So far we have seen several security services: SCP (limits), Config (compliance), GuardDuty (threats)... and there are still more. The problem is that, with so many tools, each with its own alerts, it's easy to get lost. How do you get a global view of your account's security status? That's what Security Hub is for: the "control panel" that centralizes all your security in one place.
The Problem: Too Many Sources of Alerts
Imagine the situation for a security team with everything we've seen so far:
GuardDuty → its threat findings AWS Config → its non-compliant resources Inspector → its detected vulnerabilities Macie → its sensitive data alerts ... and more services, each with its own console
Each service has its own screen, its own alert format, its own list. The team would have to check them one by one, without a consolidated view. It's exhausting and prone to missing something. You need a place where everything comes together.
What is Security Hub
AWS Security Hub is a service that aggregates and centralizes security findings from many services (GuardDuty, Config, Inspector, Macie...) into a single dashboard. Instead of looking in ten places, you look in just one, with everything unified and prioritized.
GuardDuty ─┐ Config ────┤ Inspector ─┼──► SECURITY HUB ──► a single panel with EVERYTHING, Macie ─────┤ (centralizes) unified and prioritized others ────┘
Analogy: Security Hub is like the central security control room of a large building. Instead of having one guard watching the basement cameras, another the entrance, and another the parking lot separately, all cameras and alarms go to a central room with a unified screen. From there, one person can see the status of the entire building at a glance and prioritize where to act.
What Security Hub Does
- Aggregates Findings from Everywhere
It collects alerts from different security services and puts them together in a common format. So, it doesn't matter if a problem was detected by GuardDuty or Config: you see it in the same list, described in a homogeneous way.
- Checks Security Standards
Security Hub can evaluate your account against recognized industry security standards, automatically running hundreds of best practice checks:
Standards it can check: - AWS Foundational Security Best Practices (AWS's basic best practices) - CIS AWS Benchmark (a highly recognized security standard) - PCI DSS (for those handling card payments) ...
It tells you, for example, "you comply with 87% of AWS security best practices; these are the points that fail." It's an excellent way to measure and improve your security posture.
- Prioritizes and Scores
Not all alerts are equally urgent. Security Hub prioritizes findings by severity and gives you an overall security score, so you know what to focus on first. Instead of drowning in a thousand alerts, you see what's most important to fix.
- Integrates for Response
Just like GuardDuty (subchapter 23.3), Security Hub's centralized findings can be connected with EventBridge + Lambda to automate responses, or with ticketing systems so the team can manage them in an organized way.
The Key Idea: A Single Source of Truth for Security
The great value of Security Hub is giving you a single source of truth about your security. Instead of asking yourself "am I secure?" and having to look in ten different consoles, you open Security Hub and see:
- Your overall security score.
- The most severe findings, from all services, prioritized.
- Your compliance level with industry standards.
- Which specific actions would improve your security.
Real-world example: The security manager of a company starts each morning by opening Security Hub. At a glance, they see: the security score rose to 91%, there are 3 new critical findings (one from GuardDuty about a suspicious credential, two from Config about misconfigured buckets), and 142 out of 158 CIS standard checks are met. In five minutes they know exactly where their security stands and what to address today, without opening half a dozen different consoles. That consolidated view is what makes their job manageable.
How It All Fits: The AWS Security Ecosystem
With Security Hub, the security pieces from this chapter form a coherent system:
SCP → set the maximum limits (Ch. 23.1)
IAM → controls who can do what (Ch. 7)
Config → monitors rule compliance (Ch. 23.2)
GuardDuty → detects active threats (Ch. 23.3)
Inspector/Macie/... → other specialized detections
│
▼
SECURITY HUB → CENTRALIZES everything in a unified panel (this subchapter)The specialized tools detect; Security Hub unifies and prioritizes. Together, they provide security you can actually manage.
What You Should Remember
- With many security services, each with its own alerts, it's easy to get lost; you need a centralized vision.
- Security Hub aggregates and centralizes security findings from many services (GuardDuty, Config, Inspector, Macie...) into a single panel, with a common format. Like the central control room of a building.
- Key functions: aggregates findings from everywhere, checks recognized security standards (AWS Best Practices, CIS, PCI DSS...), prioritizes and scores (so you know what to address first), and integrates to automate responses.
- Its great value: being a single source of truth about your security, so you know in minutes where you stand and what to improve, without looking in ten consoles.
- In the ecosystem: specialized tools detect, and Security Hub unifies and prioritizes.
In the next subchapter, we'll go down to the level of data protection: how to manage encryption keys with KMS.
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
