DogStark/Petchain_analytics

AI Summary: Implement robust input validation and data sanitization for the Petchain analytics APIs using NestJS pipes. This involves leveraging class-validator and class-transformer to check data types, ranges, lengths, and sanitize inputs to prevent security vulnerabilities like SQL injection and XSS, ensuring data integrity before processing.

AI Summary: Integrate a metrics collection system (like Prometheus with @nestjs/terminus) into the NestJS application within the Petchain analytics project to monitor key performance indicators (CPU, memory, latency, errors, connections). Set up dashboards (e.g., Grafana) to visualize these metrics for performance management and bottleneck detection.

AI Summary: Implement a caching layer (e.g., using Redis and @nestjs/cache-manager) for frequently accessed analytics API endpoints in the Petchain analytics project to improve performance and reduce database load. This involves selecting appropriate endpoints for caching, defining cache invalidation strategies, and integrating the caching mechanism into the existing NestJS application.

AI Summary: Design and implement a secure and efficient ID generation and management system for pets and their owners within the Petchain Starknet contracts. This involves choosing an appropriate method (e.g., hashing or sequential counters), ensuring collision resistance and non-guessability, and consistently applying the chosen method across all contract functions.

AI Summary: Optimize the NestJS services responsible for aggregating pet health data to generate trends. This involves improving database queries (using indexes and potentially materialized views) and in-memory processing to ensure fast response times for analytics dashboards, even with a large volume of health records.