Amazon Web Services
Usage BasedAmazon Web Services (AWS): cloud computing services.
Published 29 May 2026 · Last updated 27 September 2026
Scores
Popularity5/5
Market-leading cloud provider; used by the majority of production deployments globally.
Learning Curve4/5
Vast service catalog; IAM, VPC, and networking alone can take months to master.
Flexibility5/5
Hundreds of composable services with full IaC support; virtually unlimited architectural freedom.
Performance5/5
Global infrastructure; EC2, Lambda, and CloudFront deliver performance at any scale.
Portability3/5
Broad API surface and proprietary services create meaningful lock-in; migration is possible but costly.
About Amazon Web Services
Amazon Web Services (AWS) is Amazon's cloud platform and the largest public cloud by market share, launched in 2006 with S3 and EC2. It offers more than 200 services across compute, storage, databases, networking, analytics, and AI, delivered from dozens of regions worldwide, each split into multiple isolated availability zones, plus hundreds of CloudFront edge locations.
The core building blocks are EC2 virtual machines (including instances on Amazon's own Arm-based Graviton processors), Lambda for serverless functions, ECS and EKS for containers, S3 for object storage alongside EBS and EFS, and managed databases such as RDS, Aurora, DynamoDB, ElastiCache, and Redshift. Most teams combine a handful of these with IAM for access control, VPC for networking, and CloudWatch for monitoring.
AI workloads run through Amazon Bedrock, a serverless API to foundation models from Anthropic, Meta, Mistral, Amazon's own Nova family, OpenAI's open-weight models, and others, with AgentCore for running production AI agents. SageMaker covers training and hosting custom models, and GPU instances serve teams that want raw capacity.
Pricing is pay-as-you-go, billed per second, request, or gigabyte depending on the service, with savings plans and reserved capacity for steady workloads. New accounts choose between a Free plan (up to $200 in credits over six months, limited to select services) and a Paid plan with access to everything, and more than 30 services stay free within monthly limits on either plan. The breadth is the main trade-off: configuration, IAM, and billing take real expertise to get right.
Key Features
- 200+ services across compute, storage, databases, networking, analytics, and AI
- Dozens of regions, each with multiple isolated availability zones
- EC2 virtual machines, including Arm-based Graviton instances
- Lambda serverless functions and ECS/EKS containers
- S3 object storage plus EBS and EFS block and file storage
- Managed databases: RDS, Aurora, DynamoDB, ElastiCache, Redshift
- Amazon Bedrock for foundation models and AgentCore for AI agents
- Fine-grained IAM access control and VPC networking
Pros
- Broadest service catalog of any cloud provider
- Most regions and availability zones for placing workloads near users
- Deep enterprise security and compliance certifications
- Largest ecosystem of tools, partners, and experienced engineers
- Proven reliability at massive scale
- Savings plans and reserved capacity cut costs for steady workloads
Cons
- Hundreds of services with overlapping features make choosing hard
- Steep learning curve, especially IAM and networking
- Bills are hard to predict: data transfer and NAT gateway costs are easy to miss
- Support on lower-tier plans can be slow
- AWS-specific services create lock-in
- Console is functional but overwhelming
Amazon Web Services Pricing
Usage Based- · $100 in AWS credits at signup, growable to $200 total over 6 months
- · Free usage of select services only, with no charges unless you upgrade
- · Account auto-closes after 6 months or when credits run out
- · 30+ services (EC2, S3, DynamoDB, RDS, Lambda free-tier allotments) remain free within monthly limits
- · Applies on Free/Paid plans and legacy accounts, indefinitely
- · Pay-as-you-go access to all AWS services
- · New customers still receive up to $200 in credits
- · Eligible for promotional credits
Tech Stacks with Amazon Web Services
Advanced API (Go)
ProjectA high-performance API stack for advanced engineers. Go handles concurrency, PostgreSQL + Redis back the data layer, Prometheus + Grafana provide observability, and Kubernetes can orchestrate containers as an optional addition.
