Cloud Essentials

Cloud Computing Fundamentals

Conventional IT Infrastructure

Client-Server Paradigm for Web Applications

• A client application (for example, your web browser) sends a request over the internet (a network of networks) to a remote server (such as a Gmail server).
• The server continuously listens for incoming requests from clients. When a request arrives, it can accept it and establish a connection with the client.
• Clients and servers recognize each other using their IP addresses.

Physical Servers and Hardware (HW)

Computer/Server Components

1. COMPUTE: responsible for processing data and performing calculations
   • Hardware components: CPU (Central Processing Unit), GPU (Graphics Processing Unit)
   • GPUs are faster and more expensive than CPUs → ideal for high-performance tasks such as gaming graphics, big data analysis, machine learning training, and Generative AI.
2. MEMORY: temporarily holds frequently or recently accessed data for fast access
   • Data in memory is temporary/ephemeral, meaning it can be lost or overwritten (e.g., when opening new programs or restarting the server)
   • Hardware components: RAM (Random Access Memory)
3. STORAGE: persistently saves data, though access is slower than memory
   • Hardware components: SSD (Solid State Drive), HDD (Hard Disk Drive)
   • Data can be organized in various structures: block storage, object storage, file storage (file systems)
   • Databases (DBs): store data with additional structure and intelligence, making searching (querying) and processing more efficient than standard storage
4. NETWORK (NW): handles communication with external devices, sending and receiving data
   • Hardware components: cables, Network Interface Card (NIC), L3 Router, L2 Switch, DNS server, etc.
   • Networking often involves multiple intermediate devices to ensure proper routing across a network

• Physical hardware can be emulated using technologies like virtualization and containerization, allowing virtual components and servers to use physical resources more efficiently

Challenges of Physically Hosted Servers

• Traditionally, IT organizations hosted servers on their premises or in Data Centers (DCs)

• Example: Google started in a garage with its own servers before expanding

Common challenges:

• Unpredictable scaling: difficult to forecast user numbers or usage patterns (time of day, week, or year) → risk of under- or over-provisioning
• Wasted capacity: buying large servers as a precaution often leaves unused resources in the early stages
• Management overhead: engineers must update software, monitor servers 24/7, and handle hardware upgrades/replacements
• Maintenance costs: servers require space, secure facilities, power, and cooling
• Low resilience: physically localized servers are vulnerable to natural disasters, vandalism, or other incidents
• High startup costs: purchasing and setting up physical infrastructure is expensive
• Cloud computing addresses many of these issues, allowing customers to rent infrastructure and avoid the challenges of managing physical servers

Cloud Computing

• Definition: A model that provides ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, networks, storage, applications, services).
  • These resources can be rapidly allocated and released with minimal management effort or provider interaction.
• Cloud computing has transformed how businesses and individuals access and utilize computing resources.
  • Benefits: increased scalability, greater flexibility, reduced maintenance, less physical infrastructure

Five Key Characteristics of a Cloud Platform

• A cloud platform is defined by five main characteristics:
  • On-Demand Self-Service
  • Broad Network Access
  • Resource Pooling
  • Rapid Elasticity
  • Measured Service

On-Demand Self-Service

• Users can provision resources as needed without requiring human intervention.
  • Management can be done via UI, CLI, or APIs.

Broad Network Access

• Resources are available over the network and accessed through standard mechanisms.
  • No specialized devices or non-standard network protocols are required.

Resource Pooling

• Resources are shared among multiple users using a multi-tenant model.
• Users experience location independence → they do not know or control the exact location of resources.
• Economies of scale: buying hardware in bulk reduces costs, allowing cloud providers to offer more affordable services.

Rapid Elasticity

• Resources can be quickly scaled up or down based on demand.
  • Avoid overprovisioning → prevents wasted expenses
  • Avoid underprovisioning → maintains performance
• To users, resources appear unlimited.
• This is one of the most important advantages of cloud computing.

Measured Service

• Resource usage can be monitored, controlled, reported, and billed.
• Pay only for what you consume (pay-as-you-go).
  • Important: Always terminate resources you no longer need to avoid unexpected costs.

Six Advantages of Cloud Computing (AWS Whitepaper)

1. Shift from CAPEX to OPEX
   • Convert fixed capital expenses into variable operational expenses
   • Reduces Total Cost of Ownership (TCO) and operational costs
   • Customers pay on demand, without owning hardware
2. Benefit from massive economies of scale
   • Large-scale cloud providers like AWS can offer lower prices due to efficiency
3. Eliminate capacity guessing
   • Scale resources based on actual usage, avoiding idle infrastructure
4. Increase speed and agility
   • Provision or release resources faster than owning physical hardware
   • Enables cost-effective experimentation and development
5. Reduce data center management costs
   • Less time and money spent maintaining infrastructure, allowing focus on business and customers
6. Deploy globally in minutes
   • Launch applications in multiple regions with minimal effort
   • Utilize global cloud infrastructure for lower latency and improved user experience

Public vs Private vs Multi vs Hybrid Cloud

Types of Cloud Computing

Public Cloud

• A cloud computing platform that is openly available to the general public
  • Users can access, provision, and manage resources over the public internet
• Leading public cloud service providers include:
  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform (GCP)

