# Introduction to cloud programming

## Client server architecture

- Definition: Clients make request to server for a resource, and the server
  running server software make the resource available, though a response.
    - It is based on **Request/Response** mechanism.
- Client: Request resources
- Server: Provide resource

## Distributed System

- Definition: Consists of hardware, software, and data components located at
  networked computers, which communicate and coordinate their actions using
  **protocols** and **passing messages**.
- Distributed Computing: specialized field in cs, dedicated to the study of
  distributed systems.
- **Advantages**:
    - **Modularity**
    - **Speed** up computation and data processing
    - Ease of tracking **failure**

### Characteristics

- Concurrency: multiple components working on different parts of the same task
  at the same time
- No global clock for time system, use ntp to solve the problem.
- Autonomous computational entities: failure is **independent**, and is loosely
  coupled
- Communicate by passing messages

### Parallel computing vs. Distributed computing

- Parallel computing: many executions are carried out at the same time.
    - Done by dividing large problem into smaller parts that are carried out by
      different components at the same time
    - Use **shared** memory, and exchanges information between processors.
    - To speed up computation or execution
- Differences:
    - Parallel computing:
        - Sharing: system whose processors use **shared memory** to run
          processes
        - Strongly coupled and has resource contention
    - Distributed computing:
        - Sharing:have their own individual memory but communicate by passing
          **messages** among the nodes and processors.
        - Loosely coupled, and distributed

### Examples

- Internet
- Intranets
- Domain name service
- Grid computing
- Peer to peer (p2p) computing
- Cloud computing

### Architectures

#### Client-server

- 2-tier architecture
    - Server and clients: one server and many clients
    - Server has storage, database and run the application
- 3-tier architecture
    - The three tiers:
        - Presentation layer: User interface, runs **web server**
        - Business logic or application layer: functions are implemented, runs
          **dynamic content processing and generation** software
        - Data layer: data management, runs **database management system**(DBMS)
- Thin and flat client
    - Thin: client is only the **presentation**, all processing and data storage
      are provided by server
        - Heavy lifting is done on server and network
    - Fat: processing is delegated to the client, foe example **application
      processing**
        - Process may be done **both** at client and server
        - **Balanced** distribution of processing

### Peer to peer systems

- Definition: consists of nodes of computers that perform **both** client and
  server functionalities and capabilities
    - **Client** oriented: Peer machines are client computers that is connected
      to internet
    - Peer machines **autonomously** join or leave network, no master-slave
      relationship: **no** **central** coordination, and **no** **global** view

### Flynn's taxonomy

- Definition: 4 classifications for computer architectures
- SISD: Single Instruction Single Data Stream
    - Serial computer, no parallelism
- SIMD: Single Instruction Multiple Data Streams
    - Some parallelism
- MISD: Multiple Instruction Single Data Stream
    - Not popular in practice
- MIMD: Multiple Instruction Multiple Data Streams
    - True palallel computation, most widely used
    - Multiple independent processors executing different instructions on
      different data streams
    - Majority of distributed system use MIMD
    - Basis of supercomputer architectures

## Cloud Computing

### History of Cloud computing

- Started as a concept of "Utility Computing", which you can use as public
  utility.
- Grid Computing:
    - Started the concept, in 1995 to mimic the electricity grid that provides
      electric as a utility on demand basis
    - Large scale distributed systems:
        - Collection of resources from distributed locations
    - General purpose middleware
        - Interacts with heterogeneous systems
- The above gave birth to cloud computing

### Definition

- A computing infrastructure, that consists of shared pool of **virtualized**
  hardware, software and data that are **provided** as a **services**, which
  scales on the demand
- A form of **distributed** computing, that enables computational resources to
  be provided as a service
- Infrastructure as software

### Features:

- Enabled by **internet**
- Use middle-ware to connect systems
- Utility based:
    - Don't own or maintain the resources, but subscribe
- Usage on **demand**
- Elastic, can scale up and down
- **Service Oriented Architecture**
- Cheaper and save time

### Architecture

- Front end
- Cloud based delivery
- Back end

## Cloud Deployment Models

### Public Cloud

- Advantages:
    - Flexible
    - Reliable
    - Highly **scalable**
    - Low cost
    - Place independence
- Disadvantages:
    - Less secures
    - Not **customizable**

### Private cloud

- Advantages:
    - Highly **private** and **secured**
    - More **control**
- Disadvantages:
    - Poor scalability
        - Scaled within hosted resources
    - Costly:
        - secured
        - More features
    - Inflexible pricing
    - Restriction, hard to expose globally

## Cloud Service Models

- Common:
    - SaaS: Software as a service: least control
    - PaaS: Platform as a service
    - IaaS: Infrastructure as a service: most control
- Incommon:
    - DBaaS: database
    - Naas: network
    - SECaaS: Security
    - DaaS: Desktop

## Technologies for cloud computing

- Internet
    - web service
- Virtualization technologies
- Data center
- Networking
- Security
- Physical hardware

## Services:

- Amazon web services: AWS
- Microsoft Azure
- Google Cloud
- Alibaba Cloud
- Tencent Cloud
- Baidu Cloud
- IBM Cloud
- Oracle Cloud
- https://salesforce.com

## Applications and Job opportunities

### Jobs

- Big Data and Data analytics
- E-Commerce
- Computationally and data intensive applications
- AI
- IoT
- Software Development

### AWS Certification Exam

- Professional: 2 years
- Associate: 1 year
- Foundational 6 month
- Speciality: Technical experience

### MS Exam

- Expert
- Associate
- Fundamental
- Speciality

### Google Cloud Certification Exams

- Data Engineer
- CLoud Architect
- Cloud Developer
- CLoud devops Engineer
- Cloud Security Engineer
- Collaboration engineer
- Cloud network engineer
- Cloud engineer
- G suite
- Hybrid multi-cloud