# Engineering References and Applied Principles Reference documents provide evidence and design guidance; they do not override approved project specs or agent rules. ## Designing Data-Intensive Applications — Martin Kleppmann Source: Applied here through explicit reliability, scalability, and maintainability trade-offs; immutable import provenance; idempotent processing; derived-data rebuildability; and separating the logical data model from physical indexes/materializations chosen from measured access patterns. ## Site Reliability Engineering — Google Source: Applied here through service-level objectives before operational tuning, actionable monitoring, release health checks, rollback readiness, capacity awareness, and restore rehearsal rather than backup existence alone. ## Release It!, Second Edition — Michael T. Nygard Source: Applied here through bounded resources, timeouts, backpressure, failure isolation, explicit readiness/liveness, safe startup/shutdown, and treating production behavior as part of design rather than a deployment afterthought. ## Building Effective Agents — Anthropic Source: Applied to the post-MVP AI capability: begin with deterministic analytics and the simplest bounded LLM workflow, add agentic autonomy only where evaluation demonstrates value, keep tools/data access explicit, and retain human-readable traces and budgets. ## AI Agents and Cloud Patterns — course slides Local source: `C:/Users/Eight/Downloads/ai_agents_cloud_patterns_1405.pdf` Applied to future AI execution through durable job/session state, idempotency, queue boundaries, traceability, execution budgets, authentication/authorization, and an outbox-style handoff where cross-system delivery must be reliable. ## AvalAI documentation Source: Applied as a post-MVP integration constraint: AvalAI credentials remain backend-only; provider/model configuration is environment-driven and pinned; requests receive timeouts and bounded retries; prompts receive minimized aggregate data; and provider responses cannot become the analytical source of truth. ## ZarinPal visual references Source: plus the user-supplied authenticated desktop/mobile screenshots. Applied in the frontend repository's `DESIGN.md`: Persian RTL layout, right-side navigation/drawer, spacious light canvas, white cards, blue action/active states, dark ink surfaces, restrained yellow accent, rounded geometry, and responsive behavior. Proprietary assets/fonts are used only if legally supplied. ## Framework documentation - SvelteKit introduction: - Go documentation: Framework decisions remain subordinate to capability requirements. SvelteKit is used as a TypeScript application framework without assuming SEO/SSR; Go is used for the backend with architecture, DI, database access, and API choices approved through the specification process. ## Platform operations documentation - Docker Compose application model: - Docker Compose startup order: - Docker Engine logging: - Nginx proxy module: - Nginx TLS module: - PostgreSQL backup and restore: - PostgreSQL SQL dumps: - PostgreSQL official image tags: - Redis official image tags: - Nginx official image tags: - Certbot official image tags: Applied in `PLATFORM-OPERATIONS-SPEC.md` through health-gated Compose startup, isolated networks and secrets, bounded container logs, TLS/SSE proxy behavior, logical PostgreSQL backup with guarded restore, and the approved exact image tags and resource limits. ## Qlockify deployment reference Local read-only source: `D:/Programing/Scripts/Qlockify/qlockify-deployment` Applied as the approved three-repository, manual server-build, Compose, Nginx, ACME, nested-checkout, and encrypted off-host backup reference. ZarinPal keeps that simple deployment shape while excluding environment/secrets from database backup packages, separating migrations/import from application startup, refusing destructive Git synchronization on dirty checkouts, guarding production restore, and omitting scheduled application workers.