AWS Cloud Engineer: Complete Guide to AWS Services (2026)

With over 200 AWS services available, it can be overwhelming when you're just starting out - or even if you have some experience in the cloud.

I faced the same challenges when I started my journey. I'd watch one tutorial recommending a specific approach, only to find another expert suggesting something completely different. It was confusing and frustrating.

After a decade of working in tech across multiple roles - Cloud Architect, Cloud Engineer, Software Developer, and DevOps - I've gained a unique perspective on how AWS services actually fit together in real-world applications.

Here's what I've noticed: Whether I'm answering questions from students, former colleagues, or people interested in the cloud, they're not just confused about what to learn. They want to understand how these services work together to build actual solutions that solve real business problems.

That's what this guide is about. Instead of just telling you to "learn S3" or "learn EC2," I'm going to explain how these services fit into the bigger picture.

What We'll Cover

1. Core Networking Fundamentals - How the internet works with AWS
2. Static Content Hosting - S3, CloudFront, Route 53
3. Compute Services - Lambda, EC2, ECS
4. Databases - RDS and DynamoDB
5. AI and Machine Learning - Bedrock and SageMaker
6. Security - VPC and IAM
7. Monitoring - CloudWatch and CloudTrail

Let's start with the absolute basics.

Part 1: Core Networking Fundamentals

Every device connected to the internet needs an IP address. This is fundamental to everything.

When we talk about IP addresses, we're dealing with two types:

• IPv4 addresses (the original format)
• IPv6 addresses (created because we ran out of IPv4 addresses)

Since IP addresses are just numbers and humans aren't great at remembering them, we use domain names instead. This is where DNS (Domain Name System) comes in.

Route 53: AWS's DNS Service

In AWS, Route 53 handles DNS. It converts friendly domain names (like studytech.ai) into the IP addresses that computers understand.

Route 53 is smarter than a simple lookup service. If you're running your website in multiple locations around the world, Route 53 can automatically send users to the closest or fastest location.

How Data Moves: Packets and TCP/IP

When you're using the internet - loading a website or sending an email - everything moves as packets. Your data isn't moving as one big chunk. An email gets broken down into small pieces called packets.

Each packet carries:

• Your actual data
• The destination IP (where it's going)
• The source IP (where it came from)

TCP/IP manages all of this:

• TCP handles breaking down your data and making sure it arrives correctly
• IP makes sure it gets to the right destination

VPC: Your Private Network in AWS

AWS networks have both public and private spaces. When you create your network in AWS - what we call a VPC (Virtual Private Cloud) - you divide it into different sections called subnets.

Public subnets have a direct connection to the internet through an Internet Gateway. This is where you put your web servers that need to accept traffic from users.

Private subnets have no direct path to the internet. This is where you put sensitive resources like databases. No one from the outside can directly access them.

But what if your private resources need to reach the internet (for updates, for example)? That's where a NAT Gateway comes in. It allows outbound traffic but blocks inbound - a one-way street.

Security Groups vs NACLs

AWS gives you two tools to control traffic:

Security Groups control traffic for individual resources (like a specific EC2 server). They're like a firewall around each instance. You specify exactly what traffic can reach that server.

For a web server, you typically allow:

• HTTP on Port 80
• HTTPS on Port 443
• SSH on Port 22 (for management)

Network ACLs (NACLs) work at the subnet level. The key difference: NACLs can explicitly block traffic, while Security Groups can only allow traffic.

Together, they create multiple layers of security.

Part 2: Static Content Hosting and Delivery

When someone types your website address into their browser, where does the content actually come from?

S3: Simple Storage Service

At the heart of most AWS platforms is S3. This is where your website files live - every image, HTML file, JavaScript code, and CSS style.

S3 organizes files into buckets (like root folders). What makes S3 powerful:

• Versioning: S3 keeps track of all previous versions of your files. If you accidentally upload the wrong file, you can roll back instantly.
• Reliability: S3 has been around since AWS began and is incredibly reliable
• Scalability: It can handle files of any size

CloudFront: Content Delivery Network

Having files stored isn't enough - users need to access them quickly. CloudFront is AWS's content delivery network (CDN).

