Amazon Web Services (AWS)

What Amazon Web Services offers, how its pay-as-you-go pricing and commitment discounts work, where it fits well and how to get started through official channels.

Best suited to
Teams needing broad managed services, global regions and compliance options
Key services
  • EC2
  • S3
  • RDS
  • Lambda
  • CloudFront
  • Bedrock
Amazon Web Services (AWS) overview banner with stacked server units in front of a large circle

Amazon Web Services (AWS) is the cloud platform run by Amazon, and this AWS cloud platform overview explains what it offers, how it charges and where it fits. AWS has the widest catalog of managed services among the major providers, which makes it a common choice for startups that expect to grow, enterprises with complex requirements and teams building AI features.

The breadth is both the strength and the challenge. You can run almost any workload on AWS, but you also need to learn how accounts, regions, identity and billing fit together before the platform feels manageable.

Core services #

AWS groups its products into families. The table below covers the services most teams touch first. For a longer walkthrough, read our guide to how AWS core services and accounts are organized.

Area Key services What they do
Compute Amazon EC2, AWS Lambda, AWS Fargate Virtual servers (including GPU instances), event-driven functions and serverless containers
Storage Amazon S3, EBS, EFS, S3 Glacier storage classes Object storage, block volumes for instances, shared file systems and low-cost archive tiers
Databases Amazon RDS, Aurora, DynamoDB, Redshift Managed relational engines, a key-value and document database, and a data warehouse
Networking Amazon VPC, CloudFront, Route 53, API Gateway Private networks, a content delivery network, DNS and managed API endpoints
AI and ML Amazon Bedrock, SageMaker AI, Rekognition, Comprehend Foundation models through an API, a platform for training and deploying models, and prebuilt vision and language services
DevOps and events CodeBuild, CodeDeploy, CodePipeline, EventBridge Build, deploy and release automation, plus an event bus for connecting services

AWS infrastructure is organized into regions, each made up of multiple isolated Availability Zones. Most services are regional, so choosing a region affects latency, data residency and which features are available.

AI workloads on AWS

Teams building AI features usually combine GPU-backed EC2 instances or SageMaker AI for training and hosting their own models with Amazon Bedrock for managed access to foundation models from Amazon and third-party model providers. Model availability in Bedrock varies by region, and some models require you to request access in the console before use.

How pricing works #

AWS uses a pay-as-you-go model: you are billed for what you consume, measured per second, per hour, per request or per gigabyte depending on the service. There is no single price list; every service has its own pricing page and many prices differ by region.

  • On-Demand: no commitment, the highest unit price, and the right default while you learn your usage.
  • Savings Plans and Reserved Instances: lower rates in exchange for a one-year or three-year commitment to a level of usage.
  • Spot Instances: spare EC2 capacity at a discount, which AWS can reclaim with short notice. Good for fault-tolerant batch jobs.
  • Free Tier: AWS offers a free tier for new customers, but its structure has changed over time and it is limited in scope and duration. Check the official free tier page for current terms.

Data transfer out to the internet and between regions is billed separately and is often the line item that surprises new users. Our explainer on how AWS billing, the free tier and Savings Plans work covers budgets, Cost Explorer and commitment discounts in more detail.

Where it fits well #

  • Products that need many managed building blocks (queues, streaming, search, identity, analytics) from one provider.
  • Organizations with compliance requirements that benefit from a large set of audited services and regions.
  • Teams that want both self-managed GPU compute and hosted foundation models under one account and billing relationship.
  • Architectures that need multiple regions for latency or resilience.

Things to consider #

The learning curve is real. IAM policies, VPC design and cost allocation all take time to understand, and mistakes in any of them can have security or billing consequences. A small project that only needs a few virtual machines may be simpler and more predictable on a developer-focused cloud.

Costs can also grow quietly. NAT gateways, idle load balancers, unattached volumes, log retention and data transfer all add up. Set budgets and alerts on day one rather than after the first surprising invoice.

Finally, new accounts start with default service quotas, for example on the number of vCPUs you can run in a given instance family. These limits protect both you and AWS. If you need more, request an increase through Service Quotas in the console and explain your use case.

Getting started the official way #

  1. Create an account directly on the official AWS website. AWS asks for contact details, a payment method and phone verification as part of sign-up.
  2. Sign in as the root user once, enable multi-factor authentication on it, and stop using it for daily work.
  3. Set up IAM Identity Center or IAM users with least-privilege permissions for yourself and your team.
  4. Create an AWS Budget with email alerts and turn on CloudTrail so API activity is logged.
  5. Pick a primary region and start with the tutorials in the AWS documentation.

AWS support plans, documentation and the re:Post community forum are the official places to get help. Account, billing and quota questions go through the Support Center in the console, which is available on every account.

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