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1
Q

Client Server Computing - Definition and Key Characteristics

A

Definition: A network architecture where multiple clients request and receive services from a centralized server.
Key Characteristics: Centralized resource management, easy to manage data integrity and security, scalable to a large number of clients, but can have a single point of failure (the server).

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2
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Grid Computing - Definition and Comparison with Parallel Computing

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Definition: A form of distributed computing where a ‘grid’ of loosely connected, independent computers work together to perform large-scale tasks.
Comparison with Parallel Computing: Unlike parallel computing where multiple processors are involved in a single task in a cohesive system, grid computing uses a distributed architecture with each unit working on a separate task, often geographically dispersed.

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3
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Peer to Peer (P2P) - Definition and Key Characteristics

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Definition: A decentralized network model where each participant (peer) has equal capabilities and responsibilities, and can serve both as a client and a server.
Key Characteristics: No central server, peers directly share resources among each other, scalable, robust due to decentralized nature, but can have challenges in data integrity and security.

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4
Q

Cluster Computing - Basic Overview

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Overview: A set of computers (nodes) connected and working together as a single system to provide high availability, high performance, and redundancy.
Note: While not on your exam, it’s useful for understanding high-performance computing environments.

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5
Q

Elasticity in Cloud Computing - Definition and Example

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Definition: The ability of a cloud system to dynamically scale resources up or down as needed.
Example: Automatically adding more virtual machines during peak usage times and reducing them when demand decreases.

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6
Q

Scalability in Cloud Computing - Definition and Comparison with Elasticity

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Definition: The capability of a cloud system to handle a growing amount of work by increasing resources.
Comparison with Elasticity: Scalability is about the potential for growth (long-term), while elasticity refers to the system’s ability to manage short-term, dynamic changes in demand.

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7
Q

Integrity in Cloud Computing - Definition

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Definition: Ensuring data is accurate, consistent, and trustworthy throughout its lifecycle in the cloud

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8
Q

Data Release Notification in Cloud Computing - Meaning and Importance

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Meaning: The process of notifying stakeholders when sensitive or regulated data is released from a cloud environment.
Importance: Crucial for compliance, security, and maintaining trust in cloud services.

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9
Q

Migration in Cloud Computing - Definition, Types, and Importance

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Definition: The process of moving data, applications, or other business elements from an on-premises data center to a cloud environment or between cloud environments.
Types: Cloud-to-cloud, on-premises to cloud.
Importance: Key for leveraging cloud benefits like scalability, cost-efficiency, and improved performance.

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10
Q

Virtualisation in Cloud Computing - Definition and Role

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Definition: Creating a virtual version of something, such as servers, storage devices, networks, or even entire computing platforms.
Role: Fundamental for cloud computing; enables the creation of multiple simulated environments or dedicated resources from a single, physical hardware system.

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11
Q

Multitenancy in Cloud Computing - Definition and Significance

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Definition: A single instance of software runs on a server and serves multiple tenants (users or organizations).
Significance: Allows for cost savings, efficiency, and scalability as resources are shared among multiple users.

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12
Q

Web 3.0 and Its Relation to Cloud Computing

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Relation: Web 3.0, characterized by decentralized, semantic web technologies, often relies on cloud computing for enhanced data storage, processing capabilities, and to power various applications including AI and machine learning.

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13
Q

Confidentiality in Cloud Data - Definition and Importance

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Definition: Ensuring that sensitive information is accessible only to those authorized to access it.
Importance: Vital for protecting data privacy and security in cloud storage and services.

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14
Q

Cloud Bursting - Explanation and Use Cases

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Explanation: A configuration set up where an application runs in a private cloud or data center and “bursts” into a public cloud when the demand for computing capacity spikes.
Use Cases: Useful for handling peak loads, unexpected increases in traffic, or temporary requirements for additional computing resources.

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14
Q

Latency in Cloud Services - Impact and Management

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Impact: Affects the speed and performance of cloud services, important in real-time applications.
Management: Managed by optimizing network routes, using edge computing, and selecting geographically appropriate data centers.

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15
Q

Cloud Storage - Types and Key Features

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Types: Object storage, file storage, block storage.
Key Features: Scalability, durability, data redundancy, accessibility from any location.

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16
Q

Automation’s Role in Cloud Computing

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Role: Involves using software to create repeatable instructions and processes to replace or reduce human interaction with IT systems, essential for efficient cloud management, reducing errors, saving time, and maintaining consistency.

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17
Q

Serverless Computing - Definition and Benefits

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Definition: A cloud computing model where the cloud provider manages the infrastructure, allowing users to write and deploy code without worrying about the underlying hardware.
Benefits: Cost-efficiency, scalability, and simplicity in operations.

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18
Q

Instance in Cloud Computing - Explanation

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Explanation: Refers to a virtual server used for running applications on the cloud provider’s infrastructure. It’s a fundamental unit of scalable computing in a cloud environment.

