So far, we’ve looked at resources for learning on your own: documentation, courses, videos, podcasts. But there’s something none of these give you: connection with other people who are on the same path as you. Communities—groups of people interested in AWS and the cloud who share knowledge, questions, and experiences—are one of the most valuable resources of all. Because in the cloud, as in almost everything, you’re not alone, and surrounding yourself with a community accelerates your growth in ways that solo study cannot.
Why communities matter so much
Learning alone has its limits. A community gives you unique things:
What a community gives you (and solo study doesn’t): ✓ HELP when you get stuck (someone’s already been there) ✓ Learning from the EXPERIENCE of others (their successes and mistakes) ✓ Staying motivated (you’re not alone on the journey) ✓ Finding out about news and opportunities ✓ Making professional contacts (networking)
Analogy: learning alone is like climbing a mountain by yourself; with a community, you climb alongside other hikers. When you get stuck at a tough spot, someone who’s already passed it tells you which way to go; when you get discouraged, the group cheers you on; and you share the journey, the progress, and the motivation. You go further and enjoy the trip more. In the cloud, the community is that group of hikers that makes the path easier and more enjoyable.
Reddit (r/aws): questions, news, and discussion
Reddit is a great platform for online communities, and r/aws is its community dedicated to AWS: a huge place where thousands of people ask questions, share news, debate, and help each other. It’s an excellent site for:
On r/aws (the AWS community on Reddit) you can: ✓ Ask questions and get answers from experienced people ✓ Find out about AWS news and updates ✓ Read other people’s questions and solutions (you learn a lot just by reading) ✓ See debates about best practices and real-world experiences
💡 Even just reading r/aws teaches you a ton: you see the real problems people have, how they’re solved, which updates matter, and which topics are trending. It’s a window into the day-to-day of the AWS community.
AWS Community Builders: the official community program
AWS Community Builders is an official AWS program that recognizes and supports people who share knowledge about AWS with the community (writing, giving talks, creating content, helping others, etc.). It’s AWS’s way of recognizing and connecting those who actively contribute to the community.
AWS Community Builders = official program for those who SHARE AWS knowledge with the community. ✓ Official recognition from AWS ✓ Connection with others who share and teach ✓ Access to resources and the “builders” community
It’s not something for day one (it’s for when you already have knowledge and want to share it), but it’s good to know it exists: it shows that contributing to the community has value and recognition, and it can be a motivating mid-term goal.
💡 Sharing what you know is one of the best ways to learn. When you explain something to others (in a forum, a blog, a talk), you understand it much better yourself. Programs like Community Builders reward that attitude, but you can start sharing right now, at your level: answering a question from someone who knows less than you is already contributing.
Other forms of community
Besides these, there are many other ways to connect:
- Local AWS groups / meetups (events in your city) - Communities on Discord, Slack, Telegram about cloud and DevOps - AWS events (re:Invent, regional summits, etc.) - Spanish-speaking communities, if you prefer your language
The important thing isn’t which one you choose, but to be part of one: connect with other people who share your interest.
Real-world example: someone who learned the cloud self-taught with the book sometimes feels alone in the process and gets stuck on problems with no one to ask. They decide to join the AWS community on Reddit (r/aws): they start just by reading (and learn a ton by seeing others’ questions and solutions), and little by little they get encouraged to ask when they get stuck, receiving help from experienced people. Over time, they themselves start to answer beginners’ questions (and discover that teaching helps them understand things better). They feel part of something, stay motivated, find out about news, and even make contacts. What was a solitary path becomes a journey with company, and they progress much faster and with more enthusiasm. The community transformed their way of learning.
What you should remember
- Communities provide what solo study can’t: help when you get stuck, learning from others’ experience, motivation, news, and contacts. Like climbing a mountain with company instead of alone.
- Reddit (r/aws): a great AWS community where people ask, share, and discuss. 💡 Just reading it already teaches you a lot (you see real problems and their solutions).
- AWS Community Builders: official AWS program that recognizes and connects those who share knowledge. It’s not for day one, but it’s a motivating goal; 💡 teaching is one of the best ways to learn, and you can start at your level now.
- There are many more ways: local meetups, Discord/Slack, events, Spanish-speaking communities... The important thing is to be part of one and not walk the path alone.
In the last subchapter of the book, we’ll bring together everything from this chapter into a final idea: how to stay up to date sustainably throughout your career. And we’ll close this journey together.
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
