You already know how users find your website (DNS and Route 53). Now we'll see how to make your content reach them fast, wherever they are in the world. That’s the mission of CloudFront, AWS’s Content Delivery Network (CDN). We already mentioned it when talking about edge locations in Chapter 3; now we’ll understand it in depth.
The problem: distance adds slowness
Imagine your server is in Ireland (Chapter 3) and a user visits you from Japan. Every time they request something, the request has to cross half the world and come back. Even if it travels at the speed of light, that distance adds latency (delay): the website loads slowly for that user.
User in Japan ──── (half the planet) ────► Server in Ireland
◄──── (and back) ─────────
= slow for the Japanese userThe solution: a CDN (Content Delivery Network)
A CDN (Content Delivery Network) solves this by bringing the content closer to users. Instead of everyone reaching your distant server, the CDN stores copies of your content in many points distributed around the world (the edge locations from subchapter 3.3). Each user receives the content from the point closest to them.
┌── Edge in Tokyo ──► users in Japan (fast) Your server ┼── Edge in Madrid ─► users in Spain (fast) (origin) └── Edge in São Paulo ► users in Brazil (fast)
CloudFront is AWS’s CDN, with hundreds of edge locations all over the planet.
Analogy: without a CDN it’s like having a single store in a city: all customers in the country have to travel there. With a CDN it’s like opening branches in every city: each customer goes to the nearest one. Much faster for everyone.
The key concepts of CloudFront
Distribution
A distribution is the CloudFront configuration for your content: it defines where the content comes from (the origin), how it’s cached, which domain it uses, etc. It’s the “unit” you create in CloudFront.
Origin
The origin is the original source of your content, where CloudFront fetches it the first time. It can be:
- An S3 bucket (very common for static websites, remember subchapter 5.5).
- A load balancer (Chapter 13) in front of your servers.
- Any web server, even outside AWS.
Cache: the heart of CloudFront
The cache is what makes a CDN magical. The first time someone in a region requests a file, CloudFront fetches it from the origin and stores a copy in the nearby edge location. Subsequent requests from that area are served directly from the copy, without bothering the origin.
1st request (from Japan): User → Tokyo Edge (doesn’t have it) → Ireland Origin → saves copy → user (slow only this time) 2nd and subsequent requests (from Japan): User → Tokyo Edge (already has the copy!) → user (super fast, doesn’t touch the origin)
Double benefit:
- Speed: users receive the content from nearby.
- Less load on your origin: most requests are handled by the cache, not your server. Your origin works much less (and can be smaller and cheaper).
TTL: how long a copy lasts in cache
An important question: how long does CloudFront keep a copy before fetching it again from the origin? That’s controlled by the TTL (Time To Live), the cache’s “lifetime”.
- Long TTL: the copy lasts a long time. Maximum speed and minimum work for the origin, but changes take longer to show.
- Short TTL: the copy refreshes often. Changes are seen sooner, but the origin works more.
Practical rule: content that doesn’t change (images, CSS, videos, static website files) → long TTL. Content that changes often → short TTL or no cache.
Invalidation: forcing a refresh
What if you change a file and want it to update now, without waiting for the TTL? You can do an invalidation: you tell CloudFront “delete this copy from all edge locations,” and it will fetch it from the origin on the next request. Useful after publishing a new version of your website.
What content benefits the most?
CloudFront shines especially with static content: images, videos, style sheets (CSS), JavaScript, downloadable files, and static websites (S3). This content is the same for all users, so caching it is ideal. It also speeds up dynamic content, though the gains are smaller there.
Real-world example: a digital newspaper with readers all over the world puts CloudFront in front of its website. Photos, videos, and design are served from each reader’s edge location (super fast), and the newspaper’s server only handles generating new articles. Result: the website flies for everyone and the server handles millions of visits without getting overloaded.
What you should remember
- CloudFront is AWS’s CDN: it brings your content closer to users by storing copies in edge locations around the world, reducing latency.
- A distribution is your CloudFront configuration; the origin is the original source (an S3 bucket, a load balancer, etc.).
- The cache is the key: the first request fetches the content from the origin and stores a copy; subsequent requests are served from the copy. Double benefit: speed + less load on the origin.
- The TTL defines how long a copy lasts (long for static content, short for changing content); invalidation forces an immediate refresh.
- It shines with static content (images, videos, CSS, JS, S3 websites), though it also speeds up dynamic content.
In the next subchapter, we’ll see how to make your site secure with HTTPS using free SSL/TLS certificates with ACM.
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
