Module 3 Flashcards
(8 cards)
Explain the public, private and hybrid clouds with neat diagram
- Public Cloud (3 Marks)
A public cloud is a computing environment where services are delivered over the Internet and available to the general public. These clouds are owned and operated by third-party service providers like Amazon Web Services (AWS), Microsoft Azure, Google App Engine, etc.
Key Features:
Accessible by anyone who subscribes to or pays for the service.
Offers services like Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS).
High scalability and cost-effective due to pay-per-use model.
Examples: AWS, Azure, Google Cloud.
Advantages: Low capital expenditure, high scalability, accessibility from anywhere.
Disadvantages: Limited control, data security concerns.
- Private Cloud (3 Marks)
A private cloud is built and operated exclusively for a single organization. It provides greater control over data, security, and compliance.
Key Features:
Deployed within an organization’s intranet or hosted privately.
Managed either internally or by a third party.
Customized hardware and software to meet specific needs.
Advantages: High security, greater control, customization.
Disadvantages: Higher cost, limited scalability compared to public clouds.
Example: IBM’s Research Compute Cloud (RC2)
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- Hybrid Cloud (2 Marks)
A hybrid cloud combines public and private clouds to leverage the benefits of both. It allows data and applications to be shared between them, offering greater flexibility and deployment options.
Key Features:
Uses public cloud for non-sensitive operations while keeping sensitive operations in private cloud.
Ideal for businesses that require both scalability and privacy.
Advantages: Flexible, cost-efficient, scalable, and secure.
Example: A company may use AWS for general workloads and an on-premises private cloud for financial records.
- Explain the issues of data-Centre management issues.
Effective data-center management is vital for ensuring the reliability, scalability, and cost-efficiency of cloud computing infrastructures. Modern data centers host thousands of servers and handle massive volumes of data, making their management both a technical and economic challenge.
- User Satisfaction and Service Quality (1 Mark)
A data center must be capable of delivering quality service to users for extended periods—ideally 30 years. This includes maintaining high performance and ensuring minimal service interruptions, which is critical for user retention and trust. - Controlled Information Flow and High Availability (1 Mark)
Managing the flow of information within a data center requires structured communication paths and real-time monitoring to maintain high availability (HA). Sustained and uninterrupted service delivery is the primary goal, especially for mission-critical applications. - Multi-user Manageability (1 Mark)
A data center must support simultaneous multi-user access and operations. This involves traffic control, database management, software updates, and hardware maintenance without impacting performance or availability. - Scalability (1.5 Marks)
As workloads grow, data centers must be able to scale up their resources—including storage, processing, I/O capabilities, power supply, and cooling systems—to meet increasing demands. This scalability must be seamless and efficient to avoid performance bottlenecks. - Reliability and Virtualization Support (1.5 Marks)
To maintain reliability, data centers implement virtualization strategies like VM (Virtual Machine) live migration, fault tolerance, and failover mechanisms. These ensure that applications can recover from failures or disasters without data loss or significant downtime. - Cost Efficiency (1 Mark)
Operational costs must be kept low for both providers and users. This includes minimizing expenses related to power consumption, cooling, hardware, software, and administrative tasks. Optimization techniques like server consolidation and energy-efficient hardware are employed. - Security and Data Protection (1.5 Marks)
Security is a critical management issue. Mechanisms must be in place to protect data from unauthorized access, malware, and network-based attacks. Measures include firewalls, intrusion detection systems, encryption, and access control policies to ensure data integrity and confidentiality. - Green Computing and Energy Efficiency (1.5 Marks)
With environmental concerns and rising energy costs, data centers are expected to implement green computing strategies. These include the use of energy-efficient hardware, dynamic power management, and improved cooling technologies to reduce carbon footprints and operational costs.
Conclusion:
The management of data centers involves a holistic approach that balances user satisfaction, operational efficiency, data security, scalability, and sustainability. Addressing these issues ensures that data centers can reliably support modern cloud services over the long term.
- Explain IaaS, PaaS and SaaS cloud service models at different service levels
- Infrastructure as a Service (IaaS) – [3 Marks]
Definition:
IaaS provides the basic infrastructure services—compute, storage, and networking—through virtualization. Users can rent IT resources instead of purchasing and managing physical hardware.
