, Tolerance: Key concepts related to Byzantine Agreement, including the ability to reach an agreement despite faulty nodes.
- Measuring Reliability and Performance: Evaluating the reliability and performance of consensus protocols.
SLIs, SLOs, SLAs, TLAs, Byzantine failure, Byzantine Generals Problem, Failures & Recovery Approaches in Distributed Systems, Checkpointing.
- SLIs, SLOs, SLAs, TLAs: Service Level Indicators, Objectives, Agreements, and Targets that define the expected performance and reliability of cloud services.
- Byzantine failure: A type of failure in which a node can behave arbitrarily and maliciously.
- Byzantine Generals Problem: A classic problem in distributed computing that illustrates the challenges of achieving consensus in the presence of faulty nodes.
- Failures & Recovery Approaches in Distributed Systems: Strategies for handling failures and recovering data in distributed systems.
- Checkpointing: Creating consistent snapshots of data and system state for recovery purposes.
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Description
This quiz covers the fundamentals of cloud computing, including types of clouds, cloud service models, and the architecture behind cloud solutions. Learn about virtualization techniques and the major players in the cloud industry. Test your knowledge of critical concepts such as SaaS, PaaS, and IaaS.
