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zarinpal-analytics-deployment/docs/REFERENCES.md

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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: https://martin.kleppmann.com/2017/03/27/designing-data-intensive-applications.html

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: https://sre.google/sre-book/table-of-contents/

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: https://pragprog.com/titles/mnee2/release-it-second-edition/

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: https://www.anthropic.com/engineering/building-effective-agents

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: https://docs.avalai.ir:8443/en/

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: https://www.zarinpal.com/ 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

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

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 trusted-runner release orchestration. Exact product versions and runner capabilities remain explicit approval decisions rather than assumptions.

Qlockify deployment reference

Local read-only source: D:/Programing/Scripts/Qlockify/qlockify-deployment

Applied as a proven three-repository, Compose, Nginx, ACME, nested-checkout, and encrypted off-host backup reference. ZarinPal deliberately hardens the pattern by deploying immutable image digests instead of resetting/building mutable server checkouts, excluding environment/secrets from database backup packages, separating migrations/import from application startup, guarding production restore, and omitting scheduled application workers.