moai-domain-backend-architecture

Guide backend architecture for scalable APIs and infrastructure using Kubernetes, Istio, OpenTelemetry, and Prometheus.

1|Updated Jul 28, 2025

Search Tags:#architecture #api #backend

Ready to run

npx skills add https://github.com/kivo360/quickhooks --skill moai-domain-backend-architecture

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: moai-domain-backend-architecture
Source: https://github.com/kivo360/quickhooks/tree/main/.claude/skills/moai-domain-backend
Command: npx skills add https://github.com/kivo360/quickhooks --skill moai-domain-backend-architecture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides backend architecture guidance for server-side APIs and data services.

Core Features & Use Cases

API Design: REST, GraphQL, gRPC patterns.
Data Layer: Repositories, ORMs, and migrations.
Observability: Monitoring and tracing.

Quick Start

Design a layered or modular monolith for a new service.

Frequently Asked Questions about moai-domain-backend-architecture

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design a scalable backend architecture for APIs?▼

Scalable backend architecture uses layered or modular patterns with API design (REST, GraphQL, gRPC), repository layers for data access, caching strategies, and horizontal scaling via Kubernetes. Start by decomposing your service into logical layers, then apply cloud-native patterns and observability instrumentation to monitor performance as load increases.

What's the best way to optimize database performance in a backend service?▼

Database optimization combines ORM usage, migration strategies, and caching approaches. Apply repository patterns to abstract data access, use query optimization and connection pooling, and layer caching strategies between your API and database to reduce latency and improve throughput at scale.

How do I implement observability in a distributed backend system?▼

Observability requires monitoring and tracing instrumentation across your services. Use tools like OpenTelemetry and Prometheus to collect metrics, traces, and logs from your API and infrastructure. Instrument your code to emit telemetry, then aggregate signals to detect bottlenecks and troubleshoot failures.

When should I use Kubernetes and Istio for backend deployment?▼

Kubernetes orchestrates containerized backend services for horizontal scaling and resilience. Istio provides service mesh capabilities for traffic management, security, and observability between services. Use them together when you need reliable, observable deployment of multiple interdependent APIs at scale.

What are the trade-offs between REST, GraphQL, and gRPC for API design?▼

REST is simple and cacheable but verbose; GraphQL reduces over-fetching with client-driven queries but adds server complexity; gRPC uses binary protocols for high-performance service-to-service communication. Choose based on client needs, latency requirements, and ecosystem maturity for your use case.