What Are the Core Services Behind Platforms Like AWS and Google Cloud?
Cloud platforms have become the backbone of modern software, yet many people only interact with them indirectly—through apps, websites, or internal tools—without understanding what actually runs behind the scenes. Providers like Amazon Web Services, Google Cloud Platform, and Microsoft Azure offer hundreds of services, but most real-world systems rely on a relatively small set of foundational building blocks. Understanding these core services helps demystify how cloud applications are designed, deployed, and scaled.
The three foundational layers of cloud services
At a high level, cloud platforms are built on three fundamental categories:
1. Compute (processing power) This is where your code runs. Compute services provide the CPU and memory needed to execute applications.
2. Storage (data persistence) These services store files, databases, and backups, ensuring data is durable and accessible.
3. Networking (connectivity) Networking services control how systems communicate—both internally and with the internet.
Nearly every cloud architecture is some combination of these three layers.
Compute services: running your applications
Compute is often the starting point for any cloud system.
Virtual machines (VMs)
- AWS: EC2
- GCP: Compute Engine
- Azure: Virtual Machines
VMs give you full control over an operating system. They are flexible and widely used for hosting applications, running services, and managing custom environments.
Containers and orchestration
- AWS: ECS, EKS
- GCP: Google Kubernetes Engine (GKE)
- Azure: AKS
Containers package applications with their dependencies. Orchestrators like Kubernetes manage scaling, deployment, and reliability across many containers.
Serverless compute
- AWS: Lambda
- GCP: Cloud Functions
- Azure: Functions
Serverless platforms let you run code without managing servers. You upload functions, and the platform automatically handles scaling and execution.
These three models—VMs, containers, and serverless—represent different trade-offs between control and convenience.
Storage services: managing data
Data is at the center of most applications, and cloud platforms offer multiple ways to store it.
Object storage
- AWS: S3
- GCP: Cloud Storage
- Azure: Blob Storage
Used for storing files like images, videos, backups, and logs. Highly durable and scalable.
Block storage
- AWS: EBS
- GCP: Persistent Disk
- Azure: Managed Disks
Attached to VMs like a hard drive. Used for databases or applications that need low-latency disk access.
File storage
- AWS: EFS
- GCP: Filestore
- Azure: Files
Shared file systems accessible by multiple machines.
Databases Cloud platforms provide managed database services:
- Relational: MySQL, PostgreSQL, SQL Server
- NoSQL: DynamoDB, Firestore, Cosmos DB
- In-memory: Redis, Memcached
Managed databases reduce operational overhead by handling backups, scaling, and maintenance.
Networking services: connecting everything
Networking ties all components together and ensures secure communication.
Virtual networks
- AWS: VPC
- GCP: VPC
- Azure: Virtual Network
These define private, isolated networks in the cloud.
Load balancers Distribute traffic across multiple servers to improve reliability and performance.
DNS and domain services
- AWS: Route 53
- GCP: Cloud DNS
- Azure: DNS
Translate domain names into IP addresses.
Firewalls and security rules Control inbound and outbound traffic to protect systems.
Networking is critical for both performance and security, especially in distributed systems.
Identity and access management (IAM)
Every cloud platform includes a system for controlling who can access what:
- AWS: IAM
- GCP: IAM
- Azure: Active Directory integration
IAM allows you to define roles and permissions, ensuring that users and services only have access to what they need. This is a foundational security layer across all cloud usage.
Observability and monitoring
Running systems in the cloud requires visibility into performance and failures.
- Logging services collect system and application logs
- Monitoring tools track metrics like CPU usage, latency, and errors
- Alerting systems notify you when something goes wrong
Examples include CloudWatch (AWS), Cloud Monitoring (GCP), and Azure Monitor.
These tools are essential for maintaining reliability at scale.
DevOps and infrastructure automation
Modern cloud usage often relies on automation.
Infrastructure as Code (IaC) Tools like Terraform or native services allow you to define infrastructure in code and deploy it consistently.
CI/CD pipelines Automate building, testing, and deploying applications.
Cloud providers also offer their own tools for these workflows, enabling teams to move faster and reduce manual errors.
Most commonly used services in practice
While cloud platforms offer hundreds of services, most applications rely heavily on a core set:
- Virtual machines or containers to run applications
- Object storage for assets and backups
- Managed databases for structured data
- Virtual networks and load balancers for connectivity
- IAM for access control
- Monitoring and logging for operations
A typical web application might look like this:
- A load balancer receives traffic
- Requests are routed to VMs or containers
- The application reads/writes data from a database
- Static assets are stored in object storage
- Logs and metrics are collected for monitoring
This pattern appears across startups, enterprises, and large-scale platforms.
How these services fit together
Cloud services are designed to be modular. You can combine them in different ways depending on your needs:
- A simple app might use just a VM and a database
- A scalable system might use containers, load balancers, and auto-scaling
- A modern architecture might rely heavily on serverless and managed services
The flexibility of the cloud comes from this ability to mix and match building blocks.
Why there are so many services
If most applications use the same core building blocks, why do cloud platforms offer so many services?
The answer is specialization. As systems grow, teams need:
- More scalable databases
- Better analytics tools
- Machine learning platforms
- Messaging and event systems
These advanced services build on top of the core foundation, but you don’t need them to get started.
What you should focus on first
If you’re new to the cloud, you don’t need to learn everything at once. A practical starting point is:
- One compute option (VMs or serverless)
- One storage solution (object storage or a database)
- Basic networking concepts (VPC and firewall rules)
- Simple IAM usage (permissions and roles)
With just these pieces, you can already build and run real applications. From there, it becomes much easier to explore more advanced services as your needs grow.
