What is Cloud Computing?
Cloud computing is the delivery of computing services - servers, storage, databases, networking, software - over the internet ("the cloud"). Instead of owning physical hardware, you rent what you need from a cloud provider.
Think of it like electricity. Before power grids, factories had to generate their own power. Now they just plug into the grid. Cloud computing does the same for IT infrastructure - you use what you need without managing the underlying hardware.
Why Cloud Computing?
- No upfront cost: No need to buy expensive servers
- Pay-as-you-go: Only pay for what you use
- Scalability: Scale up or down in minutes
- Global reach: Deploy worldwide instantly
- Reliability: Built-in redundancy and backups
- Focus on code: Let providers handle infrastructure
Cloud Service Models
┌─────────────────────────────────────────────────────────┐
│ YOU MANAGE LESS → │
├─────────────────┬─────────────────┬─────────────────────┤
│ IaaS │ PaaS │ SaaS │
│ Infrastructure │ Platform │ Software │
│ as a Service │ as a Service │ as a Service │
├─────────────────┼─────────────────┼─────────────────────┤
│ ○ Applications │ ○ Applications │ ● Applications │
│ ○ Data │ ○ Data │ ● Data │
│ ○ Runtime │ ● Runtime │ ● Runtime │
│ ○ Middleware │ ● Middleware │ ● Middleware │
│ ○ OS │ ● OS │ ● OS │
│ ● Virtualization│ ● Virtualization│ ● Virtualization │
│ ● Servers │ ● Servers │ ● Servers │
│ ● Storage │ ● Storage │ ● Storage │
│ ● Networking │ ● Networking │ ● Networking │
└─────────────────┴─────────────────┴─────────────────────┘
○ = You manage ● = Provider manages
IaaS (Infrastructure as a Service)
Rent virtual machines, storage, and networks. You manage the OS and everything above.
Examples: AWS EC2, Azure VMs, Google Compute Engine, DigitalOcean Droplets
Use when: You need full control, running custom software, migrating existing apps
PaaS (Platform as a Service)
Rent a platform to run your code. Provider manages OS, runtime, and scaling.
Examples: Heroku, AWS Elastic Beanstalk, Google App Engine, Azure App Service
Use when: You want to focus on code, not infrastructure
SaaS (Software as a Service)
Use complete software over the internet. No installation or maintenance.
Examples: Gmail, Salesforce, Slack, Dropbox
Use when: You need ready-to-use applications
Cloud Deployment Models
Public Cloud
Services offered over the public internet, shared infrastructure managed by cloud provider.
Examples: AWS, Azure, GCP
Pros: No upfront cost, infinite scalability, global reach
Cons: Less control, data on shared infrastructure
Private Cloud
Dedicated infrastructure for a single organization, either on-premises or hosted.
Pros: Full control, better security, compliance
Cons: Higher cost, requires expertise
Hybrid Cloud
Combination of public and private clouds, with data/apps moving between them.
Pros: Flexibility, keep sensitive data private
Cons: Complexity, integration challenges
Major Cloud Providers
Provider Market Share Strengths
─────────────────────────────────────────────────────
AWS ~32% Most services, mature
Azure ~23% Enterprise, Microsoft integration
Google Cloud ~10% AI/ML, Kubernetes, data analytics
Others ~35% DigitalOcean (simplicity),
Alibaba (Asia), IBM (enterprise)
All major providers offer:
✓ Compute (VMs, containers, serverless)
✓ Storage (object, block, file)
✓ Databases (SQL, NoSQL, caching)
✓ Networking (VPC, load balancers, CDN)
✓ Security (IAM, encryption, compliance)
Core Cloud Services
Compute
- Virtual Machines: Traditional servers in the cloud (EC2, Azure VMs)
- Containers: Docker containers, Kubernetes (ECS, EKS, GKE)
- Serverless: Run code without managing servers (Lambda, Cloud Functions)
Storage
- Object Storage: Store files, images, backups (S3, Azure Blob)
- Block Storage: Virtual hard drives for VMs (EBS, Azure Disk)
- File Storage: Shared file systems (EFS, Azure Files)
Databases
- Relational: PostgreSQL, MySQL as a service (RDS, Cloud SQL)
- NoSQL: DynamoDB, CosmosDB, MongoDB Atlas
- Caching: Redis, Memcached (ElastiCache, Cloud Memorystore)
Networking
- VPC: Virtual private networks
- Load Balancers: Distribute traffic across servers
- CDN: Cache content globally (CloudFront, Azure CDN)
Serverless Computing
Run code without provisioning servers. Pay only when code runs.
# AWS Lambda example (Python)
def lambda_handler(event, context):
name = event.get('name', 'World')
return {
'statusCode': 200,
'body': f'Hello, {name}!'
}
# Triggered by:
# - HTTP requests (API Gateway)
# - File uploads (S3)
# - Database changes (DynamoDB Streams)
# - Scheduled events (CloudWatch Events)
# Benefits:
# - No server management
# - Automatic scaling
# - Pay per execution (milliseconds)
# - Great for event-driven workloads
Cloud Security Basics
- Shared Responsibility: Provider secures infrastructure, you secure your data and apps
- IAM: Identity and Access Management - control who can do what
- Encryption: Encrypt data at rest and in transit
- Network Security: Security groups, firewalls, private subnets
- Compliance: GDPR, HIPAA, SOC 2 certifications
Security Best Practices:
1. Use IAM roles instead of access keys
2. Enable MFA for all users
3. Encrypt everything (storage, databases, traffic)
4. Use private subnets for sensitive resources
5. Regularly audit access and permissions
6. Enable logging and monitoring
7. Keep software and dependencies updated
Getting Started
- Start free: All major providers offer free tiers
- Learn one provider well: Skills transfer between providers
- Start with managed services: Less to manage, faster development
- Use Infrastructure as Code: Terraform, CloudFormation
- Set billing alerts: Avoid surprise bills
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