Key Features:
Virtual machines, storage, and network resources are provisioned on-demand.
Users have control over the OS and deployed applications.
Users do not manage the underlying cloud infrastructure.
Examples:
Amazon EC2 and S3
Rackspace Cloud
GoGrid
Use Case: Ideal for system administrators and developers needing flexibility to install and manage applications and operating systems.
Figure Reference: IaaS forms the base layer in the cloud architecture stack, supporting PaaS and SaaS models above it
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- Platform as a Service (PaaS) – [3 Marks]
Definition:
PaaS provides a platform with tools and libraries to develop, test, deploy, and manage applications. It abstracts the underlying infrastructure and offers a runtime environment.
Key Features:
Includes OS, middleware, databases, and development tools.
Developers can focus solely on building applications.
Automatically handles scalability, load balancing, and failover.
Examples:
Google App Engine (GAE)
Microsoft Azure
Salesforce.com’s Force.com
Use Case: Ideal for developers who want to build applications without managing hardware or system software.
Figure Reference: PaaS sits between IaaS and SaaS, forming the platform layer that supports application development and deployment
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- Software as a Service (SaaS) – [3 Marks]
Definition:
SaaS delivers fully functional software applications over the Internet. Users access the software via web browsers without worrying about hardware, OS, or platform management.
Key Features:
Applications are hosted and maintained by the provider.
Multi-tenant architecture.
On-demand access and subscription-based billing.
Examples:
Gmail, Google Docs
Microsoft Office 365
Salesforce CRM
Use Case: Best suited for end-users needing ready-to-use applications for tasks like communication, CRM, and document processing.
Figure Reference: SaaS forms the topmost layer in the cloud stack, accessible via client interfaces or web browsers
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- Explain hardware virtualization.
Hardware virtualization is a core technology in cloud and distributed computing that enables multiple operating systems and applications to run on the same physical hardware by abstracting and managing hardware resources through a virtualization layer. It plays a critical role in improving resource utilization, system flexibility, and fault isolation.
- Definition and Concept (2 Marks)
Hardware virtualization is the abstraction of physical hardware resources (such as CPU, memory, and I/O devices) into virtual devices by inserting a software layer called a hypervisor or Virtual Machine Monitor (VMM) between the hardware and operating system
. It allows multiple virtual machines (VMs) to run concurrently on a single physical machine. - Key Components (2 Marks)
Hypervisor (VMM): Software layer that enables virtualization by controlling access to hardware.
Type 1 Hypervisor: Bare-metal, runs directly on hardware (e.g., VMware ESX, Xen).
Type 2 Hypervisor: Runs on a host OS (e.g., VMware Workstation).
Virtual Machine (VM): An isolated guest environment with its own OS and applications.
Guest OS: The operating system that runs inside the VM.
- Hardware Support for Virtualization (2 Marks)
Modern CPUs (like Intel VT-x and AMD-V) include specific instructions and modes to support virtualization efficiently:
Intel VT-x: Adds a new mode (VMX Root Mode) and traps sensitive instructions for the VMM.
Extended Page Tables (EPT): Used for memory virtualization, translating guest virtual addresses to physical addresses.
VT-d and VT-c: Support I/O virtualization
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- Advantages of Hardware Virtualization (2 Marks)
Efficient Resource Utilization: Multiple VMs can share the same hardware.
Isolation: Each VM runs in a secure, isolated environment.
Scalability: Supports dynamic provisioning of resources.
Fault Tolerance: Failures in one VM do not affect others.
- Explain a generic cloud architecture.
A generic cloud architecture outlines the foundational components and services necessary for a cloud computing environment. It describes how computing, storage, and networking resources are integrated, managed, and provisioned to deliver scalable and on-demand services to users.
- Definition and Purpose (1 Mark)
A generic cloud architecture represents a scalable, dynamic cluster of servers that deliver collective web services or distributed applications using data center resources. It enables Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) deployment models for public, private, and hybrid clouds
. - Cloud Platform Design Goals (2 Marks)
Key goals of a cloud platform include:
Scalability: Ability to grow resources on demand.
