We have reached Chapter 33: Projects to Consolidate, one of the most valuable in Part VIII. Because there is an inescapable truth in this craft: you learn by building. You can read the whole book and understand it, but until you build something real with your own hands, the knowledge doesn't fully settle. This chapter proposes four projects, from least to most complex, that tie together everything you've learned. We start with the most accessible and perfect for beginners: a serverless blog, where you'll combine S3, CloudFront, Lambda, and DynamoDB.
Why projects are so important
Before the project, let's understand its value. Reading and understanding is necessary, but insufficient: true knowledge is consolidated by applying it. Building a real project forces you to:
What building a project gives you (and theory doesn't): ✓ Bringing together many pieces you studied separately ✓ Facing real problems (and solving them) ✓ Truly understanding how services fit together ✓ Having something TANGIBLE to show (portfolio) ✓ Gaining real CONFIDENCE (not just theoretical)
Analogy: studying without building is like reading every book about how to ride a bike without ever getting on one. No matter how much you understand the theory of balance and pedaling, you won't know how to ride until you get on, wobble, maybe fall a couple of times, and finally succeed. Projects are "getting on the bike": where theoretical knowledge becomes real skill.
💡 About these projects: the idea is not to give you the exact code step by step (you'll find that in tutorials and documentation), but to show you what to build, which services to combine, and how the book's concepts fit together. The challenge of implementing it is precisely where you learn.
The project: a serverless blog
The first project is a serverless blog: a website where you can read articles, built without managing any servers (remember the serverless philosophy from Chapter 14). It's ideal to start with because it's simple, cheap (almost everything fits in the free tier), and combines several fundamental services in a clear way.
What you'll build: a blog where - visitors see the website (fast, worldwide) - articles are displayed - all WITHOUT servers to maintain (serverless)
The pieces and how they fit together
This project combines four services you already know, each with its role:
S3: hosting the website (static files)
S3 (Chapter 5) stores the website files (HTML, CSS, images... the "static" part that doesn't change). Remember that S3 can serve a static website directly. It's your blog's "warehouse": cheap, durable, and serverless.
CloudFront: delivering the website fast worldwide
CloudFront (subchapter 16.2), AWS's CDN, serves the website from locations close to each visitor, making it fast globally. It also provides HTTPS (remember ACM, subchapter 16.3). You put CloudFront "in front" of S3.
Lambda: the logic (the dynamic part)
Lambda (Chapter 14) runs the logic of the blog without servers: for example, a function that fetches the articles when someone requests them. It's the "dynamic" part (that does things), and runs only when needed, scaling automatically.
DynamoDB: storing the data (the articles)
DynamoDB (the serverless NoSQL database we saw in Chapter 8) stores the blog articles. It's serverless (fits perfectly with the rest), fast, and self-managed.
The complete architecture
This is how the four pieces fit together in a coherent system:
Visitor
│
▼
CloudFront (fast, global, HTTPS)
│
├──► S3 (the website: HTML, CSS, images)
│
└──► Lambda (the logic: fetch articles)
│
▼
DynamoDB (the stored articles)The visitor arrives via CloudFront; the website (from S3) loads quickly; when they request the articles, a Lambda fetches them from DynamoDB. All serverless: not a single server to maintain, it scales automatically, and costs very little (pay per use).
What you practice and consolidate
This project, despite its simplicity, makes you bring together and reinforce many key concepts:
Book concepts you consolidate: - S3 and static websites (Ch. 5) - CloudFront and CDN (Ch. 16) + HTTPS with ACM (Ch. 16.3) - Lambda and serverless (Ch. 14) - DynamoDB / NoSQL (Ch. 8) - And all deployed with Terraform! (Parts II-V)
💡 Do it with Terraform: deploy this entire project with Terraform (what you learned in Parts II-V), instead of manually through the console. This way you consolidate both AWS and infrastructure as code. It's the best possible practice: you build something real and do it professionally.
Real world example: someone who just finished the book wants to reinforce what they've learned and have something to show in interviews. They decide to build their personal blog as a serverless blog: storing their articles in DynamoDB, the logic in Lambda, the website in S3, and serving it with CloudFront, all defined in Terraform. While building it, they encounter real problems (how to connect CloudFront with S3, how to give Lambda permissions to read DynamoDB...) and by solving them truly understand how the pieces fit together, much better than just reading about it. They end up with a real, working, super cheap blog, and a portfolio project that proves they know how to build on AWS with Terraform. That "learning by doing" gives them a confidence that theory alone never could.
What you should remember
- You learn by building: reading and understanding is necessary but insufficient; knowledge is consolidated by applying it in real projects. Like learning to ride a bike by getting on, not just reading.
- The serverless blog is an ideal project to start with: simple, cheap (free tier), and combines fundamental services without managing servers.
- It combines four pieces: S3 (hosts the static website, Ch. 5), CloudFront (serves it fast and globally with HTTPS, Ch. 16), Lambda (dynamic logic, Ch. 14), and DynamoDB (stores the articles, Ch. 8).
- Architecture: the visitor arrives via CloudFront → website from S3 → for data, Lambda → which reads from DynamoDB. All serverless: scales automatically, costs little.
- 💡 Deploy it with Terraform (Parts II-V) to consolidate AWS and infrastructure as code at the same time, and have a portfolio project.
In the next subchapter, we'll take it up a notch with a more complete project: a REST API with containers (ECS Fargate, RDS, and ALB).
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
