199 lines
7.0 KiB
Markdown
199 lines
7.0 KiB
Markdown
# System Scalability Checklist
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Use this checklist when designing for horizontal scalability and high availability.
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## Load Estimation
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- [ ] **Current load:** [N] requests/second, [N] concurrent users
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- [ ] **Peak load:** [N] requests/second (expected during [event/time])
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- [ ] **Growth projection:** [X]% yearly growth
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- [ ] **Target capacity:** Support [N]x current load
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## Scalability Dimensions
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### Horizontal Scaling (Preferred)
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- [ ] **Stateless services:** All application servers are stateless
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- [ ] **Session storage:** Use Redis/Memcached for distributed sessions
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- [ ] **File storage:** Use object storage (S3/GCS) instead of local filesystem
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- [ ] **Auto-scaling:** Configure based on CPU/memory/RPS metrics
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- [ ] **Load balancer:** Layer 7 (application-aware) load balancing
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### Vertical Scaling (Limited)
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- [ ] **Database instance:** Right-sized for current + 6 months growth
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- [ ] **Cache instance:** Sized for working set + 20% headroom
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- [ ] **Max capacity:** Identified vertical scaling limit
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## Database Scalability
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### Read Scaling
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- [ ] **Read replicas:** [N] replicas for read-heavy workloads
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- [ ] **Read/write splitting:** Route reads to replicas, writes to primary
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- [ ] **Connection pooling:** PgBouncer/ProxySQL to limit connections
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- [ ] **Query optimization:** Queries < [10ms] with proper indexing
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### Write Scaling
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- [ ] **Sharding strategy:** [Hash-based / Range-based / Geographic]
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- Shard key: [user_id / tenant_id / region]
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- Number of shards: [N] (plan for [10x] growth)
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- [ ] **Write-ahead logging:** Asynchronous replication for replicas
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- [ ] **Bulk operations:** Batch inserts/updates to reduce round trips
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### Caching Strategy
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- [ ] **Cache layers:**
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- L1: In-memory application cache ([Caffeine / Guava])
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- L2: Distributed cache ([Redis / Memcached])
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- L3: CDN for static assets ([CloudFront / Fastly])
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- [ ] **Cache hit ratio:** Target > [90]%
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- [ ] **TTL strategy:** Balance freshness vs load ([5min] for hot data, [1h] for warm)
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- [ ] **Cache eviction:** LRU/LFU policy configured
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- [ ] **Cache warming:** Pre-populate on deployment
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- [ ] **Cache invalidation:** Event-driven invalidation for updates
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## API Gateway
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- [ ] **Rate limiting:**
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- Per-user: [N] req/min
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- Per-IP: [N] req/min
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- Burst allowance: [N] requests
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- [ ] **Request throttling:** Queue requests during spikes
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- [ ] **Response compression:** Gzip/Brotli enabled
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- [ ] **API versioning:** Support [N] concurrent versions
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## Asynchronous Processing
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- [ ] **Message queue:** [Kafka / RabbitMQ / AWS SQS]
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- Throughput: [N] messages/second
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- Retention: [X] days
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- [ ] **Worker pools:** [N] workers per queue
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- [ ] **Backpressure:** Reject requests when queue length > [N]
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- [ ] **Dead letter queue:** For failed message handling
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## Content Delivery
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- [ ] **CDN:** CloudFront/Fastly for static assets
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- [ ] **Edge caching:** Cache-Control headers configured
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- [ ] **Image optimization:** WebP format, lazy loading
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- [ ] **Asset bundling:** Minified and bundled CSS/JS
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## Data Storage Patterns
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### Hot/Warm/Cold Data
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- [ ] **Hot data:** Last [7] days in primary DB (fast access)
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- [ ] **Warm data:** Last [30] days in read replicas
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- [ ] **Cold data:** Older than [30] days archived to S3/Glacier
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- [ ] **Archival strategy:** Automated data lifecycle policies
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### Data Partitioning
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- [ ] **Time-based partitioning:** Partition by month/year for time-series data
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- [ ] **Hash partitioning:** Distribute by hash(user_id) for even distribution
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- [ ] **List partitioning:** Partition by region/tenant for isolation
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## Connection Management
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- [ ] **Database connection pool:**
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- Min connections: [N]