Virtualization: Efficient abstraction of hardware.
Efficiency: Optimal use of hardware, energy, and operations.
Reliability: Continuous service with minimal downtime
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- Core Architectural Components (4 Marks)
Client Interface Layer:
Users access the cloud through web interfaces or APIs to request services.
Cloud Service Layer (Provisioning):
Manages dynamic provisioning of compute, storage, and software resources, either on physical machines or VMs.
Virtualized Resources:
The foundation includes virtual machines, storage systems, and networks that are dynamically configured based on demand.
Data Centers:
Physical infrastructure housing thousands of servers; designed for energy efficiency, redundancy, and failover support.
Distributed Storage:
Ensures scalable and fault-tolerant storage using distributed file systems across multiple data centers.
Security and Monitoring:
Includes firewalls, trust delegation, reputation systems, and metering tools to track usage and protect resources.
5. Additional Features (1 Mark)
Automation: Software automatically manages node join/leave, resource scaling, and failure recovery.
Hybrid Deployment: Combines private and public clouds for flexibility.
APIs and Services: Cloud providers offer APIs for developers and support services such as licensing, billing, and multitenancy.
Conclusion:
A generic cloud architecture ensures on-demand resource delivery through virtualization, automation, and distributed data centers. It supports a broad range of applications from web hosting to large-scale analytics, and forms the foundation for modern cloud service providers.
- Explain VM creation and management.
Virtual Machine (VM) creation and management are core components of cloud infrastructure that allow efficient resource provisioning, workload distribution, and service delivery. A VM abstracts the hardware resources of a physical system and provides an isolated execution environment for applications and services.
- Definition and Importance (1 Mark)
VM creation involves setting up a virtual instance with a defined configuration (CPU, memory, storage, OS), while VM management includes monitoring, controlling, migrating, and terminating virtual instances as per workload and resource availability. It enables flexibility, scalability, and fault isolation in cloud computing. - VM Creation Process (2 Marks)
The process starts with selecting or defining a VM template (OS type, number of CPU cores, memory size). These templates are used to instantiate VMs on cloud platforms using VM management software or APIs.
Example templates:
Ubuntu: 1 core, 128 MB RAM
Fedora: 2 cores, 256 MB RAM
OpenSUSE: 1 core, 512 MB RAM
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Steps:
Choose a template and convert it to the virtual infrastructure engine format.
Submit the template via a VM manager (e.g., OpenNebula).
The VM is instantiated on a physical host.
VMs can be shut down, migrated, or restarted using API commands.
- VM Management Tools and APIs (2 Marks)
Cloud platforms use VM managers (like OpenNebula, VMware vSphere, or Eucalyptus) to manage VMs. These managers:
Provide public APIs for submission and control.
Support scheduling and monitoring of VM states.
Enable live migration to balance load or recover from failure.
Example command:
makefile
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vmInstance = vmms.submit(vmTemplate, host)
vmInstance.shutdown()
These APIs allow automated control of VM lifecycle from creation to de-provisioning
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- Key Operations in VM Management (2 Marks)
Provisioning: Allocate physical resources to the VM.
Monitoring: Track performance metrics like CPU usage, memory, I/O.
Migration: Move VMs across physical hosts with minimal downtime.
Scaling: Clone or adjust VM resources based on demand.
Termination: Release resources when a VM is no longer needed.
- Architecture of VM Management (2 Marks)
Referencing Figure 4.27 from the textbook, a VM management system involves interactions among:
VM manager service
Public APIs
Templates
Host infrastructure
pgsql
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User/API → VM Manager → VM Deployment on Host
This setup ensures VMs are consistently managed across platforms such as Amazon EC2 and Grid’5000
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- Benefits of Effective VM Management (1 Mark)
Resource optimization
Reduced operational cost
Increased service reliability
Automated recovery and fault tolerance
Conclusion:
VM creation and management form the backbone of cloud services, enabling dynamic and efficient use of physical resources. Through templates, public APIs, and robust VM managers, cloud providers ensure scalability, flexibility, and reliability in service delivery.
