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Skills IA documentation architecture patterns

Découvrez les skills documentation architecture patterns, comparez leurs dépôts et consultez leurs instructions.

Catégories: documentation architecture patterns

4,681–4,704 sur 6,626

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GitHub

data-contracts

AmnadTaowsoam

Implementing formal agreements between data producers and consumers to ensure data reliability and stability.

GitHub

openapi-governance

AmnadTaowsoam

Comprehensive guide to OpenAPI governance, API design standards, automated linting, breaking change detection, and API lifecycle management

GitHub

dependency-mapping

AmnadTaowsoam

Comprehensive guide to identifying, visualizing, and managing dependencies in complex projects to reduce risks and enable coordination

GitHub

saga-pattern

AmnadTaowsoam

Implementing distributed transactions across microservices using the Saga pattern with choreography and orchestration approaches.

GitHub

environment-matrix-devstgprod

AmnadTaowsoam

Environment standards for development, staging, and production: parity principles, data and access policies, configuration boundaries, and deployment controls

GitHub

tenant-aware-ops

AmnadTaowsoam

Operational patterns for multi-tenant systems: tenant-safe debugging and monitoring, per-tenant maintenance and migrations, fairness controls, and compliance-aware access

GitHub

architecture-review

AmnadTaowsoam

Structured process for reviewing and validating architectural decisions before implementation to catch issues early.

GitHub

bulkhead-patterns

AmnadTaowsoam

Resource isolation strategies to prevent cascading failures and limit blast radius in distributed systems

GitHub

event-sourcing

AmnadTaowsoam

Implementing event sourcing pattern for maintaining application state as a sequence of immutable events.

GitHub

agent-self-correction

AmnadTaowsoam

Protocols for the agent to autonomously detect failures, analyze root causes, and attempt recovery strategies before requesting user intervention.

GitHub

ai-model-registry

AmnadTaowsoam

Centralized management of machine learning models throughout their lifecycle, including versioning, metadata, and production deployment.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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