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19
Q

Data Migration in Cloud Computing - Processes Involved, Comparison with Data Integration

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Processes Involved: Assessment, planning, extraction, cleansing, loading, verification.
Comparison with Data Integration: Data migration is moving data from one location to another, whereas data integration involves combining data from different sources into a unified view.

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20
Q

Data Integration in Cloud Computing - Explanation and Key Components

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Explanation: The process of consolidating data from different sources to provide a unified, consistent, and comprehensive view.
Key Components: ETL (Extract, Transform, Load) - extracting data from different sources, transforming it for analysis, and loading it into a target system.

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21
Q

Public Cloud - Definition and Use Cases

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Definition: A cloud computing model where cloud services are offered over the public internet and available to anyone who wants to purchase them.
Use Cases: Web-based email, online office applications, storage and testing, application development environments.

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22
Q

Private Cloud - Definition and Use Cases

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Definition: A cloud computing model where the cloud infrastructure is exclusively operated for a single organization, whether managed internally or by a third party, and hosted either internally or externally.
Use Cases: Organizations with high data security and privacy concerns, businesses with mission-critical operations requiring control and flexibility, companies in regulated industries.

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23
Q

Community Cloud - Definition and Use Cases

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Definition: A cloud infrastructure shared by several organizations with common concerns (security, compliance, jurisdiction, etc.), managed and hosted internally or by a third-party provider.
Use Cases: Government organizations, healthcare sectors, financial services collaboratively using a cloud setup for shared purposes like regulatory compliance, data security.

