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Infrastructure Stratergy > Lecture Ten - Virtualisation and Cloud Computing > Flashcards

Lecture Ten - Virtualisation and Cloud Computing Flashcards

1
Q

Moore’s Law - Principle

A

The number of transistors in an integrated circuit doubles approximately every two years

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2
Q

Moore’s Law - Implication

A

Continuous growth in computing power and efficiency, driver technological advancement

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3
Q

Servers - Definition

A

High-performance computers designed for continues operation under heavy workloads

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4
Q

Servers - Characteristics

A

Non-Specialized Hardware - Utilizes high-quality components for reliability
Service Providers - Facilitate client-server interactions by providing dedicated services.
Specialization: Servers can be dedicated to specific tasks, such as web hosting or database management

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5
Q

Data Centre Formation

A

Multiple servers can be deployed to create a robust data centre infrastructure

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6
Q

Servers vs. Computers - Memory-

A

Servers: Typically have larger RAM to support multiple users and applications.
Computers: Designed for individual use with standard memory capacities.

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7
Q

Servers vs. Computers - Storage

A

Servers: Utilize large, fast disks with RAID configurations for reliability and speed.
Computers: Use standard hard drives without advanced redundancy features.

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8
Q

Servers vs. Computers - Processing Power

A

Servers: May have multiple CPUs for enhanced performance.
Computers: Generally have single CPUs sufficient for personal tasks.

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9
Q

Servers vs. Computers - Backup

A

Servers: Feature high-capacity backup drives to prevent data loss.
Computers: Typically use external or cloud backup solutions.

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10
Q

Servers vs. Computer - Connectivity

A

Servers: Equipped with multiple network cards for increased data throughput.
Computers: Usually have a single network interface.

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11
Q

Servers vs. Computers - Robustness

A

Servers: Built with high-quality components for 24/7 operation.
Computers: Designed for standard usage patterns.

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12
Q

Servers vs. Computers - Scalability

A

Servers: Allow for expansion with additional disks, power supplies, and CPUs.
Computers: Limited upgrade capabilities.

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13
Q

Basic Server-Client Model

A

Architecture: Describes the interaction between clients and servers in a network.
Process:
Request: Client sends a service request to the server.
Processing: Server processes the request and performs the necessary operations.
Response: Server sends the results back to the client, completing the interaction.
Latency Consideration: The time taken to provide a service response is critical for performance.

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14
Q

Tiered Server-Client Model

A

Structure: Involves multiple server layers to manage complex services.
Components:
Client: Initiates requests for services.
Frontend Server: Handles client requests and interacts with backend servers.
Backend Server: Processes requests and manages data operations.

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15
Q

Server-Client Model Types

A

Centralized Model: All client applications interact with a single server or server cluster.
Distributed Model: Clients communicate with multiple servers distributed across a network.
Hybrid Model: Combines centralized and distributed approaches for enhanced flexibility and resilience.

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16
Q

Server-Client Architecture

A

Components:
Client Side: User interface and client-side logic handle user interactions and requests.
Server Side: Server-side logic processes requests, manages data, and communicates with other servers.
Communication Protocols: Define the rules for data exchange between client and server.
Interoperability: Ensures seamless interaction between different systems and platforms.

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17
Q

File Servers

A

Provide centralized storage for files accessible by multiple users.

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18
Q

FTP Servers

A

Enable file transfers over the Internet or WAN.

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19
Q

Application Servers

A

Host network-enabled applications for shard use

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20
Q

Web Servers

A

Serve web pages and content using HTTP

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21
Q

Email Servers

A

Manage email communications using protocols like SMTP, POP3, and IMAP.

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22
Q

Print Servers

A

Connect printers to networks, managing print queues and jobs

23
Q

Communications Servers

A

Handle network services like remote access and firewall management

24
Q

Database Servers

A

Store and manage databases for data-driven applications

25
Q

Proxy Services

A

Intermediate devices that handle requests for resources, providing filtering and security

26
Q

Introduction to Virtualisation

A

Origin: Concept emerged in the 1960s with time-sharing systems.
Evolution: Initially used to run legacy software on new hardware.
Purpose: Abstract physical resources to create virtual environments, improving efficiency and flexibility.
Modern Significance: Central to cloud computing and resource optimization in IT infrastructures.

27
Q

Basic Concept of Virtualisation

A

Physical Resources: Include CPU, memory, storage, and network components.
Virtual Machines (VMs): Abstracted instances running on physical machines, enabling multiple operating systems to coexist.

28
Q

Virtualisation Benefits

A

Resource Optimization: Increases hardware utilization.
Isolation: Separates environments for security and stability.
Flexibility: Allows dynamic resource allocation.

29
Q

Server Virtualisation

A

Hypervisor (VMM): Software layer enabling multiple VMs to run on a single physical server.
Types of Hypervisors:
Type-1 (Bare-Metal): Runs directly on hardware, offering high performance and security.
Type-2 (Hosted): Runs on top of an operating system, providing flexibility and ease of use.
Host/Guest Model:
Host OS: Manages hardware resources.
Guest OS: Runs within VMs, isolated from the host.