MLOps Pipeline
ProjectProduction-grade ML infrastructure. PyTorch for model training, Apache Airflow (or Dagster or Prefect) for orchestration, dbt for feature transformations, and Snowflake as the data warehouse, with Docker as an optional containerization addition.
Backend
Programming
Databases
Hosting
Kubernetes DevOps Pipeline
InfrastructureA self-managed DevOps platform for teams that want the whole path from commit to production in one place. Bring your own containerized app; GitHub Actions or GitLab CI/CD tests and builds it, Kubernetes deploys and runs it, PostgreSQL is available for its data, and Grafana and Sentry close the observability loop.
Databases
Hosting
Tools Related to Amazon Web Services
Works well with Amazon Web Services(8)
AWS offers Amazon RDS for MySQL (managed) and Amazon Aurora MySQL-compatible Edition (high-performance); MySQL on AWS is one of the most common database choices for web applications in the AWS ecosystem.
AWS hosts Snowflake accounts natively; it was Snowflake's original cloud and remains a common choice.
AWS ElastiCache provides managed Redis on AWS — a common caching and session layer for AWS-hosted backends; Auto Discovery handles cluster node changes transparently.
AWS offers Amazon RDS for MariaDB as a managed service; it supports MariaDB 10.x with automated backups and multi-AZ failover, though it has fewer configuration options than RDS MySQL or Aurora.
AWS hosts MongoDB Atlas clusters or DocumentDB (MongoDB-compatible) — MongoDB Atlas has first-class AWS VPC peering; DocumentDB is Amazon's managed MongoDB-compatible service.
AWS is the most-integrated cloud target for GitHub Actions — the aws-actions organization provides official actions for ECR, ECS, Lambda, and OIDC credential federation.
Integrates with Amazon Web Services(3)
AWS works with MLflow — S3 is a first-class artifact store backend, and SageMaker supports MLflow model deployment via the mlflow.sagemaker module.
Amazon QuickSight is AWS's BI service, provisioned in an AWS account with IAM access control and native connectors to Redshift, Athena, RDS, and S3, while also reading non-AWS sources.
Datadog is a leading APM/logging solution for AWS workloads — native AWS integrations (CloudWatch, Lambda, ECS) make Datadog the standard observability platform for AWS-hosted apps.
Tools that require Amazon Web Services(1)
Amazon Redshift is a fully-managed AWS data warehouse — it only runs inside an AWS account and depends on AWS-native infrastructure (S3 for backups/Spectrum, IAM for access control, VPC networking); there is no way to provision Redshift outside AWS.
Alternatives to Amazon Web Services(10)
Competing hyperscalers; AWS has the broadest service catalog, GCP leads on data and ML services (BigQuery, Vertex AI).
Competing hyperscalers; AWS has the broadest service catalog, Azure has stronger enterprise/Windows and Microsoft 365 integration.
AWS has Amplify/CloudFront for frontend hosting; Netlify is a focused JAMstack platform — Netlify is simpler, AWS gives more control.
AWS has Elastic Beanstalk/ECS for app hosting; Railway is a simpler PaaS — Railway is faster to deploy, AWS has more services and control.
Different tiers — AWS is a full managed cloud platform, Hetzner provides affordable EU-based VPS/dedicated servers with no managed services.
AWS has ECS, App Runner, and Elastic Beanstalk for container deployments; Fly.io is a simpler PaaS alternative — Fly.io is faster to get started and global by default, AWS provides more services, compliance options, and infrastructure control.
Vendor
Amazon
Website →Tags
Details
- Maintained
- Yes
- Type
- Managed
- Regions
- Us-east-1, Us-east-2, Us-west-1, Us-west-2, Af-south-1, Ap-east-1
- CDN
- Yes
- SSL
- Yes
- Scaling
- Auto & Manual
- Free tier
- Yes