We close the content delivery chapter with protection against attacks. Your website is already fast (CloudFront) and encrypted (ACM), but the internet is full of malicious traffic: bots, hackers, attack attempts. The WAF (Web Application Firewall) is the shield that filters out that harmful traffic before it reaches your application. Integrated with CloudFront, it protects your site at the edge of the network.
What is a WAF
A WAF (Web Application Firewall) is a firewall specialized in web applications. Unlike Security Groups (Chapter 4), which filter by ports and IPs at the network level, the WAF understands HTTP and examines the content of web requests to detect and block attacks.
Internet traffic ┌─────────────────────────┐ │ ✓ legitimate users │ │ ✗ malicious bots │ ──► [ WAF ] ──► only legitimate traffic passes ──► your website │ ✗ attack attempts │ (filters) │ ✗ abusive scrapers │ └─────────────────────────┘
Analogy: the WAF is like the security bouncer at a nightclub. He checks everyone who wants to enter: lets in regular customers, but stops those looking for trouble (those carrying weapons, the troublemakers). He inspects who enters and with what intention, not just the door.
What does a WAF protect against?
The WAF defends against the most common web application attacks, many of them from the famous OWASP Top 10 (the list of the most critical web vulnerabilities):
- SQL Injection: attempts to "sneak in" malicious commands to your database through forms or URLs.
- Cross-Site Scripting (XSS): attempts to inject harmful scripts into your website to attack other users.
- Malicious bots: automated programs that crawl, copy content, or look for vulnerabilities.
- Brute force attacks: repeated attempts to guess passwords.
- Abusive request spikes: too many requests from the same source (rate limiting).
How it works: the rules
The WAF works with rules that define what to block and what to allow. There are two ways to get them:
AWS managed rules (the easiest)
AWS offers predefined rule groups maintained by their security experts. By enabling them, your website is protected against the most common threats, without you having to be a security expert. AWS constantly updates them as new threats appear.
To start, this is recommended: enable AWS managed rules (for example, the "Core" set and the "known bad inputs" set) and you'll have solid protection with very little effort.
Custom rules (your own)
You can also create your own rules for your specific case:
- Block or allow by IP: ban specific IPs or allow only certain ones (a blacklist or whitelist).
- Block by country (geo): if your business is only national, you can block traffic from countries where you only receive attacks.
- Rate limiting: "if an IP makes more than 1,000 requests in 5 minutes, block it." Excellent against bots and brute force.
- Filter by content: block requests with suspicious patterns in the URL, headers, etc.
Rate limiting rule:
Does an IP make more than 1000 requests in 5 min?
→ YES: temporarily block it (probably a bot)
→ NO: let it throughWhy integrate it with CloudFront
Here's the advantage of combining WAF with CloudFront (subchapter 16.2): by putting it in the CDN, filtering happens at the edge of the network (the edge locations), far from your application.
Attacker ──► Edge location (WAF filters here) ──✗ blocked
│
User ───► Edge location (WAF approves) ──✓──► your applicationDouble benefit:
- Malicious traffic is blocked at the edge, before it travels to your server. Your application doesn't even notice the attack.
- Since filtering is distributed worldwide, it absorbs large-scale attacks without saturating your origin.
Real world example: an online store suffers a bot attack trying to test thousands of stolen cards on its payment form. With WAF integrated into CloudFront, a rate limiting rule detects massive requests from the same IPs and blocks them at the edge locations, far from the store. The store's servers continue to function normally for real customers, without even noticing the attack.
WAF and the others: a layered defense
The WAF does not replace other protections; it adds to them, forming a defense in depth (a concept we will expand on in Chapter 23):
| Layer | What it protects | Level |
|---|---|---|
| WAF | Web application attacks (SQL injection, XSS, bots) | Application (HTTP) |
| Security Groups (Ch. 4) | Which ports/IPs reach your resources | Network |
| Network ACLs (Ch. 6) | Traffic at the subnet level | Network |
| IAM (Ch. 7) | Who can do what in AWS | Identity |
Each layer covers a different aspect. Together, they make your application much harder to attack.
What you should remember
- A WAF (Web Application Firewall) is a firewall that understands HTTP and filters malicious web traffic by examining the content of requests (unlike Security Groups, which filter by network). It's like the "security bouncer" of your website.
- It protects against common OWASP Top 10 attacks: SQL injection, XSS, malicious bots, brute force, and abusive spikes.
- It works with rules: AWS managed rules provide solid protection without being an expert (recommended to start), and you can add custom rules (block by IP/country, rate limiting...).
- Integrated with CloudFront, it filters malicious traffic at the edge of the network, far from your application, and absorbs large-scale attacks.
- The WAF is part of a layered defense along with Security Groups, Network ACLs, and IAM.
You've finished Chapter 16! Your application is now fast, secure, and protected for the internet. In Chapter 17 we close Part IV with containers on AWS: Docker, ECR, ECS, and EKS, another fundamental way to deploy applications.
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
