AWS / Amazon Web Services
Amazon's leading cloud platform with over 200 services for compute, storage, AI, databases and more – the basis for modern web apps and AI projects.
Amazon Web Services is the clear market leader in cloud computing with over 30% share. From startups to Fortune 500 – Netflix, Airbnb, BMW and Siemens use AWS. With over 200 services AWS covers almost every IT need – from simple web hosting to complex machine learning pipelines. For many companies the question is not whether to use AWS but how to use it best.
What is AWS / Amazon Web Services?
AWS (Amazon Web Services) is a cloud computing platform that has provided IT infrastructure and services on demand since 2006. Instead of buying and running their own servers, companies rent compute, storage, databases, networking and AI services and pay only for what they use (pay-as-you-go). AWS runs 33 regions with over 100 Availability Zones worldwide and offers high availability and compliance (including GDPR-aligned regions in Frankfurt and Ireland).
How does AWS / Amazon Web Services work?
AWS provides infrastructure as code: resources can be provisioned in seconds via APIs, SDKs or the Management Console. EC2 provides virtual servers, S3 offers object storage, RDS manages databases, Lambda runs code serverlessly. Access is controlled with IAM (Identity and Access Management). With Infrastructure as Code (Terraform, CloudFormation) the whole setup is versioned and reproducible. Auto Scaling adjusts capacity to load – scale up for Black Friday, scale down at night.
Practical Examples
Startup stack: EC2 for web server, RDS for PostgreSQL, S3 for images/uploads, CloudFront as CDN, SES for email – set up in an hour.
AI pipeline: SageMaker trains models, Lambda exposes them as API, S3 stores training data, CloudWatch monitors performance.
Disaster recovery: Critical systems replicated between Frankfurt and Ireland – the other region takes over if one fails.
Big data: Redshift (data warehouse) analyses terabytes of business data; Athena runs SQL directly on S3.
IoT: AWS IoT Core connects millions of sensors; Kinesis processes streams in real time; DynamoDB stores sensor data.
Typical Use Cases
Web applications: Hosting, CDN, databases and load balancing for sites and SaaS
AI and machine learning: Training and deploying models with SageMaker, Rekognition, Comprehend
Analytics: Data lakes on S3, ETL with Glue, analysis with Redshift and QuickSight
Enterprise migration: Gradual migration from on-premise to the cloud
DevOps: CI/CD with CodePipeline, container orchestration with ECS/EKS
Advantages and Disadvantages
Advantages
- Broadest service portfolio: Over 200 services for practically every use case
- Global presence: 33 regions worldwide including GDPR-aligned locations in Europe
- Pay-as-you-go: No upfront investment, billing by actual use
- Mature ecosystem: Largest community, documentation and certifications
- Enterprise-ready: SOC 2, ISO 27001, HIPAA, PCI-DSS and more
Disadvantages
- Complexity: The number of services and options can be overwhelming
- Cost risk: Without monitoring, costs can surprise (forgotten resources, data transfer)
- Vendor lock-in: Proprietary services (DynamoDB, Lambda) make switching harder
- Learning curve: AWS expertise requires significant investment or certified partners
Frequently Asked Questions about AWS / Amazon Web Services
What does AWS cost?
AWS, Azure or Google Cloud – which is better?
Is AWS GDPR compliant?
Related Terms
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