Instead of serving content from one location, CloudFront copies your files to data centers around the world. AWS has over 450 points of presence (Edge locations) across six continents.

Real-world example: When you stream a show on Netflix (which uses AWS), you're not getting that video from one central server. If you're watching in Sydney, you're streaming from an Australian data center. Someone watching the same show in London gets it from a UK data center.

CloudFront also provides security features:

• Signed URLs for controlling access
• Integration with AWS WAF (Web Application Firewall)

How It All Fits Together

1. User types your domain name
2. Route 53 converts it to an IP address
3. Static content (images, CSS, JS) is stored in S3
4. CloudFront delivers it from the nearest Edge location
5. Dynamic requests go to your backend servers

The beautiful thing: whether you have 10 visitors or 10 million, these services automatically scale.

Part 3: Running Backend Services (Compute)

Every application has two parts:

• Frontend: What users see and interact with (buttons, images, text)
• Backend: What processes information when users take actions

AWS provides three main ways to handle backend operations.

Option 1: Serverless with Lambda and API Gateway

When we say "serverless," there are still servers - AWS just manages them for you.

API Gateway receives requests and acts like a receptionist, directing them to the right Lambda function.

Lambda functions wake up, process the request, and shut down - all in milliseconds. You only pay for when the function is actually running.

When to use serverless:

• Unpredictable workloads (100 visitors one hour, 10,000 the next)
• Specific tasks like image processing
• Teams that want to focus on features, not infrastructure

Option 2: EC2 (Elastic Compute Cloud)

EC2 gives you virtual servers in AWS's data centers. You have complete control - choose the operating system, install any software, configure security settings.

The "elastic" part is crucial: Scale up during Black Friday, scale down when the rush is over. You're not locked into hardware you initially bought.

When to use EC2:

• Applications requiring specific configurations
• Legacy software with particular dependencies
• When you need complete control over your environment

The trade-off: You're responsible for OS updates, security patches, and monitoring.

EC2 integrates with:

• Load Balancers (ELB): Distribute traffic across multiple instances
• Auto Scaling: Automatically launch/remove instances based on demand
• Multiple Availability Zones: If one data center has issues, your app keeps running

Option 3: Containers with ECS

ECS (Elastic Container Service) sits between serverless and traditional EC2.

Containers solve a fundamental problem: getting applications to run consistently across different environments. A container packages your application code with everything it needs to run.

When to use containers:

• Microservices architecture (breaking a large app into smaller pieces)
• When you need more control than Lambda but less management than EC2
• Applications that need to scale individual components independently

Part 4: Storing and Managing Data

S3 vs Databases

S3 (Object Storage) is perfect for files - images, videos, documents. Each file is stored as a complete object accessed via URL.

Databases are for data that needs to be queried, updated frequently, and has relationships between pieces.

RDS: Relational Databases

Amazon RDS manages traditional SQL databases (MySQL, PostgreSQL, etc.). SQL databases organize data in tables with clear relationships.

Example: In an e-commerce site, you need to track how orders relate to customers, how products relate to categories, how inventory relates to sales.

RDS handles backups, security patches, and scaling automatically.

DynamoDB: NoSQL Database

DynamoDB is built for speed and scale - single-digit millisecond responses no matter how big your application grows.

Instead of rigid tables, it's more flexible. Perfect for data that doesn't fit neatly into tables or needs extremely fast access.

Example: Tracking delivery driver locations that update every few seconds.

When to Use Each

• Complex queries and relationships? → RDS
• Extreme speed and scalability? → DynamoDB
• Both? Many applications use both together

Part 5: AI and Machine Learning

Understanding AI is becoming non-negotiable for engineers in 2026 and beyond. AWS has made it easier than ever with two key services.

Amazon Bedrock

Bedrock is your shortcut to using advanced AI without building from scratch. It gives you access to pre-built models from Anthropic, Meta, and others.

Example: Add a chatbot to your application. Pick a pre-trained model, train it on your company's data (product info, FAQs), and deploy. Your data stays within your AWS environment.