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- Max connections: [N]
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- Connection timeout: [Xms]
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- [ ] **HTTP keep-alive:** Reuse connections to upstream services
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- [ ] **Circuit breaker:** Prevent cascade failures
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## Observability for Scalability
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### Key Metrics
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- [ ] **Golden signals:**
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- Latency: p50, p95, p99 response times
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- Traffic: Requests per second
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- Errors: Error rate (4xx, 5xx)
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- Saturation: CPU, memory, disk, network usage
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- [ ] **Capacity metrics:**
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- Database connections used/available
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- Queue depth and processing rate
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- Cache hit/miss ratio
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- Thread pool utilization
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### Alerts
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- [ ] CPU > [70]% for [5] minutes → Scale out
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- [ ] Memory > [80]% for [5] minutes → Investigate memory leak
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- [ ] Database connections > [80]% → Add replicas
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- [ ] Queue depth > [1000] → Add workers
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- [ ] Error rate > [1]% → Page on-call
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## Load Testing
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- [ ] **Baseline test:** Measure current performance under typical load
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- [ ] **Stress test:** Identify breaking point (max capacity before failure)
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- [ ] **Spike test:** Test behavior under sudden 10x traffic spike
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- [ ] **Soak test:** Run at [2x] typical load for [24] hours
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- [ ] **Tools:** [k6 / JMeter / Gatling / Locust]
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### Load Test Scenarios
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- [ ] Scenario 1: [N] users browsing product catalog
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- [ ] Scenario 2: [N] users checking out simultaneously
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- [ ] Scenario 3: [N] API clients polling for updates
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- [ ] Target performance: p95 < [200ms], error rate < [0.1]%
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## Cost Optimization
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- [ ] **Right-sizing:** Use smallest instance that meets SLA
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- [ ] **Reserved instances:** [70]% reserved, [30]% on-demand/spot
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- [ ] **Auto-scaling policies:**
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- Scale up: When CPU > [70]% for [2] minutes
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- Scale down: When CPU < [30]% for [10] minutes
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- Min instances: [N], Max instances: [N]
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- [ ] **Database optimization:** Remove unused indexes, optimize slow queries
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- [ ] **CDN optimization:** Increase cache TTL where possible
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## Geographic Distribution
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- [ ] **Multi-region deployment:**
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- Primary region: [us-east-1]
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- Secondary region: [eu-west-1]
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- Failover: Automatic DNS failover
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- [ ] **Data locality:** Store user data in nearest region (GDPR compliance)
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- [ ] **Latency optimization:** < [100ms] within region, < [300ms] cross-region
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## Disaster Recovery
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- [ ] **RTO (Recovery Time Objective):** [X] hours
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- [ ] **RPO (Recovery Point Objective):** [X] minutes
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- [ ] **Backup frequency:** Database backup every [X] hours
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- [ ] **Failover testing:** Quarterly DR drills
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- [ ] **Data replication:** Asynchronous cross-region replication
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## Security at Scale
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- [ ] **DDoS protection:** CloudFlare/AWS Shield enabled
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- [ ] **Rate limiting:** Per-IP and per-user limits
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- [ ] **WAF rules:** Block common attack patterns
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- [ ] **Certificate management:** Auto-renewal with Let's Encrypt/ACM
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## Deployment Strategy
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- [ ] **Blue-green deployment:** Zero-downtime releases
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- [ ] **Canary releases:** [10]% traffic to new version initially
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- [ ] **Feature flags:** Toggle features without deployment
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- [ ] **Rollback plan:** Automated rollback if error rate > [X]%
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## Checklist Before Production
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- [ ] Load tested at [3x] expected peak traffic
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- [ ] Auto-scaling policies validated
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- [ ] Database read replicas configured
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- [ ] Caching strategy implemented and tested
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- [ ] Monitoring and alerts configured
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- [ ] Disaster recovery plan documented and tested
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- [ ] Cost monitoring and budgets set
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- [ ] Security review completed
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- [ ] Runbooks created for common incidents
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- [ ] On-call rotation established
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