After the Solutions Architect path (subchapter 32.2), there is another high-level certification that is especially relevant for those following this book, because it connects with its very spirit: the AWS Certified DevOps Engineer – Professional. While the architect focuses on designing systems, the DevOps engineer focuses on automating, deploying, and operating those systems efficiently. This is the certification that validates the automation, CI/CD, and infrastructure as code practices we have worked on throughout the book.
What is DevOps (a review)
Remember the DevOps culture that permeates this book: the union of development (Dev) and operations (Ops) to build, deploy, and operate software in a fast, automated, and reliable way. Instead of one team building and another deploying "over the wall," DevOps integrates everything with automation, infrastructure as code, and continuous improvement.
DevOps = automate and unify the entire cycle: build → deploy → operate → monitor → improve (all automated, fast, and reliable, with no "walls" between teams)
Everything you have learned about Terraform (Parts II-V), CI/CD (Chapter 22), observability (Chapter 24), and automation is, in essence, DevOps.
What is the DevOps Engineer Professional certification
The AWS Certified DevOps Engineer – Professional is an advanced (professional) level certification that validates that you know how to apply DevOps practices in AWS: automate deployments, manage infrastructure as code, set up CI/CD pipelines, monitor systems, and operate them efficiently and reliably.
What the DevOps Engineer Professional validates: ✓ Deployment automation (CI/CD) ✓ Infrastructure as code (Terraform, the whole book!) ✓ Monitoring and observability (Ch. 24) ✓ Operating systems reliably and efficiently ✓ Automating security and compliance
It is at the professional level (advanced and demanding, like the Solutions Architect Professional), and demonstrates a deep mastery of the automated operation of systems in AWS.
Analogy: if the Solutions Architect (subchapter 32.2) is the architect who designs the building, the DevOps Engineer is the engineer of the construction and automated maintenance: the one who ensures that the building is constructed efficiently, repeatably, and without errors, and that it works perfectly day by day (with systems that monitor, repair, and update themselves). Both are essential and complementary: one designs, the other ensures it is built and operated flawlessly.
Why it is the "spirit of the book" certification
This certification is especially aligned with this book because it covers precisely the practices we have worked on chapter by chapter:
What the book teaches → What DevOps Pro evaluates ───────────────────────────────────────────────────────────── Terraform / IaC (Parts II-V) → infrastructure as code CI/CD for Terraform (Ch. 22) → automation pipelines Observability (Ch. 24) → monitoring and alerts Automated security (Ch. 23) → security and compliance as code Multi-account, deployments... → operate at scale reliably
If you have internalized the philosophy of automating everything, treating infrastructure as code, and operating with observability, you already think like a DevOps engineer. This certification proves it.
Architect or DevOps? (not mutually exclusive)
A common question: which to choose, Solutions Architect or DevOps Engineer? The answer depends on your focus, but they are not mutually exclusive (many professionals have both):
| Solutions Architect | DevOps Engineer | |
|---|---|---|
| Focuses on | Designing architectures | Automating and operating systems |
| Key question | What do I build and how do I combine it? | How do I deploy and operate it automatically and reliably? |
| Affinity with the book | High (Well-Architected, Ch. 27) | Very high (IaC, CI/CD, observability) |
Architect: the WHAT and the HOW of design DevOps: the HOW of automation and operation → many valuable professionals master BOTH
💡 Recommendation: if you are attracted to designing systems, prioritize the Architect path; if you are attracted to automating and operating (which is very much the spirit of this book), the DevOps path will suit you perfectly. Ideally, over time, both complement each other.
How to prepare for it
- Master infrastructure as code (Terraform): it is central. Everything in Parts II-V is directly applicable.
- Understand CI/CD well (Chapter 22): pipelines, automated deployments, deployment strategies.
- Handle observability (Chapter 24): logs, metrics, alarms, traces.
- Practice real automation: set up pipelines, write infrastructure as code, configure monitoring. Real experience is key for a professional certification.
Real world example: an engineer who has worked extensively with Terraform, CI/CD pipelines, and monitoring wants to officially validate their DevOps profile to access better positions. They prepare for the DevOps Engineer Professional: since they already applied these practices in their daily work (infrastructure as code, automated deployments, observability), studying mainly consists of deepening and organizing what they already did, plus practicing scenarios. They pass, and their professional level certification positions them as a highly sought-after senior DevOps profile. For someone who has followed the philosophy of this book, this certification is the natural culmination of their technical profile.
What you should remember
- DevOps unites development and operations to build, deploy, and operate software in a fast, automated, and reliable way; it is the spirit that runs through this entire book (Terraform, CI/CD, observability, automation).
- The AWS Certified DevOps Engineer – Professional is an advanced level certification that validates that you know how to apply DevOps practices in AWS: deployment automation, infrastructure as code, CI/CD, monitoring, and reliable operation.
- If the Solutions Architect is the architect who designs, the DevOps Engineer is the engineer who automates construction and operation. Complementary.
- It is the certification most aligned with this book, because it covers exactly what has been worked on: IaC (Parts II-V), CI/CD (Ch. 22), observability (Ch. 24), automated security (Ch. 23).
- 💡 Architect vs DevOps is not exclusive: choose according to whether you are more attracted to designing or automating/operating; many professionals master both. Prepare by mastering Terraform, CI/CD, and observability, and by practicing for real.
In the next subchapter we will look at certifications to deepen in specific areas: the Specialty certifications.
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
