~linuxgoose/engineering-templates

0bf73b454c1004d5383309b0d61ee6ec030e5606 — Jordan Robinson 3 months ago 3b62ebd
add capacity planning and scaling document template
2 files changed, 138 insertions(+), 0 deletions(-)

M README.md
A templates/capacity-planning-scaling-document.md
M README.md => README.md +1 -0
@@ 12,3 12,4 @@ Comprehensive collection of templates for solutions design, architecture decisio
* Runbook / Operations Guide
* Code Review Standards & Guidelines
* Technical Debt Registry
* Capacity Planning & Scaling Document
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A templates/capacity-planning-scaling-document.md => templates/capacity-planning-scaling-document.md +137 -0
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# Capacity Planning & Scaling Document

## Current State Assessment

### System Metrics (as of [Date])
- Current daily active users
- Peak requests per second (RPS)
- Average response time (p50/p95/p99)
- Error rate
- Data storage used
- Resource utilization (CPU, memory, disk)

### Infrastructure Details
- Number of application servers
- Database configuration (replicas, shards, etc.)
- Cache configuration
- CDN/load balancer setup
- Region/availability zone setup

## Growth Projections

### Forecasted Growth
- User growth rate
- Expected peak RPS in 3/6/12 months
- Data growth projections
- Usage pattern changes expected

### Traffic Patterns
- Daily peaks and troughs
- Seasonal variations
- Special events that cause spikes

## Scaling Limits

### Current Bottlenecks
- What limits us today?
  - Database connection pool
  - Memory constraints
  - I/O limitations
  - External service rate limits
  - Network bandwidth

### Projected Capacity Headroom
- How long until we hit limits (in months)?
- When do we need to take action?
- Action items and timeline

## Scaling Strategies

### Horizontal Scaling
**Application Layer:**
- Load balancing strategy
- Session management approach
- Stateless design requirements
- Max number of instances

**Database Layer:**
- Replication approach
- Read replicas strategy
- Sharding approach (if needed)
- Consistency model

**Cache Layer:**
- Cache distribution strategy
- Eviction policy
- Warming strategy

### Vertical Scaling
- Current instance size
- Available larger instances
- When horizontal scaling isn't enough
- Cost implications

### Feature-Level Scaling
- Feature flags for traffic shaping
- Graceful degradation strategies
- Circuit breakers
- Rate limiting approach

## Infrastructure Upgrades

### Immediate (0-3 months)
| Item | Current | Upgrade | Timeline | Cost |
|------|---------|---------|----------|------|
| [Item 1] | [Current] | [New] | [When] | [Cost] |

### Medium-term (3-6 months)
| Item | Current | Upgrade | Timeline | Cost |
|------|---------|---------|----------|------|
| [Item 1] | [Current] | [New] | [When] | [Cost] |

### Long-term (6-12 months)
| Item | Current | Upgrade | Timeline | Cost |
|------|---------|---------|----------|------|
| [Item 1] | [Current] | [New] | [When] | [Cost] |

## Performance Optimization Opportunities
- Low-hanging fruit for improvement
- Estimated impact of each optimization
- Timeline for implementation

## Cost Implications
- Current monthly infrastructure cost
- Projected cost increase with growth
- Cost optimization strategies
- ROI of scaling investments

## Testing & Validation

### Load Testing Plan
- How to simulate projected load
- Testing methodology
- Key metrics to measure
- Acceptable failure modes

### Staging Validation
- How to test scaling procedures in staging
- Frequency of capacity tests
- Rollback procedures

## Monitoring & Alarms

### Early Warning Indicators
- Metrics that signal capacity issues
- Alert thresholds
- Action triggers

### Post-Scaling Validation
- Metrics to verify scaling was successful
- Dashboard updates needed
- Communication to stakeholders

## Owner & Review
- Owner: [Team/Person]
- Last reviewed: [Date]
- Next review: [Date]
- Previous versions/history: [Links]
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