One of the most popular and practical uses of S3 is hosting a website directly, with no need for servers. It’s cheap, simple, and automatically scales to millions of visits. In this subchapter, we wrap up the S3 chapter by seeing how and when to use it.
Static Web vs Dynamic Web
First, a key distinction:
- Static web: files are served as is to all visitors. The content doesn’t change depending on who visits. These are HTML, CSS, JavaScript files, images… Examples: a corporate website, a blog, a portfolio, product documentation, a landing page.
- Dynamic web: content is generated on the fly depending on the user or data (requires a server to run code and query databases). Examples: your online banking dashboard, a personalized shopping cart.
S3 serves static websites, not dynamic ones. But beware: today, many modern websites (built with React, Vue, Angular…) are static in delivery and get dynamic data by calling an API separately. So “static” doesn’t mean “simple” or “boring.”
Analogy: A static website on S3 is like a bulletin board: you pin up the sheets and everyone who passes by sees the same thing. A dynamic website is like a waiter who prepares something different for each customer.
Why Hosting a Website on S3 is a Good Idea
- No servers to manage: there’s no EC2 to maintain, patch, or monitor. You just upload files.
- Automatically scales: if your website goes viral and millions visit, S3 handles it without you doing anything. There’s no server to get overloaded.
- Cheap: you only pay for storage (just a few files) and for downloads. A small website can cost cents per month.
- Very reliable: you inherit S3’s durability and availability.
Real example: A startup launches its presentation website (the typical landing page with product info and a contact form). Instead of paying for a server running 24/7, they upload it to S3. When they hit the news and get a huge spike in visits, the website holds up perfectly and the cost remains minimal.
How It Works, Broadly Speaking
The conceptual steps to host a static website on S3 are:
- Create a bucket (remember: globally unique name, subchapter 5.1).
- Upload the website files (
index.html, style sheets, images, etc.). - Enable the "static website hosting" option on the bucket, specifying the start document (usually
index.html) and the error document (for example,error.html). - Grant public read permission to the files via a bucket policy (remember subchapter 5.4: you must consciously open access and only as needed).
With this, S3 gives you a URL from which your website is accessible.
The URL and HTTPS Problem (and Its Solution: CloudFront)
Hosting directly on S3 has two limitations:
- The URL S3 gives is long and ugly (something like
my-bucket.s3-website-eu-west-1.amazonaws.com), not your nice domainwww.mycompany.com. - Direct S3 hosting does not offer HTTPS (the secure connection with the padlock) for custom domains.
The professional solution is to put CloudFront in front of the bucket (remember subchapter 3.3). This gives you:
- HTTPS with a free certificate (ACM, which we’ll see in Chapter 16).
- Your own domain (
www.mycompany.com) via Route 53 (Chapter 16). - Global speed thanks to caching at edge locations.
- More security: the bucket can remain private and only CloudFront accesses it (you no longer need to expose it to the public).
Recommended architecture for a professional static website:
User → CloudFront (HTTPS, global cache) → S3 (private files) ↑ Route 53 (your domain) + ACM (free SSL certificate)This combination —S3 + CloudFront + Route 53 + ACM— is one of the most widely used patterns in the world for serving websites and is also Project 1 that you’ll build in Chapter 33.
When to Use S3 for Hosting (and When Not To)
Use it for:
- Corporate websites, blogs, portfolios, documentation.
- Landing pages and marketing websites.
- Single Page Applications (SPA) built with React, Vue, Angular… that consume a separate API.
Don’t use it (directly) for:
- Websites that need to run code on the server for each request (for that, EC2, containers, or Lambda).
- When you need server logic, sessions, heavy server-side rendering, etc. (though you can often combine S3 for static + Lambda/API for dynamic).
What You Should Remember
- S3 can host static websites (HTML, CSS, JS, images) without servers: cheap, scalable, and reliable.
- “Static” doesn’t mean simple: modern SPAs (React, Vue…) are served this way and get data from a separate API.
- Direct S3 hosting gives you an ugly URL and no HTTPS for custom domains; the professional solution is to put CloudFront in front (HTTPS, custom domain, speed, and security).
- The S3 + CloudFront + Route 53 + ACM pattern is the standard for static websites and you’ll build it in Chapter 33.
- For per-request server logic, S3 is not enough: combine it with Lambda, containers, or EC2.
With this, you finish Chapter 5 and master object storage. In Chapter 6 we’ll look at networks in AWS with VPC: how your resources connect and are isolated securely.
