tool#AI#Machine Learning#Cloud Computing#Services
Amazon Web Services (AWS)
AWS is a comprehensive cloud computing platform from Amazon.
AWS (Amazon Web Services) offers a wide range of cloud services, including computing, storage, databases, machine learning, and more.
Maturity
Established
Cognitive loadMedium
Classification
- ComplexityMedium
- Impact areaTechnical
- Decision typeTechnical
- Organizational maturityAdvanced
Technical context
Integrations
Integration with CI/CD toolsConnection to external databasesAPI integration
Principles & goals
Flexibility in infrastructurePay-as-you-go modelHigh availability
Value stream stage
Build
Organizational level
Enterprise, Domain, Team
Use cases & scenarios
Use cases
Scenarios
Compromises
Risks
- Data loss due to misconfiguration
- Excessive costs due to unused resources
- Vendor lock-in
Best practices
- Regularly review costs
- Implement security policies
- Plan resource scaling
I/O & resources
Inputs
- Access to AWS account
- Technical requirements
- Development resources
Outputs
- Deployed services
- Scalable infrastructure
- Access statistics
Description
AWS (Amazon Web Services) offers a wide range of cloud services, including computing, storage, databases, machine learning, and more. These services enable businesses to design their IT infrastructure flexibly and scalably.
✔Benefits
- Scalability of resources
- Cost efficiency through usage-based billing
- Access to a wide range of services
✖Limitations
- Complexity of pricing
- Dependence on internet connection
- Security concerns regarding data storage
Trade-offs
Metrics
- Cost per usage
Measurement of costs relative to the usage of services.
- Availability
Percentage of time services are available.
- Response time
Time taken to respond to requests.
Examples & implementations
Netflix
Netflix uses AWS for streaming content to millions of users worldwide.
Airbnb
Airbnb uses AWS to keep their platform scalable and reliable.
NASA
NASA uses AWS for storing and analyzing large amounts of data from space missions.
Implementation steps
1
Create and configure AWS account
2
Select and deploy services
3
Set up monitoring and security
⚠️ Technical debt & bottlenecks
Technical debt
- Insufficient documentation of configurations
- Outdated security policies
- Lack of monitoring of resources
Known bottlenecks
Network latencyResource contentionComplex configurations
Misuse examples
- Excessive resource usage without planning
- Misconfiguration of security groups
- Insufficient backup strategies
Typical traps
- Assuming all services are free
- Believing that the cloud is always secure
- Underestimating training needs
Required skills
Knowledge of cloud architecturesExperience with AWS servicesSkills in data analysis
Architectural drivers
Microservices architectureServerless computingContainerization
Constraints
- • Compliance with data protection regulations
- • Availability of internet connections
- • Technical limitations of services