Cloud Computing
Master AWS, Azure, GCP services, serverless architectures, and cloud-native development
Overview
Cloud computing has revolutionized how applications are built, deployed, and scaled. Major cloud providers offer comprehensive platforms with compute, storage, networking, databases, and managed services that eliminate infrastructure management overhead.
This section covers AWS (Amazon Web Services), Azure (Microsoft), and GCP (Google Cloud Platform), serverless computing with Functions as a Service (FaaS), container services, managed databases, cloud storage, networking, and cost optimization strategies. For infrastructure automation, see our DevOps & Infrastructure guide.
Cloud-native applications leverage managed services, auto-scaling, and pay-as-you-go pricing. Understanding cloud architecture patterns, service selection, and cost management is essential for successful cloud deployments. For container orchestration, see our Kubernetes guide.
Amazon Web Services
Comprehensive cloud platform with EC2, S3, Lambda, RDS, and hundreds of services.
Learn AWS →Microsoft Azure
Enterprise-focused cloud platform with strong integration with Microsoft ecosystem.
Learn Azure →Google Cloud Platform
Data and AI-focused platform with excellent Kubernetes support and machine learning services.
Learn GCP →Cloud Service Models
Infrastructure as a Service (IaaS)
IaaS provides virtualized computing resources over the internet. You manage operating systems, applications, and data, while the provider manages virtualization, servers, storage, and networking. Examples include AWS EC2, Azure Virtual Machines, and GCP Compute Engine.
Use IaaS for full control over infrastructure, custom configurations, and migration of existing applications. For infrastructure automation, see our DevOps & Infrastructure guide on Terraform and infrastructure as code.
Platform as a Service (PaaS)
PaaS provides a platform for developing, running, and managing applications without managing underlying infrastructure. You focus on application code while the provider handles runtime, middleware, and infrastructure. Examples include AWS Elastic Beanstalk, Azure App Service, and GCP App Engine.
PaaS accelerates development and reduces operational overhead. Ideal for web applications and APIs. For API development, see our RESTful API Design guide.
Serverless (Functions as a Service)
Serverless computing executes code in response to events without managing servers. You write functions, and the platform handles scaling, availability, and infrastructure. Examples include AWS Lambda, Azure Functions, and Google Cloud Functions.
Serverless is ideal for event-driven architectures, APIs, and microservices. Pay only for execution time. For microservices patterns, see our APIs & Microservices documentation.
Software as a Service (SaaS)
SaaS delivers complete applications over the internet. Users access software through web browsers without installation or maintenance. Examples include Salesforce, Office 365, and Google Workspace.
SaaS eliminates software installation and maintenance. Focus on using applications rather than managing them. Many SaaS platforms provide APIs for integration and customization.
Cloud Architecture Patterns
Multi-Tier Architecture
Separate applications into presentation, application, and data tiers. Use load balancers for high availability, separate security groups for each tier, and scale tiers independently based on load.
Implement proper network segmentation and security controls between tiers. Use managed databases for the data tier. For database design, see our Databases guide.
Microservices on Cloud
Deploy microservices using container services (ECS, AKS, GKE) or serverless functions. Use API gateways for routing, service discovery for location, and managed message queues for asynchronous communication.
Implement proper monitoring, logging, and distributed tracing. Use managed Kubernetes services for orchestration. For microservices patterns, see our APIs & Microservices guide.
Event-Driven Architecture
Use managed message queues (SQS, Service Bus, Pub/Sub) and event streaming (Kinesis, Event Hubs, Pub/Sub) for decoupled, scalable systems. Events trigger serverless functions or microservices.
Design for eventual consistency and implement proper error handling and retry mechanisms. Use event sourcing for audit trails and replay capabilities.
Serverless Architecture
Build applications using serverless functions, managed databases, object storage, and API gateways. Functions respond to HTTP requests, database changes, file uploads, or scheduled events.
Optimize for cold starts, implement proper error handling, and use provisioned concurrency for consistent performance. Monitor function execution and costs carefully.
Cost Optimization
Right-Sizing Resources
Regularly review and adjust resource sizes based on actual usage. Use cloud provider cost analysis tools to identify underutilized resources. Implement auto-scaling to match demand automatically.
Use reserved instances or savings plans for predictable workloads. Spot instances can reduce costs for fault-tolerant workloads. Monitor costs continuously and set up billing alerts.
Storage Optimization
Use appropriate storage classes: hot storage for frequently accessed data, cool storage for infrequent access, and archive storage for long-term retention. Implement lifecycle policies to automatically transition data.
Compress data before storage, delete unused resources, and use data deduplication where applicable. Regularly audit storage usage and remove unnecessary data.
Network Optimization
Minimize data transfer costs by using CDNs for static content, keeping data in the same region, and using private networks instead of public internet where possible. Optimize API calls and implement caching.
Use edge locations for content delivery. Implement proper caching strategies to reduce data transfer. For API optimization, see our RESTful API Design guide.