24
SaaS - Definition, Skill Level, and Responsibility
Definition: A software distribution model where applications are hosted by a third-party provider and made available to customers over the internet. Skill Level and Responsibility: Requires basic operational skills; users are responsible for managing the software's use, with the provider managing the infrastructure, platforms, and software maintenance.
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Hybrid Cloud - Definition and Use Cases
Definition: A cloud computing environment that combines on-premises private cloud with third-party public cloud services, with orchestration between the two platforms. Use Cases: Businesses requiring the flexibility of the public cloud for non-sensitive operations but need a private environment for sensitive or critical operations, companies with dynamic workloads or seasonal data spikes.
25
PaaS - Definition, Skill Level, and Responsibility
Definition: A cloud computing model that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure. Skill Level and Responsibility: Requires intermediate technical skills; users manage applications and data, while the provider manages runtime, middleware, O/S, virtualization, servers, storage, and networking.
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IaaS - Definition, Skill Level, and Responsibility
Definition: A form of cloud computing that provides virtualized computing resources over the internet. Skill Level and Responsibility: Requires advanced technical skills; users manage applications, data, runtime, middleware, and O/S, while the provider manages virtualization, servers, storage, and networking.
27
MAP Reduce - Overview and Use in Cloud Computing
Overview: A programming model and processing technique for distributed computing, based on two functions: Map (processes and converts data into a format suitable for reduction) and Reduce (performs summary operations). Use in Cloud Computing: Widely used for big data processing, analytics, and scalable, parallel processing tasks in cloud environments.
28
Bulk Synchronous Parallel - Overview and Use in Cloud Computing
Overview: A parallel computing model designed to simplify parallel programming, based on a sequence of computation and communication phases, separated by barrier synchronizations. Use in Cloud Computing: Utilized in large-scale parallel processing tasks and in situations where structured and predictable computation is required.
29
Principles of Cloud Computing - Fundamental Concepts
On-demand self-service, broad network access, resource pooling, rapid elasticity, measured service. These principles enable cloud computing to provide scalable, flexible, and efficient IT services.
30
Pervasive Computing - Definition and Relation to Cloud Computing
Definition: Pervasive computing, also known as ubiquitous computing, refers to the integration of computing capabilities into everyday life, through various interconnected devices. Relation to Cloud: Cloud computing supports pervasive computing by providing the necessary backend infrastructure, data storage, and processing power.
31
Cloud Stack Hardware - Components
Components: Physical servers, storage devices, networking equipment, and virtualization software. These components work together to create the infrastructure layer of cloud computing stacks.
32
Load Balancer in Cloud Computing - Role and Importance
Role and Importance: Distributes network or application traffic across multiple servers to ensure no single server becomes overloaded, improving responsiveness and availability of applications.
33
Firewall in Cloud Computing - Purpose and Function
Purpose and Function: A network security device that monitors and filters incoming and outgoing network traffic based on an organization's previously established security policies. In cloud environments, it helps protect data and resources from unauthorized access.
34
Routers in Cloud Computing - Function
Function: Networking devices that forward data packets between computer networks, playing a crucial role in managing traffic and ensuring data is sent efficiently across the cloud network.
35
Switches in Cloud Computing - Function
Function: Network devices that connect devices within a network, using MAC addresses to forward data to the correct destination. They are essential for building a scalable and efficient internal cloud network.
36
Vertical Storage Area Network - Explanation
Explanation: A storage network that is vertically integrated into a cloud environment, allowing for centralized storage management and scalability. Often used in large data centers for efficient data storage and management.
37
Horizontal & Vertical Scaling in Cloud Computing - Differences
Horizontal Scaling: Adding more machines or setting up a cluster of machines working together to distribute the load (scale out/in). Vertical Scaling: Increasing the capacity of existing hardware or software by adding resources like CPU, RAM (scale up/down).
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High Availability in Cloud Computing - Significance and Implementation
Significance: Refers to the system's ability to remain operational and accessible for a long period without interruption. Implementation: Achieved through redundant systems, failover mechanisms, and robust disaster recovery plans to ensure continuous operation and minimal downtime.
39
Strategies for Mitigating or Stopping Attacks in Cloud Security
Strategies: Implementing robust firewalls, intrusion detection/prevention systems, regular security audits, up-to-date anti-malware software, comprehensive access control, and continuous monitoring of network traffic.
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Common Cloud Security Threats - Malware Injection and Cookie Poisoning
Malware Injection: Injecting malicious code into cloud services or software. Cookie Poisoning: Altering or forging a cookie to gain unauthorized information or access.
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Vulnerabilities Commonly Found in Cloud Computing
Vulnerabilities: Include insecure APIs, misconfigured cloud storage, lack of encryption, and insufficient access controls, leading to potential unauthorized access and data breaches.
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Two-Factor Authentication (2FA) in Cloud Security
Definition: An additional security layer requiring not only a password and username but also something the user has on them, such as a physical token, to prevent unauthorized access.
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Single Sign-On (SSO) in Cloud Computing
Definition: A session and user authentication service that permits a user to use one set of login credentials to access multiple applications, enhancing user convenience and reducing password fatigue.
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Countermeasures in Cloud Security - Firewall and Antivirus
Firewall: Monitors and controls incoming and outgoing network traffic based on predetermined security rules. Antivirus: Protects against malware through detection, prevention, and removal tools.
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Consequences of Security Breaches in Cloud Computing
Consequences: Can include loss of reputation, legal penalties, financial loss, and data loss or corruption.
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Outline of Security Concepts - Avoid, Mitigate, Transfer, Accept
Avoid: Eliminating the risk by not engaging in the risky activity. Mitigate: Implementing measures to reduce the impact or likelihood of the risk. Transfer: Shifting the risk to a third party, like insurance. Accept: Acknowledging the risk and choosing to accept it without countermeasures.
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What is ISMS and How to Set It Up
ISMS: A systematic approach to managing sensitive company information, ensuring it remains secure. Includes people, processes, and IT systems. Setting Up: Assess risks, design policies, implement controls, conduct audits, and continuously monitor and improve the ISMS to address evolving threats.
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Virtualisation in Cloud Computing
Definition: The process of creating a virtual version of something, such as a server, storage device, network resource, or even an entire operating system, allowing multiple virtual systems to run on a single physical system. Importance: Increases efficiency and availability of resources, reduces costs, and facilitates scalability and quick deployment.
47
HyperThreading Technology
Definition: A technology (by Intel) that allows a single physical processor core to act like two logical processors, effectively enabling parallel processing and improving performance on threaded software. Use in Cloud Computing: Enhances the performance of cloud servers, allowing them to handle multiple tasks simultaneously.
48
Multi-Core Processors in Computing
Definition: Processors with two or more independent cores (or CPUs) in a single package, working simultaneously on different tasks. Benefit: Increases processing speed and efficiency, as tasks can be distributed across cores, reducing the load on each individual core.
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Service Oriented Architecture (SOA) in Cloud Computing
Definition: A software design style where services are provided to other components by application components, through a communication protocol over a network. The basic idea is that various services communicate with each other, often in a loosely coupled way, to create a working software application. Importance: Allows for greater reuse of existing software, flexibility in development, and integration of various services, essential in cloud environments for building efficient and scalable applications.
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Parallel Processing in Computing
Definition: The method of processing different parts of a single task simultaneously on multiple processors to increase computational speed. Application in Cloud Computing: Used in data processing and complex computations, where tasks can be divided and processed concurrently, enhancing performance.
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Azure Virtual Machines (VMs)
Description: Azure VMs offer scalable virtualized computing resources in the cloud. Used for a broad range of applications, they allow users to deploy both Windows and Linux-based environments, providing flexibility for various computing solutions.
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Azure Image Builder
Description: This service automates the process of building and patching VM images. It simplifies the management and deployment of custom VM images with automated workflows, reducing the manual effort involved in image configuration.
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AWS Elastic Load Balancer
Description: Designed to distribute incoming application traffic across multiple targets such as EC2 instances, containers, and IP addresses, ensuring high availability and fault tolerance for applications.
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AWS EC2 (Elastic Compute Cloud)
Description: AWS EC2 provides scalable compute capacity in the AWS cloud. It allows users to run and manage server instances, offering a wide range of instance types suited for different workloads and applications, including virtual machines.

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