30
Q

Virtualisation Levels - Emulation

A

Software simulates hardware, allowing unmodified OSes and applications to run.

31
Q

Virtualisation Levels - Full/Native Virtualisation

A

VMs run as if they have direct access to hardware, unaware of the virtual layer.

32
Q

Virtualisation Levels - Para-Virtualisation

A

OS is aware of the virtual environment, requiring modifications for efficiency.

33
Q

Virtualisation Levels - OS-Level Virtualisation

A

Multiple user spaces share a single OS kernel, providing lightweight isolation.

34
Q

Virtualisation Levels - Application Level Virtualisation

A

Provides a virtual environment for specific applications, often using interpreters or runtime compilers.

35
Q

Virtualisation Levels Examples

A

Storage Virtualisation: Virtual disks and cloud storage solutions.
Computing Power Virtualisation: Virtual machines and cloud computing services.
Network Virtualisation: Virtual paths, circuits, and VPNs.
Function Virtualisation: Network function virtualisation (NFV) for flexible service deployments.

36
Q

Physical vs. Virtual Server - Performance

A

Physical Server: Offers dedicated resources and optimal performance.
Virtual Server: May incur a performance penalty but is often sufficient for most applications.

37
Q

Physical vs. Virtual Server - Security

A

Physical Server: Provides complete control over hardware and data.
Virtual Server: May share physical resources with other users, raising security concerns.

38
Q

Physical vs. Virtual Server - Availability

A

Virtual Server: Offers high availability with seamless failover and recovery.

39
Q

Physical vs. Virtual Server - Cost

A

Virtualisation: Can reduce long-term costs, especially for large deployments.

40
Q

Traditional Networking

A

Control Plane: Manages signaling and routing decisions.
Data Plane: Handles user data transport.

41
Q

Software-Defined Networking (SDN) Principles

A

Decoupling of Control and Data Planes: Separates decision-making from data transport.
Centralized Control: SDN controllers manage network behavior programmatically.
Programmability: Enables dynamic and flexible network configurations.

42
Q

Network Function Virtualisation (NFV)

A

Concept: Separates network functions from hardware, enabling virtual deployment.
Benefits:
Flexibility: Allows dynamic service deployment and scaling.
Efficiency: Reduces the need for dedicated hardware devices.
Implementation: Utilizes virtual machines to host functions like firewalls, load balancers, and NAT.

43
Q

SDN and NFV Integration

A

Combined Benefits:
SDN: Provides centralized network management and control.
NFV: Offers flexible, virtualized network functions.
Application: Supports diverse network services in fixed and mobile access networks, enhancing performance and reducing costs.

44
Q

Cloud Computing Concepts - Definition

A

Internet-based computing providing shared resources and services on demand

45
Q

Cloud Computing Concepts - Cloud Types

A

Public Cloud: Services available to the general public.
Private Cloud: Exclusive services for a specific organization.

46
Q

Cloud Computing Concepts - Resource Abstraction

A

Virtual resources are abstracted from physical data centers, allowing flexible and scalable solutions.

47
Q

Infrastructure as a Service (IaaS)

A

Provides virtualized computing resources over the Internet.
Consumer Control: Over OS, storage, and applications.
Examples: Amazon EC2, Google Compute Engine.

48
Q

Platform as a Service (PaaS)

A

Offers a development platform for building applications.
Development Platform: For building and deploying applications.
Examples: Windows Azure, Google AppEngine.

49
Q

Software as a Service (SaaS)

A

Delivers software applications over the Internet.
Software Delivery: Applications accessed via web browsers.
Examples: Google Apps, Microsoft Office 365.

50
Q

Everything as a Service (aaS)

A

Extends the service model to include various aspects of IT infrastructure.

51
Q

Computational Principles of Cloud Computing

A

Multi-Tenancy: A single software instance serves multiple customers, requiring privacy, performance, and failure isolation.
Elasticity: Dynamic resource allocation based on demand.
Resource Consolidation: Aggregates workloads to optimize resource usage and reduce variability.

52
Q

Cloud Computing Economics

A

Provisioning Dilemma: Balancing resource allocation with fluctuating demand patterns.
Cost Model: Pay-as-you-go pricing reduces upfront investment and accommodates demand spikes.
Economy of Scale: Shares resources across multiple users, akin to a utility service.

53
Q

Future Trends in Cloud Computing

A

Edge Computing: Brings cloud capabilities closer to users, enabling applications with low latency and high resource demands.
Multi-Access Edge Computing (MEC): Extends telecom infrastructure with computing facilities for mobile applications.
Fog and Crowd Computing: Engages user equipment and shared resources for enhanced performance.

54
Q

Future Trends - MEC

A

Applications: Supports mobile multimedia, augmented reality, video streaming, and gaming.
Challenges: Balances cost and performance with dynamic user traffic and limited resources.
Solutions: Incorporates edge computing paradigms to reduce latency and improve user experiences.

Infrastructure Stratergy (9 decks)

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