aws-well-architected-framework/SKILL.md
Provides comprehensive AWS Well-Architected Framework knowledge covering all six pillars, design principles, review process, and the Well-Architected Tool. Use when learning or teaching the framework, preparing for Well-Architected Reviews, understanding pillar trade-offs, selecting appropriate AWS lenses, or evaluating workload architecture against the latest 2024-2025 best practices. Not to be confused with the aws-well-architected enforcement skill.
npx skillsauth add kayaman/skills aws-well-architected-frameworkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Reference: AWS Well-Architected Framework (updated Nov 2024)
This skill provides knowledge and guidance. For enforcement rules during code reviews and IaC development, see the aws-well-architected skill.
These cross-cutting principles apply to all six pillars:
Focus: Build and run workloads effectively while continuously improving processes.
8 Design Principles (expanded June 2024):
Key Areas: Organization → Prepare → Operate → Evolve
Key Services: CloudWatch, Systems Manager, Config, EventBridge, Fault Injection Service, CloudFormation
Focus: Protect data, systems, and assets using cloud-native controls.
7 Design Principles:
Key Areas: Identity & Access → Detection → Infrastructure Protection → Data Protection → Incident Response
Key Services: IAM, GuardDuty, Security Hub, CloudTrail, KMS, WAF, Shield, Secrets Manager, Macie
Focus: Ensure workloads perform their intended function correctly and consistently.
5 Design Principles:
Key Areas: Foundations → Workload Architecture → Change Management → Failure Management
Key Services: Route 53, ELB, Auto Scaling, SQS, Resilience Hub, Elastic Disaster Recovery, Fault Injection Service
Critical Rules:
Focus: Use computing resources efficiently as demand and technologies evolve.
5 Design Principles:
Key Areas: Selection (Compute, Storage, Database, Networking) → Review → Monitoring → Trade-offs
Key Services: EC2 Graviton, Lambda, ECS/EKS, ElastiCache, DAX, CloudFront, DynamoDB, Aurora, Global Accelerator
Focus: Achieve business value at the lowest price point.
5 Design Principles:
Key Areas: Cloud Financial Management → Expenditure Awareness → Cost-Effective Resources → Demand/Supply Management → Optimization Over Time
Key Services: Cost Explorer, Budgets, Cost Optimization Hub, Compute Optimizer, Savings Plans, Spot Instances, Trusted Advisor
Focus: Minimize environmental impact of cloud workloads.
6 Design Principles:
Key Areas: Region Selection → User Behavior → Software/Architecture Patterns → Data Patterns → Hardware Patterns → Development/Deployment Patterns
Key Strategies: Right-size compute, use Graviton (ARM) instances, S3 Lifecycle policies, serverless for variable workloads, eliminate idle resources
A Well-Architected Review is a constructive conversation about architectural decisions, not an audit mechanism.
| Phase | Activities | Output | |-------|-----------|--------| | Prepare | Identify workload, sponsors, and stakeholders; select pillars and lenses | Review scope and participants | | Review | Walk through per-pillar questions in the WA Tool; identify High/Medium Risk Issues (HRIs/MRIs) | Documented risks and findings | | Improve | Create improvement plan; prioritize by business impact; implement and track via milestones | Measurable risk reduction |
Lenses extend the framework for specific workload types or industries:
| Lens Category | Examples | |--------------|---------| | Technology | Serverless, SaaS, IoT, Container Build, Data Analytics | | AI/ML | Machine Learning, Generative AI, Responsible AI | | Industry | Financial Services, Healthcare, Games | | Custom | Organization-specific lenses via JSON templates |
| Tension | Guidance | |---------|---------| | Security vs Performance | TLS termination at the load balancer, not per-instance; use regional endpoints for latency | | Cost vs Reliability | Multi-AZ for stateful tiers; accept single-AZ for stateless compute in non-critical environments only | | Cost vs Performance | Reserved capacity for baseline; on-demand/Spot for burst; cache aggressively | | Operational Simplicity vs Reliability | Prefer managed services even at higher unit cost — reduced operational burden outweighs marginal cost | | Sustainability vs Performance | Right-sizing and Graviton generally improve both; optimize per-transaction cost | | Security vs Operational Simplicity | Automate security controls; manual security processes cause drift and become a bottleneck |
When conducting or preparing for a Well-Architected Review:
| Book / Resource | Author(s) | Publisher | Year | |------|-----------|-----------|------| | AWS Well-Architected Framework (official) | AWS | AWS Docs | 2024 | | Designing Data-Intensive Applications | Martin Kleppmann | O'Reilly | 2017 | | Software Engineering at Google | Winters, Manshreck, Wright | O'Reilly | 2020 | | Fundamentals of Software Architecture | Richards, Ford | O'Reilly | 2020 | | AWS for Solutions Architects (2nd ed.) | Shrivastava et al. | Packt | 2023 | | Cloud Native Patterns | Cornelia Davis | Manning | 2019 |
tools
Guidance for designing charts, graphs, plots, dashboards, and data visualizations that communicate clearly and persuade. Use when creating or reviewing a visualization, choosing a chart type, picking a color palette, decluttering a busy graphic, fixing misleading axes or proportions, building a dashboard, annotating a figure, or turning data into a presentation, report, or data-driven story. Grounded in the standard data-visualization literature (Knaflic, Tufte, Cleveland & McGill, Cairo, Wilke, Munzner, Few, Berinato). Covers chart selection, graphical perception and encoding, color and accessibility, decluttering, graphical integrity, dashboards, and narrative. Does NOT cover building data pipelines or ETL, statistical modeling or analysis methods, BI tool/vendor selection, or general UI/UX layout (see ux-design-principles). Tool-agnostic, with optional Python recipes.
development
Architect and implement production-grade microservices systems in TypeScript (NestJS) and Python (FastAPI), including resilience, observability, testing, deployment, and migration guidance.
development
--- name: databricks-genie-spaces-best-practices description: Design, configure, curate, govern, monitor, and integrate Databricks AI/BI Genie Spaces — the natural-language-to-SQL surface over Unity Catalog. Covers space scoping, general instructions, parameterized example SQL, SQL functions, trusted assets, JOIN configuration, knowledge store, certified queries, benchmarks, monitoring tab, feedback loops, the Genie Conversation API, governance via Unity Catalog (row filters, column masks, embed
tools
Implement OTP and passwordless authentication on AWS for TypeScript projects using Cognito CUSTOM_AUTH triggers (default) or a custom DynamoDB-backed flow, with SES (email) and SNS (SMS) delivery. Use when the user mentions OTP, one-time password, passwordless login, magic link, Cognito custom auth, DefineAuthChallenge, CreateAuthChallenge, VerifyAuthChallengeResponse, SES verification email, SNS SMS code, or MFA over email/SMS. Covers architecture decision (Cognito vs custom), Lambda trigger handlers, SES/SNS notifiers, DynamoDB schema with TTL, rate limiting, constant-time comparison, threat model (enumeration, replay, brute force), and aws-sdk-client-mock testing.