Comprehensive type definitions and schemas for Sophra’s configuration system
types.ts
file within the src/lib/nous/config
directory serves as the cornerstone for Sophra’s configuration management system. This module defines a robust set of TypeScript interfaces and Zod schemas that encapsulate the entire configuration structure of the Sophra platform. By leveraging Zod, a TypeScript-first schema declaration and validation library, Sophra ensures type safety and runtime validation for all configuration parameters across its microservices architecture.
The configuration system is designed to support Sophra’s scalable and modular architecture, providing type definitions for various components including server settings, registry management, observability, and machine learning pipelines. This granular approach to configuration allows for fine-tuned control over different aspects of the system, enabling developers to optimize performance and tailor the behavior of Sophra to specific deployment environments.
One of the key architectural decisions reflected in this module is the use of environment-specific configurations. The Environment
enum facilitates the definition of distinct settings for development, staging, and production environments, allowing for seamless transitions between different deployment stages. This approach aligns with best practices for configuration management in cloud-native applications, ensuring consistency and reducing the risk of environment-specific issues.
Performance considerations are evident in the default values and structure of the configuration schemas. For instance, the ObserveConfigSchema
includes parameters for event buffering and batch processing, which can be fine-tuned to optimize the system’s observability pipeline for different workloads and hardware configurations. Similarly, the LearnConfigSchema
provides controls for model caching and training batch sizes, allowing for performance optimization of the machine learning components.
A unique feature of this configuration system is its extensibility. The additionalSettings
field in the ConfigSchema
allows for the inclusion of arbitrary key-value pairs, providing flexibility for future expansions or custom configurations without requiring changes to the core schema definition. This forward-thinking design ensures that Sophra can adapt to new requirements and integrate with various external systems without compromising type safety or validation.
ServerConfigSchema
host
: string (default: “0.0.0.0”)port
: number (default: 3000)corsOrigins
: string[] (default: [”*”])corsAllowCredentials
: boolean (default: true)corsAllowMethods
: string[] (default: [”*”])corsAllowHeaders
: string[] (default: [”*”])RegistryConfigSchema
storagePath
: stringmaxVersionsPerEntry
: number (default: 10)enableVersionPruning
: boolean (default: true)metadataValidation
: boolean (default: true)ObserveConfigSchema
eventBufferSize
: number (default: 1000)batchSize
: number (default: 100)processingIntervalMs
: number (default: 500)LearnConfigSchema
modelCacheSize
: number (default: 5)trainingBatchSize
: number (default: 32)evaluationInterval
: number (default: 1000)minSamplesRequired
: number (default: 100)ServerConfig
is used by the API Gateway to set up CORS and server parameters.RegistryConfig
governs the behavior of Sophra’s data registry, including version management.ObserveConfig
is utilized by the Analytics Engine to configure event processing and metrics collection.LearnConfig
is consumed by the Machine Learning Pipeline to optimize model training and caching.modelCacheSize
in LearnConfig
allows for tuning of memory usage vs. performance in ML operations.eventBufferSize
and batchSize
in ObserveConfig
can be adjusted to optimize throughput and latency in the observability pipeline.eventBufferSize
and batchSize
to reduce processing overhead.corsOrigins
setting in ServerConfig
allows for precise control over allowed origins, mitigating CORS-related vulnerabilities.metadataValidation
in RegistryConfig
ensures data integrity in the registry.types.ts
.