The Cortex Reporting Types module forms the backbone of Sophra’s advanced analytics and monitoring capabilities. This crucial component defines the structure and behavior of the system’s intelligent reporting, recommendation engine, and alerting mechanisms. By leveraging TypeScript’s robust type system, it ensures type safety and provides a clear contract for data flow throughout the Sophra ecosystem.

At its core, this module introduces three pivotal interfaces: Recommendation, AlertConfig, and DistributionConfig. These interfaces work in concert to enable Sophra’s adaptive learning system, providing real-time insights, performance optimizations, and proactive issue detection. The Recommendation interface, for instance, encapsulates the system’s ability to generate smart suggestions, ranging from caching strategies to resource allocation advice.

The architectural decision to separate these types into a dedicated module reflects Sophra’s commitment to modularity and scalability. By centralizing these definitions, the system maintains consistency across various services while allowing for easy extension and modification of reporting capabilities. This approach also facilitates the integration of machine learning pipelines, enabling the system to continuously refine its recommendations based on evolving data patterns and user interactions.

From a performance perspective, the lean design of these interfaces ensures minimal overhead when passing data between services. The use of discriminated unions for properties like type and priority in the Recommendation interface allows for efficient pattern matching and type inference throughout the codebase. This design choice not only enhances runtime performance but also improves developer productivity by providing clear, self-documenting code.

One of the unique features of this module is its integration with Sophra’s analytics engine. The AlertConfig interface, for example, directly references metrics from the AnalyticsReport type, creating a tight coupling between the system’s data collection and its alerting mechanisms. This integration enables highly targeted and context-aware alerts, significantly reducing noise and focusing attention on truly critical issues.

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Exported Components

interface Recommendation {
  type: "cache" | "performance" | "resource" | "error";
  priority: "low" | "medium" | "high" | "critical";
  message: string;
  metrics: Record<string, number>;
  action?: string;
}

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Recommendation Interface

The Recommendation interface defines the structure for intelligent suggestions generated by Sophra’s adaptive learning system.

  • type: Categorizes the recommendation (cache, performance, resource, or error)
  • priority: Indicates the urgency of the recommendation
  • message: Provides a human-readable description of the suggestion
  • metrics: Contains relevant numerical data supporting the recommendation
  • action: Optional field suggesting a specific action to take

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AlertConfig Interface

AlertConfig specifies the conditions for triggering system alerts based on analytics metrics.

  • metric: References a specific metric from the AnalyticsReport
  • operator: Defines the comparison logic (greater than, less than, or equal to)
  • value: Sets the threshold for triggering the alert
  • severity: Indicates the importance of the alert

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DistributionConfig Interface

DistributionConfig outlines the various channels and methods for distributing reports and alerts.

  • email: Configuration for email-based report distribution
  • slack: Settings for Slack notifications
  • storage: Options for persisting reports to various storage systems

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Implementation Examples

import { Recommendation } from '@/lib/cortex/reporting/types';

const generateCacheRecommendation = (hitRate: number): Recommendation => {
  return {
    type: "cache",
    priority: hitRate < 0.5 ? "high" : "medium",
    message: `Consider optimizing cache strategy. Current hit rate: ${hitRate * 100}%`,
    metrics: { hitRate },
    action: "Review caching policies and increase cache size if necessary."
  };
};

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Sophra Integration Details

The Cortex Reporting Types module integrates deeply with Sophra’s analytics and monitoring services. Here’s a detailed look at its interactions:

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Error Handling

The Cortex Reporting Types module incorporates robust error handling strategies:

Error Scenarios and Recovery

  • Invalid metric references in AlertConfig are caught during configuration validation, preventing runtime errors.
  • Distribution failures (e.g., email delivery issues) are logged and retried with exponential backoff.
  • Malformed recommendations are filtered out before distribution, ensuring only valid insights reach end-users.

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Data Flow

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Performance Considerations

The Cortex Reporting Types module is designed for optimal performance:

  • Lean interface designs minimize memory footprint
  • Use of discriminated unions enables efficient type checking and pattern matching
  • Caching of frequently accessed configurations improves response times

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Security Implementation

Security is a top priority in the Cortex Reporting module:

  • All distribution channels (email, Slack) require authentication
  • S3 and GCS storage options use IAM roles for secure access
  • Sensitive data in recommendations and alerts is encrypted at rest and in transit

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Configuration

SOPHRA_ALERT_THRESHOLD=0.95
SOPHRA_REPORT_RETENTION_DAYS=90
SOPHRA_DISTRIBUTION_CONCURRENCY=5