Overview Diagram of Cloud Computing Models

• The use of multiple public cloud platforms to deploy and operate applications
• Common implementation examples include:
  • Hosting different components of an application architecture across separate cloud providers
  • Mirrored cloud architecture, where the complete application stack is deployed across two providers (e.g., AWS and Azure)
    • If one cloud environment becomes unavailable, the application remains accessible through the other, ensuring high availability (HA)
• Recommendation: Avoid single-pane-of-glass management interfaces for multi-cloud environments
  • These tools abstract vendor-specific details
    • This makes it difficult to identify which capabilities and advantages belong to each provider
  • Only shared features across vendors are typically exposed
    • Provider-exclusive services and innovations may not be visible

Private Cloud

• An on-premises cloud platform dedicated to a single organization
• Major public cloud providers also offer private, on-premises cloud solutions, such as:
  • AWS Outposts
  • Azure Stack
  • Google Anthos
• To qualify as a true private cloud, the platform must still meet the five essential characteristics of cloud computing
  • Traditional on-premises virtualization platforms (e.g., VMware, Hyper-V, XenServer) are not equivalent to a private cloud
    • Although they may offer cloud-like features, they do not satisfy all five required cloud computing characteristics

Hybrid Cloud

• A model that combines private cloud and public cloud resources, operating together as a single, integrated environment
  • The same tools, processes, and management interfaces are used across both public and private cloud components
• Using public cloud services alongside on-premises infrastructure alone constitutes a hybrid environment or hybrid networking, not a hybrid cloud
  • To be classified as a hybrid cloud, both public cloud and private cloud platforms must be fully integrated

Overview Diagram of Cloud Computing Models

Cloud Service Models (Everything as a Service – XaaS)

Infrastructure Stack (App Stack)

• The infrastructure stack represents the layers involved in deploying a software application:
  1. Application
  2. Data – data stores, databases, etc.
  3. Runtime Environment (RTE) – code libraries and dependencies
  4. Container – Docker, Kubernetes (K8s), etc.
  5. Operating System (OS) – Linux, Windows, macOS, etc.
  6. Virtualization
  7. Server – physical machine or computer
  8. Infrastructure – server racks, network routers, and related hardware
  9. Facilities – building, electricity, real estate, security personnel, etc.
• Unit of consumption: The component of the stack that the customer pays for and consumes
  • All layers below the unit of consumption are managed by the vendor
  • The unit of consumption itself and all layers above are managed by the customer
  • Different cloud service models define different units of consumption
• On-Premises Deployment
  • Customers are responsible for all layers of the infrastructure stack
  • High cost, significant administrative overhead, and operational risks
  • Maximum control and flexibility over the environment
• Data Center (DC) Hosted Deployment
  • Customers pay primarily for facility usage (fully or partially) while managing other layers themselves
  • Common practice prior to the widespread adoption of cloud computing

Popular Cloud Service Models

Infrastructure-as-a-Service (IaaS)

• Unit of consumption: Operating System (OS)
• IaaS provides virtualized servers or machines (VMs)
• Pricing: Pay-as-you-go
  • Charges are based on seconds, minutes, or hours of VM usage
  • No costs are incurred when VMs are not in use
• Offers reduced cost and operational risk, with some trade-offs in flexibility
• One of the most widely adopted cloud services
• Example: Amazon Elastic Compute Cloud (EC2)

Platform-as-a-Service (PaaS)

• Unit of consumption: Runtime Environment (RTE)
• Designed for developers who want to deploy and run applications without managing underlying infrastructure
• Example platforms: Heroku, AWS Elastic Beanstalk

Software-as-a-Service (SaaS)

• Unit of consumption: Application
• Users access the application directly without exposure to other infrastructure layers
  • Limited control over tools and customization
  • Minimal costs and operational risks
• Pricing: Usually subscription-based (monthly or yearly), sometimes with free tiers or trial options
• Examples: Netflix, Dropbox, Gmail

Other Cloud Services

• Function-as-a-Service (FaaS): e.g., AWS Lambda
• Database-as-a-Service (DBaaS): e.g., MongoDB Atlas
• Container-as-a-Service (CaaS): e.g., Amazon Elastic Container Service (ECS)
• …and more specialized offerings

Overview Diagram

On-Site	Data Center Hosted	Infrastructure as a Service (IaaS)	Platform as a Service (PaaS)	Database as a Service (DBaaS)	Software as a Service (SaaS)
Application Software	Application Software	Application Software	Application Software	Application Software	Application Software
Data Assets	Data Assets	Data Assets	Data Assets	Data Assets	Data Assets
Runtime Environment	Runtime Environment	Runtime Environment	Runtime Environment	Runtime Environment	Runtime Environment
Container Platform	Container Platform	Container Platform	Container Platform	Container Platform	Container Platform
Operating System	Operating System	Operating System	Operating System	Operating System	Operating System
Virtualization	Virtualization	Virtualization	Virtualization	Virtualization	Virtualization
Physical Servers	Physical Servers	Physical Servers	Physical Servers	Physical Servers	Physical Servers
Physical Infrastructure	Physical Infrastructure	Physical Infrastructure	Physical Infrastructure	Physical Infrastructure	Physical Infrastructure
Facilities	Facilities	Facilities	Facilities	Facilities	Facilities