Detailed component design

Meeting Management Service

Functionality:

Meeting Creation and Editing: Handles requests to create or modify meetings, setting details like date, time, duration, participants, and agenda.
Recurring Meetings: Stores recurrence rules and generates future occurrences based on user-specified intervals (daily, weekly, monthly).

Detailed Design:

Data Storage: Relational database (e.g., PostgreSQL) for structured meeting data, ensuring data integrity and supporting complex queries.
API Endpoints:
- POST /meetings: Create a new meeting, validate details, and save.
- PUT /meetings/{id}: Update meeting details.
- DELETE /meetings/{id}: Delete a meeting and associated data like notifications.
Recurring Meeting Processing:
- Option 1: Store recurrence rules and create only the first instance in the database. A scheduler creates future instances when the date approaches.
- Option 2: Pre-generate instances for a set period (e.g., a month) and add them to the database.

Tradeoffs:

Option 1 (Generate instances on demand):
- Pros: Saves storage and avoids having to store many future events, making updates to recurrence rules easier.
- Cons: Requires a scheduler, which can add latency for retrieval and complexity in managing when to create new instances.
Option 2 (Pre-generate instances):
- Pros: Faster querying and predictable scheduling; users can see all occurrences in advance.
- Cons: Higher storage usage, especially if many users schedule recurring meetings, and more complex updates if a rule changes.

2. Notification Service

Functionality:

Notifications and Reminders: Send notifications before meetings and updates on changes or cancellations.
Notification Channels: Supports email and SMS (extendable to push notifications).

Detailed Design:

Queue-based Processing: A messaging queue (e.g., RabbitMQ or Apache Kafka) processes notification tasks asynchronously, decoupling the Notification Service from other services.
Scheduler Integration: Uses a task scheduler (e.g., Celery, Quartz) to send notifications based on meeting start times and user preferences.
API Endpoints:
- POST /notifications: Schedule a notification for a meeting.
- DELETE /notifications/{id}: Cancel scheduled notifications for canceled or rescheduled meetings.
Database Schema:
- notification_id, meeting_id, user_id, send_at, status.

Tradeoffs:

Email vs. SMS vs. Push:
- Email: Reliable, but can be delayed by email providers and may end up in spam.
- SMS: Quicker but costlier per message; better suited for urgent reminders.
- Push: Free and instant but requires an app.
Immediate vs. Scheduled Notifications:
- Immediate: Directly trigger a notification for important changes; uses resources quickly but provides instant feedback.
- Scheduled: Queue notifications and rely on a scheduler, improving scalability but adding some delay.

3. User Service

Functionality:

User Management: Handles user profile data, authentication, and role-based access control.
Participant Management: Tracks RSVPs for each meeting and notifies users of meeting changes.

Detailed Design:

Authentication:
- Uses JWT tokens or OAuth2 for secure, scalable authentication.
- External OAuth providers (e.g., Google or Microsoft) are optional, enabling calendar integration.
User Data Storage:
- Stores users with a user_id, name, email, phone, and roles in a relational database.
Participant Management:
- Each meeting can have multiple participants, with a relational link (join table) in a Participants table for efficient lookups.

Tradeoffs:

OAuth Integration:
- Pros: Easier access to third-party calendars, secure authentication.
- Cons: More complex implementation and handling of third-party API rate limits.
Relational vs. NoSQL Storage for User Data:
- Relational: Easier to query relationships between meetings and participants.
- NoSQL: Better for high read/write scalability but more complex joins for relational data.

4. Availability Service

Functionality:

Availability Checking: Prevents scheduling conflicts by checking user availability.
Integration with External Calendars: Syncs with Google Calendar, Outlook, etc., to get real-time availability.

Detailed Design:

Internal Availability Check:
- Query the database for user schedules and compare proposed meeting times.
- Store availability blocks in a separate table with user_id, busy_start, and busy_end.
External Calendar Sync:
- Use APIs (e.g., Google Calendar API) to pull busy/free data for participants.
- Data is either cached for performance or requested on-demand based on rate limits.
API Endpoints:
- GET /availability/check: Check availability for specified users within a time range.

Tradeoffs:

On-Demand vs. Cached External Availability:
- On-Demand: Real-time accuracy but more API calls and can hit rate limits.
- Cached: Reduces API calls, but data can be slightly outdated and may need refresh logic.
Availability Block Storage:
- Database: Simplifies data management and retrieval for internal schedules.
- In-Memory Store (e.g., Redis): Faster but requires synchronization with the database.

In a detailed design for a meeting scheduling system, we break down each core functionality, describe the technical components involved, and evaluate tradeoffs for scalability, maintainability, and complexity. Below, I’ll cover each core service, how it works, and some design choices with tradeoffs.

1. Meeting Management Service

Functionality:

Meeting Creation and Editing: Handles requests to create or modify meetings, setting details like date, time, duration, participants, and agenda.
Recurring Meetings: Stores recurrence rules and generates future occurrences based on user-specified intervals (daily, weekly, monthly).

