We have reached Chapter 34, the last chapter of the book. Throughout these pages, you have traveled a long road: from what the cloud is to designing complete architectures with AWS and Terraform. But there is a truth you must internalize: learning does not end here. The cloud is constantly evolving, and the best professionals are those who never stop learning. This chapter gives you the resources and community to keep growing. We start with the two most reliable and official sources of learning: the AWS documentation and AWS Skill Builder.
The reality: the cloud never stops changing
Before the resources, assume this key idea: AWS continuously launches services and improvements. What you know today is an excellent foundation, but in a while there will be new developments. That’s why, rather than “finishing learning,” the goal is to know where to keep learning when you need it.
It's not about knowing EVERYTHING (impossible), but about knowing WHERE to find reliable information when you need it.
Analogy: being good in the cloud is not like memorizing an entire dictionary (impossible and absurd), but like knowing how to use the dictionary very well: when you need a word, you know exactly where to look and how to interpret it. The resources in this chapter are your cloud “dictionary”: you don’t memorize them, you consult them skillfully.
The official AWS documentation
The official AWS documentation is the most complete, accurate, and up-to-date source on any service. Every AWS service has its detailed documentation: what it does, how it’s used, all its options, examples... It is the definitive reference: when you have a question about how something works in AWS, the official documentation is the source of truth.
Official AWS documentation: ✓ The MOST reliable and up-to-date source (written by AWS) ✓ Covers ALL services in detail ✓ Even experts go there to confirm details
💡 Don’t be afraid of the documentation. At first it may seem dense, but it is your best ally. Learning to navigate and read it is a key professional skill: good engineers consult the official documentation constantly, they don’t know everything by heart. Get used to turning to it whenever you have a question.
⚠️ For the same reason, beware of outdated information in old blogs or forums: in the cloud, something written years ago may be obsolete. When in doubt, always cross-check with the official documentation, which is what AWS keeps up to date.
AWS Skill Builder: the official training platform
AWS Skill Builder is the official AWS training platform: courses, exercises, and resources to learn AWS, created by AWS itself. We have mentioned it several times in the book (for example, when talking about how to prepare for certifications in Chapter 32), and now is the time to introduce it properly.
AWS Skill Builder = the "official school" of AWS: ✓ Courses on AWS services and topics (created by AWS) ✓ Material to prepare for CERTIFICATIONS (Ch. 32) ✓ Lots of free content + paid options for more ✓ Hands-on labs to learn BY DOING
It is especially useful for:
- Deepening your knowledge of specific services with structured courses.
- Preparing for certifications (remember all of Chapter 32): there is official material specific to each one.
- Practicing with labs where you use real AWS.
💡 It combines very well with this book: what you have learned here gives you the foundation and the big picture; Skill Builder allows you to go deeper into specific topics and prepare for certifications with official AWS material.
How to use these official resources
A good way to take advantage of them:
- Specific question about how a service works? → Official documentation - Want to LEARN a topic or service in depth? → Skill Builder (courses) - Preparing for a certification? → Skill Builder (official material) - Want to practice? → Skill Builder (labs)
Real world example: someone who finished the book starts working with an AWS service that we only briefly covered here. Instead of feeling lost, they know exactly what to do: for specific questions (“what options does this configuration have?”), they go to the official documentation and find the precise and up-to-date answer. When they want to master that service in depth, they take a course on AWS Skill Builder. And when they decide to get certified, they use the official Skill Builder material to prepare. Thanks to knowing where to look, they never get stuck: the book gave them the foundation, and these official resources allow them to keep growing independently on any new topic. That autonomy is what makes them a professional who doesn’t depend on “someone teaching them.”
What you should remember
- Learning doesn’t end with the book: the cloud constantly evolves, and the best professionals never stop learning. The goal is not to know everything, but to know where to find reliable information. Like knowing how to use the dictionary well, not memorizing it.
- The official AWS documentation is the most complete, accurate, and up-to-date source (written by AWS): the definitive reference for any question. 💡 Get used to consulting it; ⚠️ beware of old information in blogs and always cross-check with the official one.
- AWS Skill Builder is the official AWS training platform: courses, hands-on labs, and material to prepare for certifications (Ch. 32), with lots of free content. The “official school” of AWS.
- Use them according to your needs: documentation for specific questions; Skill Builder to learn in depth, practice, or get certified. They combine perfectly with the foundation this book has given you.
In the next subchapter we will look at more informal but very valuable resources to keep you up to date and continue learning: YouTube and podcasts.
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
