You already know SQS (queues) and SNS (notifications). Now we’ll look at EventBridge, a more modern and powerful event service that takes messaging ideas a step further. It’s the backbone of many event-driven architectures in AWS.
What is EventBridge
EventBridge is an event bus: a kind of “central highway” through which events from your entire application and AWS services travel. Services publish events to the bus, and EventBridge automatically routes them to the appropriate destinations according to rules.
Event sources EventBridge Destinations
┌──────────────┐ ┌──────────────────┐ ┌──────────────┐
│ Your app │ ──────► │ Event Bus │ ─────► │ Lambda │
│ AWS services │ ──────► │ (+ rules that │ ─────► │ SQS Queue │
│ SaaS Apps │ ──────► │ filter and route)│ ────► │ SNS Topic │
└──────────────┘ └──────────────────┘ │ Step Functions│
└──────────────┘Analogy: EventBridge is like the mail sorting system in a large office. Letters (events) arrive from many senders. A sorter (the rules) reads each letter and sends it to the correct department based on its content. No one has to deliver by hand: the system routes everything automatically according to predefined rules.
The key piece: rules
The heart of EventBridge is the rules. A rule says: “when an event matches this pattern, send it to this destination.” EventBridge examines each event and, if it matches a rule’s pattern, routes it to its destination.
Rule: "if the event is an order over €1000"
→ send to the manual-review Lambda
Rule: "if the event is a new registered user"
→ send to the welcome SQS queueThe interesting thing is that rules filter by the content of the event. An event is basically a JSON with data, and the rule can look at that data:
{
"source": "store.orders",
"detail-type": "OrderCreated",
"detail": {
"amount": 1500,
"country": "ES"
}
}A rule could say: “send to manual review the OrderCreated events with amount greater than 1000.” EventBridge filters and routes automatically, without you writing any routing code.
EventBridge vs SNS: how are they different?
It’s the natural question: SNS also broadcasts messages to multiple destinations. Why EventBridge? The key differences:
| SNS | EventBridge | |
|---|---|---|
| Routing | All subscribers receive everything | Advanced filtering by content: each destination receives only what interests it |
| Sources | What you publish | Your app + many AWS services + external SaaS apps |
| Rules | Basic filtering | Powerful rules based on content patterns |
| Focus | Fast notifications, high throughput | Smart event routing, integration |
In summary: SNS is simple and super-fast for broadcasting; EventBridge is more sophisticated, with advanced content filtering and native integration with dozens of AWS services and external applications.
Practical rule: use SNS when you just need to broadcast a message to several destinations simply and quickly. Use EventBridge when you need to route events intelligently based on their content, or integrate events from AWS services and SaaS applications.
A huge advantage: events from AWS services themselves
EventBridge has a superpower: many AWS services emit events to EventBridge automatically. This lets you react to things happening inside AWS without programming anything special:
- “When an EC2 instance changes state” → trigger a Lambda.
- “When an object is uploaded to S3” → route to a destination.
- “When a service task finishes” → notify a system.
Real-world example: you want to receive an alert in Slack every time someone starts a large (expensive) EC2 instance. You create a rule in EventBridge: “when an event indicates a large instance has been launched, send it to a Lambda that notifies Slack.” You don’t have to program any monitoring system: EventBridge already receives those AWS events, you just define the rule.
Schedules: scheduled tasks
EventBridge also allows you to schedule events in time (what used to be called “CloudWatch Events”). You can trigger an action on a schedule, like a recurring task:
"Every day at 02:00" → trigger the backup Lambda "Every Monday at 09:00" → trigger the weekly report
It’s the serverless way of doing the classic server “cron”: tasks that run on a schedule, without needing a server running and watching the clock.
What you should remember
- EventBridge is an event bus: a “central highway” where services publish events and EventBridge routes them to their destinations according to rules.
- Rules filter by the content of the event (“if amount > 1000 → manual review”) and route automatically, with no routing code.
- Compared to SNS: EventBridge offers advanced content filtering and native integration with many AWS services and SaaS apps. Use SNS for simple, fast broadcasting; EventBridge for smart routing and integrations.
- Superpower: many AWS services emit events to EventBridge, letting you react to what happens inside AWS without programming monitoring.
- With schedules, EventBridge runs scheduled tasks (the serverless “cron”).
In the last subchapter of this chapter, we’ll bring all these pieces together (SQS, SNS, EventBridge) into the major patterns they enable: pub/sub, decoupling, and saga.
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