Cloud, AWS & Terraform — From Zero to Expert
Chapter 1 · What is cloud computing
- 1.1 The traditional client-server model
- 1.2 Problems the cloud came to solve
- 1.3 On-premise vs cloud vs hybrid
- 1.4 The three service models: IaaS, PaaS, SaaS
- 1.5 The five pillars of cloud (according to NIST)
- 1.6 Real advantages: elasticity, pay-as-you-go, global availability
Chapter 2 · The cloud market and major providers
- 2.1 AWS, Azure and GCP: differences and market share
- 2.2 Why learn AWS first
- 2.3 Concepts that are universal among providers
Chapter 3 · Regions, availability zones and edge
- 3.1 What is an AWS region and how to choose it
- 3.2 Availability Zones: high availability by design
- 3.3 Edge locations and CloudFront
- 3.4 Latency, resilience and data sovereignty
Chapter 4 · Compute: EC2
- 4.1 Instances: types, families and when to choose each
- 4.2 AMIs, key pairs and Security Groups
- 4.3 Instance lifecycle
- 4.4 Elastic IPs and Placement Groups
- 4.5 Savings Plans vs Reserved vs On-Demand vs Spot
Chapter 5 · Storage: S3
- 5.1 Buckets, objects and keys
- 5.2 Storage classes (Standard, IA, Glacier…)
- 5.3 Versioning and object lifecycle
- 5.4 Bucket policies and ACLs
- 5.5 Static website hosting
Chapter 6 · Networking: VPC
- 6.1 What is a VPC and why you need it
- 6.2 Public and private subnets
- 6.3 Internet Gateway and NAT Gateway
- 6.4 Route Tables and Network ACLs
- 6.5 VPC Peering and endpoints
Chapter 7 · Identity and access: IAM
- 7.1 Users, groups, roles and policies
- 7.2 The principle of least privilege
- 7.3 Identity-based vs resource-based policies
- 7.4 MFA and temporary credentials (STS)
- 7.5 IAM security best practices
Chapter 8 · Managed databases
- 8.1 RDS: engines, Multi-AZ and read replicas
- 8.2 Aurora and its advantages over vanilla RDS
- 8.3 DynamoDB: key-value / document model
- 8.4 ElastiCache for in-memory cache
- 8.5 When to use each type of database
Chapter 9 · Why Infrastructure as Code
- 9.1 Problems with manual provisioning
- 9.2 Declarative vs imperative IaC
- 9.3 Terraform vs CloudFormation vs Pulumi vs CDK
- 9.4 The plan → apply → destroy cycle
Chapter 10 · HCL: the Terraform language
- 10.1 Resource, variable, output, locals blocks
- 10.2 Data types: string, number, bool, list, map, object
- 10.3 Expressions, references and built-in functions
- 10.4 Conditionals and loops (count, for_each, for)
Chapter 11 · Providers and state
- 11.1 How the AWS provider works
- 11.2 The terraform.tfstate file and its importance
- 11.3 Local state vs remote state (S3 + DynamoDB)
- 11.4 Essential commands: init, plan, apply, destroy, fmt, validate
Chapter 12 · Your first real infrastructure in Terraform
- 12.1 Create a VPC with subnets from scratch
- 12.2 Launch a public EC2 instance
- 12.3 Associate a Security Group and an Elastic IP
- 12.4 Outputs and references between resources
- 12.5 Team workflow: PR review of plans
Chapter 13 · Load balancing and auto scaling
- 13.1 Application Load Balancer vs Network Load Balancer
- 13.2 Target Groups, listeners and rules
- 13.3 Auto Scaling Groups: policies and metrics
- 13.4 Warm pools and lifecycle hooks
Chapter 14 · Serverless with Lambda
- 14.1 The Lambda execution model
- 14.2 Triggers: API Gateway, S3, DynamoDB Streams, SQS
- 14.3 Dependency management and layers
- 14.4 Cold starts and strategies to reduce them
- 14.5 Limits and anti-patterns
Chapter 15 · Messaging and events
- 15.1 SQS: standard vs FIFO queues, DLQ
- 15.2 SNS: topics, subscriptions, fan-out
- 15.3 EventBridge: event buses and rules
- 15.4 Patterns: pub/sub, decoupling, saga
Chapter 16 · Content delivery and DNS
- 16.1 Route 53: record types and routing policies
- 16.2 CloudFront: distributions, caches and origins
- 16.3 ACM: free SSL/TLS certificates
- 16.4 WAF integrated with CloudFront
Chapter 17 · Containers on AWS
- 17.1 Docker: quick review of key concepts
- 17.2 ECR: private image registry
- 17.3 ECS: task definitions, services, Fargate vs EC2
- 17.4 EKS: when Kubernetes and when not
Chapter 18 · Modules: reuse and composition