- Explain public cloud platforms in brief in brief with neat diagram. (at least write 8 points for each platform).
Public cloud platforms provide computing resources such as servers, storage, and services over the internet, accessible to users on a pay-per-use or subscription model. Three major public cloud platforms include Google App Engine (GAE), Amazon Web Services (AWS), and Microsoft Azure. Each offers unique features under the IaaS, PaaS, and SaaS models.
- Google App Engine (GAE) – [3 Marks]
GAE is a Platform as a Service (PaaS) offered by Google that enables developers to build and host web applications in Google-managed data centers.
Key Features:
Supports Python and Java for application development.
BigTable is used as the distributed database system.
GFS (Google File System) stores large-scale data.
MapReduce handles distributed data processing.
Chubby provides distributed lock services.
Offers automatic scaling and load balancing.
Comes with a software development kit (SDK) for local development and testing.
Applications are deployed in Google’s globally distributed data centers
.2. Amazon Web Services (AWS) – [3 Marks]
AWS is the leading Infrastructure as a Service (IaaS) provider that offers a wide array of services for computing, storage, and networking.
Key Features:
EC2 (Elastic Compute Cloud) for scalable VM instances.
S3 (Simple Storage Service) for object-based storage.
EBS (Elastic Block Store) for block-level storage.
SQS (Simple Queue Service) enables reliable message queuing.
CloudWatch monitors VM and resource usage.
Elastic Load Balancing (ELB) distributes workloads.
Elastic MapReduce supports big data analytics using Hadoop.
RDS (Relational Database Service) offers managed databases
3. Microsoft Windows Azure – [3 Marks]
Azure is a hybrid cloud platform that provides IaaS, PaaS, and SaaS services over Microsoft-managed data centers.
Key Features:
Built on Windows OS and Microsoft’s virtualization technology.
Azure Portal provides a GUI for management.
.NET Services allow application execution in the cloud.
SQL Azure offers cloud-based relational database.
Azure Blob, Table, and Queue Storage for scalable data handling.
Dynamic CRM and SharePoint for business solutions.
Live services for real-time collaboration.
Offers a powerful SDK for development and debugging
- List and explain cloud design objectives.
Cloud design objectives guide the development and implementation of cloud computing platforms to meet user demands for scalability, reliability, and cost-efficiency. These objectives aim to enhance the usability, security, and interoperability of cloud services across diverse environments and users.
- Shifting Computing from Desktops to Data Centers (1.5 Marks)
One of the primary objectives is to centralize computing by moving processing, storage, and software delivery from individual desktops and local servers to centralized data centers. This transition allows better resource sharing, easier maintenance, and streamlined software updates
. - Service Provisioning and Cloud Economics (1.5 Marks)
Cloud services are provided under Service Level Agreements (SLAs), ensuring reliability and performance. The economic model is based on pay-as-you-go, reducing upfront costs and optimizing operational expenses. Efficient service delivery is expected in terms of computing, storage, and power consumption
. - Scalability in Performance (1.5 Marks)
Cloud platforms must scale horizontally and vertically to handle varying workloads. As the number of users or tasks increases, the system must maintain performance by dynamically allocating resources without affecting user experience
. - Data Privacy Protection (1.5 Marks)
Trust in cloud services depends on robust mechanisms to secure user data. Clouds must ensure privacy, confidentiality, and integrity through encryption, access control, and compliance with legal regulations such as data residency and GDPR
. - High Quality of Cloud Services (1.5 Marks)
To ensure user satisfaction and platform adoption, cloud services must offer high Quality of Service (QoS). Parameters like availability, reliability, performance, and response time should be standardized to facilitate service interoperability among different providers
. - New Standards and Interfaces (1.5 Marks)
Standardization is essential to prevent vendor lock-in. Cloud platforms must adopt universally accepted APIs and protocols for application portability and seamless data migration across providers. This ensures flexibility and future-proofing for businesses
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Conclusion:
The success of cloud computing hinges on meeting these design objectives which address technical scalability, economic viability, and user trust. By aligning with these goals, cloud platforms ensure long-term usability, adaptability, and acceptance in the computing industry.