Detailed Design:

Data Storage: Relational database (e.g., PostgreSQL) for structured meeting data, ensuring data integrity and supporting complex queries.
API Endpoints:
- POST /meetings: Create a new meeting, validate details, and save.
- PUT /meetings/{id}: Update meeting details.
- DELETE /meetings/{id}: Delete a meeting and associated data like notifications.
Recurring Meeting Processing:
- Option 1: Store recurrence rules and create only the first instance in the database. A scheduler creates future instances when the date approaches.
- Option 2: Pre-generate instances for a set period (e.g., a month) and add them to the database.

Tradeoffs:

Option 1 (Generate instances on demand):
- Pros: Saves storage and avoids having to store many future events, making updates to recurrence rules easier.
- Cons: Requires a scheduler, which can add latency for retrieval and complexity in managing when to create new instances.
Option 2 (Pre-generate instances):
- Pros: Faster querying and predictable scheduling; users can see all occurrences in advance.
- Cons: Higher storage usage, especially if many users schedule recurring meetings, and more complex updates if a rule changes.

2. Notification Service

Functionality:

Notifications and Reminders: Send notifications before meetings and updates on changes or cancellations.
Notification Channels: Supports email and SMS (extendable to push notifications).

Detailed Design:

Queue-based Processing: A messaging queue (e.g., RabbitMQ or Apache Kafka) processes notification tasks asynchronously, decoupling the Notification Service from other services.
Scheduler Integration: Uses a task scheduler (e.g., Celery, Quartz) to send notifications based on meeting start times and user preferences.
API Endpoints:
- POST /notifications: Schedule a notification for a meeting.
- DELETE /notifications/{id}: Cancel scheduled notifications for canceled or rescheduled meetings.
Database Schema:
- notification_id, meeting_id, user_id, send_at, status.

Tradeoffs:

Email vs. SMS vs. Push:
- Email: Reliable, but can be delayed by email providers and may end up in spam.
- SMS: Quicker but costlier per message; better suited for urgent reminders.
- Push: Free and instant but requires an app.
Immediate vs. Scheduled Notifications:
- Immediate: Directly trigger a notification for important changes; uses resources quickly but provides instant feedback.
- Scheduled: Queue notifications and rely on a scheduler, improving scalability but adding some delay.

3. User Service

Functionality:

User Management: Handles user profile data, authentication, and role-based access control.
Participant Management: Tracks RSVPs for each meeting and notifies users of meeting changes.

Detailed Design:

Authentication:
- Uses JWT tokens or OAuth2 for secure, scalable authentication.
- External OAuth providers (e.g., Google or Microsoft) are optional, enabling calendar integration.
User Data Storage:
- Stores users with a user_id, name, email, phone, and roles in a relational database.
Participant Management:
- Each meeting can have multiple participants, with a relational link (join table) in a Participants table for efficient lookups.

Tradeoffs:

OAuth Integration:
- Pros: Easier access to third-party calendars, secure authentication.
- Cons: More complex implementation and handling of third-party API rate limits.
Relational vs. NoSQL Storage for User Data:
- Relational: Easier to query relationships between meetings and participants.
- NoSQL: Better for high read/write scalability but more complex joins for relational data.

4. Availability Service

Functionality:

Availability Checking: Prevents scheduling conflicts by checking user availability.
Integration with External Calendars: Syncs with Google Calendar, Outlook, etc., to get real-time availability.

Detailed Design:

Internal Availability Check:
- Query the database for user schedules and compare proposed meeting times.
- Store availability blocks in a separate table with user_id, busy_start, and busy_end.
External Calendar Sync:
- Use APIs (e.g., Google Calendar API) to pull busy/free data for participants.
- Data is either cached for performance or requested on-demand based on rate limits.
API Endpoints:
- GET /availability/check: Check availability for specified users within a time range.

Tradeoffs:

On-Demand vs. Cached External Availability:
- On-Demand: Real-time accuracy but more API calls and can hit rate limits.
- Cached: Reduces API calls, but data can be slightly outdated and may need refresh logic.
Availability Block Storage:
- Database: Simplifies data management and retrieval for internal schedules.
- In-Memory Store (e.g., Redis): Faster but requires synchronization with the database.

5. Search and Filter Service

Functionality:

Search Meetings: Allows users to search meetings by title, date, or participants.
Filters: Supports filtering by attributes like dates, keywords, and participant lists.

Detailed Design:

Search Engine:
- Option 1: Database search with SQL and indexing (simple, low-cost for small datasets).
- Option 2: Use a dedicated search engine like Elasticsearch for faster, full-text search.
Caching:
- Caches popular search results or commonly filtered items to improve performance.
API Endpoints:
- GET /meetings/search: Search by title, participant, date, etc.

Tradeoffs:

SQL Search vs. Elasticsearch:
- SQL Search: Efficient for structured queries, simpler to manage; may slow down with large datasets.
- Elasticsearch: Optimized for full-text search, ideal for larger datasets; adds infrastructure and complexity.

Submissions

Displaying Solutions with Scores Ranging from 1 to 10