We start Part IV with a leap: from single servers to scalable architectures. The first key piece is the load balancer, the component that distributes traffic among several servers. In this chapter, you’ll learn how to use it and, in this first subchapter, how to choose between the two main types in AWS: the Application Load Balancer (ALB) and the Network Load Balancer (NLB).
The problem: one server is not enough
In Chapter 12 you set up one server. But what if...?
- You get a lot of traffic and one server can’t handle it.
- That server goes down: your entire website stops working.
The solution is to have multiple servers and put something in front that distributes requests among them. That “something” is the load balancer.
What is a load balancer
A load balancer is like the maître d’ at a busy restaurant: at the door, assigning each arriving customer to a free table, distributing them among all the waiters so none get overwhelmed.
┌─────────────┐
Users ────► │ Load Balancer │
└──────┬──────┘
┌────────────┼────────────┐
▼ ▼ ▼
Server 1 Server 2 Server 3Immediate benefits:
- Distributes the load: no server gets overwhelmed.
- High availability: if a server goes down, the balancer stops sending it traffic and uses the others. Users don’t even notice.
- Single entry point: users access a single address, without knowing how many servers are behind it.
The two main types in AWS
AWS offers several balancers, but the two you need to know are the ALB and the NLB. The key difference is at what level they operate.
Application Load Balancer (ALB)
Works at the application level (layer 7): understands HTTP and HTTPS. This means it can “read” web requests and make smart decisions based on their content:
- Send
/api/*to some servers and/images/*to others (path-based routing). - Send
store.mydomain.comandblog.mydomain.comto different groups (host-based routing). - Manage HTTPS certificates, headers, session cookies, etc.
It’s the default balancer for web applications and APIs.
Network Load Balancer (NLB)
Works at the network level (layer 4): only understands TCP/UDP, without looking at the content. In return, it’s extremely fast and supports huge amounts of traffic with minimal latency.
- Doesn’t read HTTP; just distributes network connections.
- Ideal for extreme performance, protocols that aren’t HTTP (for example, databases, online games, IoT, streaming) or when you need a fixed IP.
Analogy to distinguish them
- The ALB is like a hotel receptionist who reads your request (“I want the spa,” “I’m looking for the restaurant”) and directs you to the right place. Smart, but that reading takes a moment.
- The NLB is like a subway turnstile: it doesn’t care who you are or where you’re going, it just lets people through as fast as possible. It’s incredibly fast, but “doesn’t think.”
Comparison table
| Feature | Application Load Balancer (ALB) | Network Load Balancer (NLB) |
|---|---|---|
| OSI Layer | 7 (application) | 4 (network) |
| Protocols | HTTP, HTTPS | TCP, UDP, TLS |
| Intelligence | High (routes, hosts, headers) | Low (just distributes connections) |
| Speed | Very good | Extreme (minimal latency) |
| Fixed IP | No (DNS name) | Yes (can have static IP) |
| Typical use case | Websites and APIs | Extreme performance, non-HTTP |
| SSL Certificates | Yes (ACM, Chapter 16) | Yes (TLS) |
Which one should I choose?
The practical rule to start is simple:
- Is it a web application or an API (HTTP/HTTPS)? → ALB. This is the case for 90% of projects. It’s what you’ll use almost always.
- Do you need maximum performance, a fixed IP, or work with protocols that aren’t HTTP? → NLB.
For beginners: focus on the ALB. It’s what you’ll use in the vast majority of web applications, and it’s what we’ll cover in the rest of the chapter (Target Groups, listeners, autoscaling). The NLB will be there for special high-performance cases.
What you should remember
- A load balancer distributes traffic among several servers: it provides scaling and high availability (if one goes down, it uses the others).
- The ALB (layer 7) understands HTTP/HTTPS and is smart: routes by path, host, headers. It’s the standard for websites and APIs.
- The NLB (layer 4) only understands TCP/UDP, is extremely fast and allows fixed IP. For extreme performance or non-HTTP protocols.
- Practical rule: web application? → ALB. Special performance or non-HTTP cases → NLB.
In the next subchapter we’ll see how the balancer knows which servers to send traffic to: the Target Groups, the listeners, and the rules.
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
