Building a Simple Serverless Social Network on AWS

AWS Resources We’ll Use

Here’s the complete list of AWS resources for our serverless social network:

1. User Management:

   • social-userpool - Amazon Cognito user pool
   • social-idpool - Amazon Cognito identity pool

2. Database:

   • social-users-table - DynamoDB table for user profiles
   • social-posts-table - DynamoDB table for posts
   • social-follows-table - DynamoDB table for follow relationships

3. Storage:

   • social-media-bucket - S3 bucket for user uploads
   • social-processed-bucket - S3 bucket for processed media

4. API Layer:

   • social-api - API Gateway for REST endpoints
   • social-socket-api - API Gateway for WebSockets

5. Compute:

   • social-auth-function - Lambda for authentication
   • social-user-function - Lambda for user operations
   • social-post-function - Lambda for post operations
   • social-feed-function - Lambda for feed generation
   • social-upload-function - Lambda for media uploads
   • social-search-function - Lambda for search

6. Messaging:

   • social-media-queue - SQS queue for media processing
   • social-notification-topic - SNS topic for notifications

7. Media Processing:

   • social-media-convert - MediaConvert for video processing

8. Search:

   • social-search-service - OpenSearch for content search

9. Configuration & Monitoring:

   • social-app-config - AppConfig for feature flags
   • social-dashboard - CloudWatch dashboard
   • social-alarms - CloudWatch alarms

Let’s build our social network step-by-step using these resources.

Step 1: User Authentication and Profiles

We’ll start with user management, the foundation of any social network.

Resources Used:

• social-userpool: Handles user registration, authentication, and basic profile storage without building these systems from scratch
• social-idpool: Provides secure AWS credentials for users to access services directly (like S3 for uploads)
• social-users-table: Stores additional user profile data beyond what Cognito provides
• social-auth-function: Validates tokens and handles custom authorization logic

Resource Integration Flow:

[User Signup/Login] → social-userpool → [JWT Token]
                           |
                           v
                     social-idpool → [AWS Credentials]
                           |
                           v
[API Request] → social-api → social-auth-function → social-users-table

How It Works:

1. New users register through social-userpool
2. After login, they receive JWT tokens from Cognito
3. social-idpool exchanges these tokens for temporary AWS credentials
4. social-auth-function validates tokens for API requests
5. User profile data is stored and retrieved from social-users-table

This approach gives us secure authentication with minimal code, leveraging AWS’s built-in security features.

Step 2: Content Creation and Storage

Now let’s implement the core feature of our social network - creating and storing posts.

Resources Used:

• social-posts-table: Stores all post content, metadata, and relationships
• social-media-bucket: Stores media files uploaded by users (photos, videos)
• social-post-function: Handles creating, retrieving, and deleting posts
• social-upload-function: Manages secure uploads to S3
• social-media-queue: Buffers media processing requests to handle traffic spikes

Resource Integration Flow:

[Text Post] → social-api → social-post-function → social-posts-table
                                  |
                                  v
                           [Update Feed]

[Media Upload] → social-api → social-upload-function → social-media-bucket
                                       |
                                       v
                                 social-media-queue
                                       |
                                       v
                                 [Process Media]

How It Works:

1. Users create posts through the API, handled by social-post-function
2. Text content and metadata are stored directly in social-posts-table
3. For media uploads, social-upload-function generates pre-signed URLs for direct S3 upload
4. Once media is uploaded to social-media-bucket, an event notification is sent to social-media-queue
5. The queue buffers processing requests, preventing system overload during high traffic

This design handles both simple text posts and media-rich content efficiently.

Step 3: Media Processing Pipeline

Social networks need efficient media processing for different devices and bandwidth conditions.

Resources Used:

• social-media-queue: Decouples upload from processing, handling traffic spikes
• social-media-convert: Processes videos into different formats and resolutions
• social-processed-bucket: Stores optimized media for delivery to users
• social-post-function: Updates posts with processed media links

Resource Integration Flow:

[Media Upload Complete] → social-media-bucket → [S3 Event] → social-media-queue
                                                                    |
                                                                    v
                                                        [Lambda Trigger Function]
                                                                    |
                                                                    v
                                                            social-media-convert
                                                                    |
                                                                    v
                                                          social-processed-bucket
                                                                    |
                                                                    v
                                                            social-post-function
                                                                    |
                                                                    v
                                                            social-posts-table

How It Works:

1. When media is uploaded to social-media-bucket, an event is sent to social-media-queue
2. A Lambda function is triggered by the queue to start processing
3. For videos, the function creates a job in social-media-convert
4. For images, the function resizes and optimizes directly
5. Processed media is stored in social-processed-bucket
6. The post in social-posts-table is updated with links to the processed media

This pipeline ensures that all media is properly optimized for different devices and connection speeds.

Step 4: Social Graph and Feed Generation

The social graph (who follows whom) and personalized feeds are central to any social network.

