Data Layer Architecture Management
Standardizes the implementation of data fetching, caching, and storage patterns for complex Next.js applications.
This skill provides specialized guidance for working within the ethereum.org data-layer architecture, ensuring consistency when managing external data sources. It facilitates the creation of standardized fetchers, centralized task keys for Trigger.dev, and storage abstractions that toggle between production Netlify Blobs and local mock files. By enforcing architectural rules such as pure passthrough getters and cached wrappers, it helps developers maintain a scalable and performant data pipeline for high-traffic documentation and resource sites.
Key Features
01Seamless storage abstraction between Netlify Blobs and local mocks
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03Standardized fetcher and transformer implementation patterns
04Centralized task management for Trigger.dev schedules
05Automated workflow for adding new external data sources
06Next.js caching adapter integration for optimized data retrieval
Use Cases
01Setting up local development environments with mock data to reduce API dependency
02Integrating a new external API or data source into the ethereum.org website
03Configuring scheduled data updates for metrics like ETH price or L2 statistics