RAG (Retrieval Augmented Generation): Your AI can pull real-time data from your databases while answering questions - like checking if a product is in stock.

Amazon SageMaker

SageMaker is for building, training, and deploying your own machine learning models.

Use cases:

• Predicting user behavior
• Detecting fraud
• Recommending products

Example: Predict which customers are likely to buy certain products based on browsing habits. Train the model, deploy it, and get real-time predictions.

Why AI Matters Now

• E-commerce platforms recommend products with AI
• Social media shows you relevant content with AI
• Logistics companies optimize delivery routes with AI
• Healthcare predicts patient risks with AI

Both Bedrock and SageMaker integrate seamlessly with other AWS services - pulling data from DynamoDB, triggered by Lambda functions, working alongside EC2.

Part 6: Security (The Most Important Part)

Cloud security is in extremely high demand. As businesses move to the cloud, the need for security experts who understand cloud environments has grown - but availability hasn't kept up.

Every piece of your architecture needs security at its core from the beginning.

VPC Security Deep Dive

Your VPC controls exactly how your application's networking works.

Subnets:

• Public subnets for internet-facing resources
• Private subnets for sensitive resources

NAT Gateway: Allows private resources to reach the internet for updates, but never allows incoming connections. One-way street.

Network ACLs: Firewall for entire subnets. Can explicitly block traffic.

Security Groups: Firewall for individual resources. Control exactly which traffic reaches each instance.

IAM: Identity and Access Management

While VPC controls network access, IAM controls who can access what within your AWS environment.

Principle: Give everyone exactly the access they need - nothing more.

Example: A Lambda function that analyzes customer feedback with Bedrock AI. Create an IAM role that allows that specific Lambda to use that specific AI model - but nothing else.

Defense in Depth

Multiple security layers:

1. VPC isolates your network
2. Subnets separate public from private
3. NAT Gateways control internet access
4. Network ACLs protect at subnet level
5. Security Groups protect at resource level
6. IAM ensures minimal permissions

If an attacker gets past one layer, they still face all the others.

Part 7: Monitoring and Auditing

After building everything, you need to know what's actually happening.

CloudWatch: Operational Monitoring

CloudWatch collects performance metrics, logs, and events from all your AWS services.

What you can do:

• Create dashboards showing important metrics
• Set up alerts when something isn't working
• Trigger automated responses (auto-scaling, recovery)

Example alerts:

• API response times getting slow
• Database running out of connections
• Lambda functions experiencing errors

CloudTrail: Audit Trail

CloudTrail records every API call made in your AWS account. Anytime someone makes a change, CloudTrail logs it.

• Who changed what
• When they changed it
• What exactly was modified

Crucial for troubleshooting: CloudWatch shows operational impact, CloudTrail helps track down what changes caused issues.

How These Services Work Together

Let's trace a request through a complete application:

1. User types your domain → Route 53 resolves it
2. Static content served from S3 via CloudFront
3. Dynamic request hits API Gateway or Load Balancer
4. Lambda or EC2 processes the request
5. Data retrieved from RDS or DynamoDB
6. AI features powered by Bedrock or SageMaker
7. Everything secured by VPC and IAM
8. Monitored by CloudWatch and CloudTrail

While AWS offers hundreds of services, this core set is what you'll use consistently in day-to-day work.

Ready to Master AWS?

Understanding how these services fit together is crucial - but there's a difference between knowing the concepts and being ready for certification exams.

StudyTech identifies exactly where your knowledge gaps are.

Our AI assessment tests you across all AWS domains, then creates a personalized study plan focused only on what you need to learn. No wasting time on concepts you already understand.

Here's what you get:

• 10-minute gap assessment - Know your weak areas instantly
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• AI-generated practice questions - Targeted to your specific gaps
• Real-time readiness score - Know exactly when to book your exam

Most users go from beginner to certification-ready in 4-6 weeks.

Over 1,000 learners are already using StudyTech to master AWS services faster. Your cloud engineering career starts with knowing exactly what you need to study.

Originally based on a video from Tech With Soleyman's YouTube channel, adapted for StudyTech readers.