🏗️ Scaling Applications with TuskLang Ruby SDK

"We don't bow to any king" – Scale beyond limits.

TuskLang for Ruby is built for scale: from single-server Rails apps to global, distributed systems. These patterns and tools will help you scale your configuration logic, optimize for high concurrency, and keep your systems robust under load.

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🌐 Why Scaling Matters in TuskLang

- Dynamic configs: Scaling means configs must be fast and consistent everywhere - Distributed systems: Configs must sync across nodes and environments - Concurrency: Avoid bottlenecks in config evaluation

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🏢 Core Scaling Features

1. Distributed Caching

Use @cache with distributed stores (Redis, Memcached):

[cache]
user_sessions: @cache("10m", @query("SELECT * FROM sessions WHERE active=1"))

Ruby Usage:

require 'tusk_lang'
config = TuskLang::TSK.from_file('config.tsk')
sessions = config.get_value('cache', 'user_sessions')

2. Config Synchronization

Sync TSK files across servers with shared storage or CI/CD:

rsync config/app.tsk user@server:/app/config/app.tsk

3. Sharding and Partitioning

Split configs for different services or tenants:

[tenant_a]
db_url: "postgres://a..."
[tenant_b]
db_url: "postgres://b..."

4. Rate Limiting and Throttling

Use @rate_limit to protect resources:

[api]
rate_limit: @rate_limit("100/minute")

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🚂 Rails & Jekyll Integration

Rails: Multi-Process and Clustered Apps

- Use Puma/Unicorn with preloaded TSK configs - Share cache via Redis for cross-process consistency

$tsk_config ||= TuskLang::TSK.from_file('config/app.tsk')

Jekyll: Large-Scale Static Sites

- Use TSK to generate thousands of pages efficiently - Cache expensive computations at build time

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🧩 Advanced Scaling Patterns

1. Dynamic Feature Rollouts

Enable features for subsets of users:

[features]
beta_access: @if(@query("SELECT beta FROM users WHERE id=$user_id") == true, true, false)

2. Global Config Distribution

Distribute configs via CDN or object storage:

aws s3 cp config/app.tsk s3://mybucket/config/app.tsk

3. Auto-Scaling Config Logic

Adapt config based on load:

[autoscale]
worker_count: @if(@metrics("cpu_load") > 0.7, 8, 4)

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🚨 Troubleshooting

- Stale configs? Use distributed cache and sync scripts - Scaling bottlenecks? Profile config evaluation and cache aggressively - Rate limit errors? Tune @rate_limit values for your traffic

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⚡ Scaling & Performance Notes

- Performance: Use distributed cache for all shared config data - Security: Sync configs securely, never expose secrets - Best Practice: Monitor, profile, and adapt scaling logic

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🏆 Best Practices

- Use @cache and distributed stores for all shared data - Sync configs via CI/CD or storage - Partition configs for multi-tenant systems - Document your scaling patterns

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Master scaling in TuskLang Ruby and grow without fear. 🏗️