# Activity: Define Performance & Scalability

**Activity ID**: 48
**Order**: 7
**Phase**: Inception
**Dependencies**: None

## Description

Define Performance & Scalability

## Guidance

# Define Performance & Scalability

## Objective

Define expected load profile, caching tiers, async processing strategy, connection pooling, scaling approach, and capacity planning.

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## Decisions to Make

### 1. Expected Load Profile

Characterize the system's expected usage:
- **Concurrent users**: How many at peak?
- **Requests/sec**: Expected throughput per endpoint category
- **Data volume**: How much data at launch? At 1 year? At 5 years?
- **Read/write ratio**: What percentage of requests are reads vs writes?
- **Burst patterns**: Are there predictable spikes (daily, weekly, seasonal)?

### 2. Caching Tiers

Define caching at each level:
- **Application cache**: In-memory cache (Django cache framework, Redis)
- **CDN**: Static assets, pre-rendered pages
- **DB query cache**: Query result caching, materialized views
- **Session cache**: Session storage (DB, Redis, cookie-based)
- **HTTP cache**: Cache-Control headers, ETags, conditional requests

For each tier: what to cache, TTL, invalidation strategy.

### 3. Async Processing

- **Task queues**: Celery, RQ, Dramatiq — for background jobs
- **Workers**: How many? Auto-scaling?
- **Use cases**: Email sending, PDF generation, data import/export, AI inference
- **Priority queues**: Critical vs. best-effort tasks

### 4. Connection Pooling

- **DB connections**: Pool size, timeout, max overflow
- **HTTP clients**: Connection reuse for external API calls
- **WebSocket connections** (if applicable)

### 5. Scaling Strategy

- **Horizontal**: Add more instances behind load balancer
- **Vertical**: Increase instance resources (CPU, RAM)
- **Auto-scaling**: Triggers (CPU%, request count, queue depth)
- **Database scaling**: Read replicas, sharding, connection pooling

### 6. Capacity Planning

- Baseline resource requirements
- Growth projections (linear, exponential)
- Cost model per scaling tier
- When to re-evaluate architecture

### 7. Scan Skills

Query Playbook Skills where `capability_domain` in:
- `PERF_CACHING`
- `PERF_ASYNC`
- `PERF_SCALING`

Report coverage and gaps.

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## Deliverables

- ✅ **Load profile** characterized
- ✅ **Caching strategy** defined per tier
- ✅ **Async processing** approach chosen
- ✅ **Connection pooling** configured
- ✅ **Scaling strategy** defined
- ✅ **Capacity plan** with cost model
- ✅ **Skill coverage** assessed for this domain
- ✅ **Decision recorded** for inclusion in SAO.md (DTA-18)

## Agent

None

## Skill

None

## Rules

None

## Artifacts Produced

None

## Artifacts Consumed

None

## Notes

No additional notes.
