Update nexus: fix conflicts and sync local changes
This commit is contained in:
Shen Wei
@@ -1,72 +1,72 @@
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# Scalability
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## Definition
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Scalability is a system's ability to handle increased load (users, traffic, data volume) without experiencing performance degradation. The DevOps Maturity Model explicitly lists Scalability as a key metric for measuring DevOps maturity.
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## Types of Scalability
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### Vertical Scaling (Scale-Up)
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- Adding more resources (CPU, RAM, storage) to existing servers
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- Simpler to implement but has hardware limits
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- Often a Phase 1-2 approach
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### Horizontal Scaling (Scale-Out)
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- Adding more servers to handle load
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- More complex but theoretically unlimited
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- Characteristic of Phase 3+ maturity
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### Auto-Scaling
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- Automatically adjusting capacity based on demand
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- Cloud-native approach enabled by IaC
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- Characteristic of Phase 4-5 maturity
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## Across DevOps Maturity Levels
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| Maturity | Scalability Approach |
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|----------|---------------------|
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| Phase 1 | Manual scaling — servers receive individual attention, unable to respond quickly to load changes |
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| Phase 2 | Basic automation — version control for configurations, but manual scaling still required |
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| Phase 3 | Automated infrastructure — provisioning becomes repeatable and reliable |
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| Phase 4 | Auto-scaling — immutable infrastructure, load testing ensures readiness for production scale |
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| Phase 5 | Full elasticity — infrastructure scales automatically, minimal manual effort |
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## Key Scalability Practices in DevOps
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### Infrastructure as Code (IaC)
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IaC enables automated and repeatable infrastructure provisioning, which is foundational for scalability. Without IaC, scaling requires manual intervention for each new resource.
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### Containerization and Orchestration
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- Docker containers package applications consistently
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- Kubernetes or similar orchestrators manage container lifecycles
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- Enables horizontal scaling with minimal overhead
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### Cloud-Native Architecture
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- Microservices allow independent scaling of components
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- Serverless (Lambda, Cloud Functions) scales automatically
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- Managed services offload operational burden
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### Load Testing
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- Phase 4 maturity requires performance and load testing before production deployment
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- Testing ensures systems are ready for production scale
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- Identifies bottlenecks before they affect users
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## Scalability and Business Impact
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| Scalability Aspect | Business Impact |
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|-------------------|----------------|
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| Handle traffic spikes | No lost revenue during peak events |
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| Geographic expansion | Support new markets without redesign |
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| Data growth | Store and process more data over time |
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| Feature expansion | New features don't degrade existing functionality |
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| Cost optimization | Scale down during low demand to save costs |
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## Sources
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- [[sources/devops-maturity-model-from-traditional-it-to-advanced-devops.md]]
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- [[sources/cloud-devop-maturity-guideline.md]]
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## Related Concepts
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- [[concepts/Infrastructure-as-Code]]
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- [[concepts/Cloud-Native]]
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- [[concepts/High-Availability]]
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- [[concepts/Continuous-Deployment]]
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- [[concepts/DevOps-Maturity]]
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# Scalability
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## Definition
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Scalability is a system's ability to handle increased load (users, traffic, data volume) without experiencing performance degradation. The DevOps Maturity Model explicitly lists Scalability as a key metric for measuring DevOps maturity.
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## Types of Scalability
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### Vertical Scaling (Scale-Up)
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- Adding more resources (CPU, RAM, storage) to existing servers
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- Simpler to implement but has hardware limits
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- Often a Phase 1-2 approach
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|
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### Horizontal Scaling (Scale-Out)
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- Adding more servers to handle load
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- More complex but theoretically unlimited
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- Characteristic of Phase 3+ maturity
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### Auto-Scaling
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- Automatically adjusting capacity based on demand
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- Cloud-native approach enabled by IaC
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- Characteristic of Phase 4-5 maturity
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## Across DevOps Maturity Levels
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| Maturity | Scalability Approach |
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|----------|---------------------|
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| Phase 1 | Manual scaling — servers receive individual attention, unable to respond quickly to load changes |
|
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| Phase 2 | Basic automation — version control for configurations, but manual scaling still required |
|
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| Phase 3 | Automated infrastructure — provisioning becomes repeatable and reliable |
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| Phase 4 | Auto-scaling — immutable infrastructure, load testing ensures readiness for production scale |
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| Phase 5 | Full elasticity — infrastructure scales automatically, minimal manual effort |
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## Key Scalability Practices in DevOps
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### Infrastructure as Code (IaC)
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IaC enables automated and repeatable infrastructure provisioning, which is foundational for scalability. Without IaC, scaling requires manual intervention for each new resource.
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### Containerization and Orchestration
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- Docker containers package applications consistently
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- Kubernetes or similar orchestrators manage container lifecycles
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- Enables horizontal scaling with minimal overhead
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### Cloud-Native Architecture
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- Microservices allow independent scaling of components
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- Serverless (Lambda, Cloud Functions) scales automatically
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- Managed services offload operational burden
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### Load Testing
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- Phase 4 maturity requires performance and load testing before production deployment
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- Testing ensures systems are ready for production scale
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- Identifies bottlenecks before they affect users
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## Scalability and Business Impact
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| Scalability Aspect | Business Impact |
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|-------------------|----------------|
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| Handle traffic spikes | No lost revenue during peak events |
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| Geographic expansion | Support new markets without redesign |
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| Data growth | Store and process more data over time |
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| Feature expansion | New features don't degrade existing functionality |
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| Cost optimization | Scale down during low demand to save costs |
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## Sources
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- [[sources/devops-maturity-model-from-traditional-it-to-advanced-devops.md]]
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- [[sources/cloud-devop-maturity-guideline.md]]
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## Related Concepts
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- [[concepts/Infrastructure-as-Code]]
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- [[concepts/Cloud-Native]]
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- [[concepts/High-Availability]]
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- [[concepts/Continuous-Deployment]]
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- [[concepts/DevOps-Maturity]]
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