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Foundations of Cloud Computing - Runbook & Reference

中文 · GitHub source Facts verified against official AWS documentation: 2026-08-19

Overview

Cloud computing delivers on-demand IT resources over the internet with pay-as-you-go pricing. AWS provides compute, storage, databases, networking, analytics, and many other services on a global infrastructure, replacing large up-front capital expenses with variable costs that scale with usage.

Key concepts

  • On-demand self-service: provision resources when you need them without human interaction, and release them when done.
  • Pay-as-you-go: pay only for what you use, converting capital expense into variable operating expense.
  • Economies of scale: AWS aggregates demand across many customers, reducing per-unit costs.
  • Elasticity and scalability: scale capacity up/down or out/in automatically; vertical (larger instances) and horizontal (more instances) scaling.
  • High availability and fault tolerance: design across Availability Zones and Regions to survive failures.
  • Global infrastructure: Regions (geographic areas), Availability Zones (isolated data centers within Regions), and edge locations for content delivery.
  • Service models: IaaS (EC2: infrastructure), PaaS (Elastic Beanstalk, RDS: platform managed), SaaS (fully managed applications).
  • Agility: develop, test, and deploy faster with self-service infrastructure and managed services.
  • Shared responsibility: AWS secures the cloud; customers secure what they put in the cloud (see the Shared Responsibility Model runbook).

Common operations

The foundation is concepts rather than a single API; apply it with:

# Examples: elasticity and managed services in practice
aws ec2 describe-regions                          # global infrastructure
aws autoscaling describe-auto-scaling-groups      # elasticity
aws elasticbeanstalk describe-applications        # PaaS model
aws lambda list-functions                         # serverless compute

Best practices

  • Design for failure: multi-AZ/Region architectures, health checks, and automated recovery.
  • Use elasticity: match capacity to demand with Auto Scaling and serverless options.
  • Choose the right service model (IaaS/PaaS/SaaS) per workload to reduce operational burden.
  • Track cost from day one with budgets, tags, and Cost Explorer.
  • Follow the Well-Architected Framework pillars when designing new workloads.

Troubleshooting

Symptom Checks and fixes
Capacity surprises at launch Use Elastic Beanstalk/Auto Scaling and test scaling behavior in staging.
Costs grow with idle resources Release or scale down unused resources; use managed/serverless where possible.
Single point of failure Spread workloads across AZs and add health-checked redundancy.

Limits

Concepts are general; actual behavior depends on service quotas and architecture choices. See the AWS Cloud overview and the per-service runbooks in this knowledge base.

Official references