当执行实现新功能或增强现有功能的任务时，开发人员通常会面临有关最佳方法的决策。 Copilot Chat 可以通过分析问题并生成实现选项来帮助你探索多个解决方案。
示例方案
你被分配了创建一项新功能的任务，要求实现在用户仪表板上显示最近查看的项目。 下面是实现此功能的示例议题：
[Feature Request] Add "Recent Items" section to user dashboard #753
## Issue Description
Users have requested a "Recent Items" section on their dashboard to quickly access the most recently viewed documents, projects, or files. This section should display the ten most recent items, sorted by the last access time.
## Requirements
* Display up to ten items that the user has accessed recently.
* Items must be sorted by the time they were last accessed.
* The solution should minimize database load.
* Data should reflect updates in near real-time.
* The solution should prioritize performance, especially for large datasets of items.
## Acceptance Criteria
* Dashboard loads the "Recent Items" section within 200ms under normal load.
* The solution must not degrade performance for users with thousands of items.
示例提示
你想要评估此实现的不同方法，以了解它们是否符合你的需求和约束。 在这里，我们将要求 Copilot Chat 建议不同的方法。
导航到议题，然后键入：
Given the criteria in Issue #753, list options for implementation and tradeoffs for each option.
Tip
使用 Copilot 来帮助识别实现选项时，最好从常规提示开始激发想法，如此示例所示。 然后，可以跟进更具体的问题，以更深入地了解它建议的选项。
示例响应
Note
以下响应是示例。 Copilot Chat 响应是不确定的，所以你可能会得到与这里所显示的不同的响应。
Copilot 列出了实现该仪表板的几种不同选项，以及每种选项的权衡。 然后，它会提出建议。
例如：
# Implementation Options and Tradeoffs for "Recent Items" Section
## 1. Client-Side Storage
- Description: Store recent items data in the user's browser using LocalStorage or IndexedDB.
- Tradeoffs:
- Pros:
- Reduces server load by handling data storage and retrieval on the client side.
- Immediate updates and access without server communication.
- Cons:
- Limited by browser storage capacity.
- Data lost if the user clears browser storage or switches devices.
- Security concerns with storing sensitive data on the client side.
## 2. Server-Side Storage with Database Indexing
- Description: Store recent items in the database and use indexing to quickly retrieve the most recent items.
- Tradeoffs:
- Pros:
- Centralized data storage, accessible from any device.
- Scalable and can handle large datasets efficiently with proper indexing.
- Cons:
- Increased database load, especially for frequent access updates.
- Potential latency in updating the recent items list.
## 3. In-Memory Caching (e.g., Redis)
- Description: Use an in-memory data store like Redis to cache recent items for fast retrieval.
- Tradeoffs:
- Pros:
- Extremely fast data access and updates.
- Reduces database load by offloading frequent read operations.
- Cons:
- Requires additional infrastructure and maintenance.
- Data may be lost if the cache is cleared or server restarts.
## 4. Hybrid Approach
- Description: Combine server-side storage with in-memory caching to balance performance and persistence.
- Tradeoffs:
- Pros:
- Fast access through caching, with persistent storage in the database.
- Can handle large datasets and frequent updates efficiently.
- Cons:
- Increased complexity in implementation and maintenance.
- Potential consistency issues between cache and database.
## 5. Event-Driven Updates
- Description: Use event-driven architecture to update recent items in real-time as users access documents.
- Tradeoffs:
- Pros:
- Near real-time updates with minimal delay.
- Efficient handling of updates through events rather than periodic polling.
- Cons:
- Requires setting up event handling infrastructure (e.g., message queues).
- Increased complexity in managing events and ensuring consistency.
## Recommendation
The hybrid approach (option 4) is a balanced solution, offering fast access through caching and persistence through database storage. It meets performance requirements and scales well with a large dataset, although it involves a more complex implementation.