Resources Used:

• social-follows-table: Stores follow relationships between users
• social-feed-function: Generates personalized feeds for users
• social-user-function: Handles user profile operations and follow relationships

Resource Integration Flow:

[Follow User] → social-api → social-user-function → social-follows-table

[Get Feed] → social-api → social-feed-function → [Query Flow]
                                  |
                   +---------------+----------------+
                   |                                |
                   v                                v
            social-follows-table           social-posts-table
                   |                                |
                   +---------------+----------------+
                                  |
                                  v
                          [Generate Feed Response]

How It Works:

1. When a user follows another user, social-user-function adds the relationship to social-follows-table
2. When a user requests their feed, social-feed-function queries:
   • social-follows-table to get the list of people they follow
   • social-posts-table to get recent posts from those users
3. The function then sorts and paginates posts before returning to the user
4. For efficiency, feed results can be cached for users with many followers

This approach creates personalized feeds that show content from people the user follows.

Step 5: Notifications System

Notifications keep users engaged and informed about activity relevant to them.

Resources Used:

• social-user-function (enhanced)
• social-post-function (enhanced)
• social-notification-topic: Distributes notifications to multiple channels
• Enhanced functions: Generate notifications for relevant activities

Resource Integration Flow:

[User Activity] → [Lambda Function] → social-notification-topic
      (like/comment)                             |
                                   +-------------+-------------+
                                   |             |             |
                                   v             v             v
                            [Email Lambda]  [Push Lambda]  [In-App Lambda]
                                   |             |             |
                                   v             v             v
                           [Send Email]   [Send Push]   [Update DynamoDB]

How It Works:

1. When a user takes action (likes/comments on a post, follows another user), the handling Lambda function publishes to social-notification-topic
2. The message includes the notification type, target user, and relevant data
3. Different Lambda functions subscribe to the topic to handle different notification channels:
   • Email notifications via Amazon SES
   • Push notifications for mobile devices
   • In-app notifications stored in DynamoDB

This design ensures users receive timely notifications through their preferred channels.

Step 6: Search Functionality

As content grows, users need a way to find specific posts and people.

Resources Used:

• social-posts-table (streams)
• social-users-table (streams)
• social-search-service: Provides full-text search capabilities
• social-search-function: Handles search requests and formats results
• DynamoDB streams: Keep search indexes up-to-date automatically

Resource Integration Flow:

[Content Change] → social-posts-table → [DynamoDB Stream] → [Index Lambda]
                                                                  |
                                                                  v
[Profile Change] → social-users-table → [DynamoDB Stream] → social-search-service

[Search Request] → social-api → social-search-function → social-search-service

How It Works:

1. When content is created or updated in DynamoDB, streams trigger indexing Lambdas
2. These Lambdas update the appropriate indexes in social-search-service
3. When a user performs a search, social-search-function queries OpenSearch
4. Results are formatted and returned to the user

This approach enables powerful search features like finding posts by content, hashtags, or usernames.

Step 7: Feature Flags and Monitoring

Proper configuration management and monitoring ensure reliable operation.

Resources Used:

• social-app-config: Manages feature flags and configuration without redeployment
• social-dashboard: Provides visibility into system performance
• social-alarms: Alerts on potential issues before they affect users

Resource Integration Flow:

[Lambda Startup] → social-app-config → [Feature Configuration]

[System Activity] → CloudWatch Metrics → social-dashboard
                           |
                           v
                     social-alarms → [Notification]

How It Works:

1. Lambda functions check social-app-config at startup to get current feature flags
2. All resources emit metrics to CloudWatch
3. social-dashboard displays key metrics in a unified view
4. social-alarms trigger notifications when metrics cross thresholds

This infrastructure ensures you can roll out features gradually and detect issues early.

Complete System Architecture

Here’s how all the components fit together to create our serverless social network:

[Users] → social-api/social-socket-api → [Lambda Functions]
           |                                    |
          /|\                                  /|\
         / | \                                / | \
        /  |  \                              /  |  \
  social   |   social              social    |   social
 -userpool |  -media-             -users-    |   -posts-
           |   bucket              table     |    table
           |      |                  |       |      |
           |      v                  |       |      |
           |  social-media-queue     |       |      |
           |      |                  |       |      |
           |      v                  |       |      |
           |  social-media-convert   |       |      |
           |      |                  |       |      |
           |      v                  |       |      |
           |  social-processed-bucket|       |      |
           |                         |       |      |
           +-----------------+-------+-------+------+
                             |
                             v
                   social-notification-topic
                             |
                         [Delivery]
                             
[Search] → social-search-function → social-search-service

[Monitoring] → social-dashboard → social-alarms

Why This Serverless Architecture Works

This serverless social network architecture provides several advantages:

1. Automatic Scaling: Every component scales based on demand - no capacity planning needed
2. Cost Efficiency: Pay only for what you use, ideal for growing platforms
3. Rapid Development: Managed services reduce custom code and maintenance
4. High Availability: AWS services include built-in redundancy across availability zones
5. Simplified Operations: No servers to manage, patch, or scale manually

Most importantly, this architecture handles the unpredictable traffic patterns common to social networks. When a post goes viral or a celebrity joins, the system scales automatically to handle the load without intervention.

Conclusion: Build, Learn, Evolve

The design I’ve outlined gives you a solid foundation for a serverless social network. Start with these core components and evolve as you learn what your users need. The beauty of serverless is that you can add capabilities incrementally without rebuilding your infrastructure.

As your network grows, you’ll discover opportunities to enhance specific features. AWS’s serverless ecosystem makes it easy to plug in additional services as needed, whether that’s AI for content moderation, sophisticated analytics, or advanced recommendation systems.

The most important advice: build something users love and let AWS handle the infrastructure scaling. That’s the true power of serverless architecture for social networks.