- 18.1 Anatomy of a Terraform module
- 18.2 Input variables, outputs and dependencies
- 18.3 Local modules vs Terraform Registry modules
- 18.4 Module versioning with Git tags
- 18.5 Design of generic vs domain-specific modules
Chapter 19 · Workspaces and environment management
- 19.1 Terraform workspaces: use cases and limitations
- 19.2 Directory strategy per environment (dev/stg/prod)
- 19.3 Terragrunt: DRY for environment configurations
- 19.4 Environment variables and .tfvars files
Chapter 20 · Remote backends and locking
- 20.1 Configure S3 + DynamoDB as backend
- 20.2 State locking: avoiding team corruption
- 20.3 State migration between backends
- 20.4 terraform import: bring existing resources into state
Chapter 21 · Infrastructure testing
- 21.1 Terraform validate and fmt in CI
- 21.2 Checkov and tfsec: static security analysis
- 21.3 Terratest: integration tests in Go
- 21.4 Contract testing between modules
Chapter 22 · Terraform in CI/CD
- 22.1 Basic pipeline: lint → plan → apply in GitHub Actions
- 22.2 Atlantis: GitOps for Terraform
- 22.3 Terraform Cloud / HCP Terraform
- 22.4 Drift detection and automatic reconciliation
Chapter 23 · Defense in depth
- 23.1 AWS Organizations and Service Control Policies
- 23.2 AWS Config: continuous compliance
- 23.3 GuardDuty: threat detection
- 23.4 Security Hub: centralized view
- 23.5 KMS: key management and rotation
- 23.6 Secrets Manager vs Parameter Store
Chapter 24 · Observability: logs, metrics and traces
- 24.1 CloudWatch Logs, metrics and alarms
- 24.2 CloudWatch Dashboards and Contributor Insights
- 24.3 X-Ray: distributed tracing
- 24.4 OpenTelemetry on AWS
- 24.5 Managed Grafana and Managed Prometheus
Chapter 25 · Cost optimization
- 25.1 AWS Cost Explorer and budgets with alerts
- 25.2 Trusted Advisor and Compute Optimizer
- 25.3 Rightsizing: how to detect overprovisioning
- 25.4 Savings Plans vs Reserved Instances: strategic decision
- 25.5 FinOps: culture and processes to control spending
Chapter 26 · High availability and disaster recovery
- 26.1 RTO and RPO: defining objectives
- 26.2 Strategies: backup/restore, pilot light, warm standby, multi-site
- 26.3 Route 53 health checks and automatic failover
- 26.4 AWS Backup: centralized backup policy
Chapter 27 · AWS Well-Architected Framework
- 27.1 The six pillars: operational excellence, security, reliability, performance efficiency, cost optimization, sustainability
- 27.2 Well-Architected Tool: formal reviews
- 27.3 How to apply the framework in design decisions
Chapter 28 · Serverless architectures at scale
- 28.1 Event-driven architecture with Lambda + EventBridge
- 28.2 Saga pattern for distributed transactions
- 28.3 Step Functions: orchestration of complex workflows
- 28.4 Lambda@Edge and CloudFront Functions
Chapter 29 · Data platforms on AWS
- 29.1 Data Lake with S3, Glue and Athena
- 29.2 Kinesis Data Streams and Firehose for streaming
- 29.3 Redshift: data warehousing at scale
- 29.4 Lake Formation: data governance
Chapter 30 · Multi-account and landing zones
- 30.1 Why separate workloads into different accounts
- 30.2 AWS Control Tower and Account Factory
- 30.3 Centralized log and security management
- 30.4 Terraform at multi-account scale with shared modules
Chapter 31 · Platform Engineering and Internal Developer Platform
- 31.1 Golden paths and abstractions over Terraform
- 31.2 AWS Service Catalog
- 31.3 Backstage as a developer portal
- 31.4 Terraform modules as internal product
Chapter 32 · Relevant AWS certifications
- 32.1 Cloud Practitioner: is it worth it?
- 32.2 Solutions Architect Associate → Professional
- 32.3 DevOps Engineer Professional
- 32.4 Specialty: Security, Database, Networking
- 32.5 HashiCorp Terraform Associate
Chapter 33 · Projects to consolidate what you've learned
- 33.1 Project 1: serverless blog (S3 + CloudFront + Lambda + DynamoDB)
- 33.2 Project 2: REST API with ECS Fargate + RDS + ALB
- 33.3 Project 3: data platform with Glue + Athena + Redshift
- 33.4 Project 4: multi-account landing zone with Terraform and Control Tower
