Webhook System Design - One Pager

Overview

A scalable webhook delivery system that enables users to register webhooks for specific events and reliably delivers event notifications to registered endpoints with comprehensive monitoring and retry capabilities.

Functional Requirements

FR1: User Webhook Registration

• Users can register webhooks with custom URLs, authentication methods, and event types
• Support for webhook configuration including expiration time and retry policies
• Ability to manage (create, update, delete) webhook subscriptions

FR2: Event-Triggered Webhook Callbacks

• System automatically triggers webhook callbacks when registered events occur
• Asynchronous processing of webhook deliveries
• Support for multiple event types and selective webhook routing

FR3: Webhook Observability

• Users can monitor webhook delivery status and execution history
• Detailed execution logs with success/failure tracking
• Real-time status updates and historical analytics

Non-Functional Requirements

NFR1: At-Least-Once Delivery Guarantee

• Implement retry mechanisms with configurable retry strategies
• Persistent execution queue to prevent message loss
• Idempotency considerations for duplicate deliveries

NFR2: High Availability & Horizontal Scalability

• Distributed worker architecture for processing webhook deliveries
• Load balancer for distributing traffic across services
• Stateless services to enable easy scaling

NFR3: Security

• Authentication support for webhook endpoints
• Secure storage of webhook credentials
• Request signing and validation mechanisms

System Architecture

Core Components

1. Webhook Manager Service

• Responsibility: Handle webhook CRUD operations
• API Endpoints:
  • POST /webhooks - Register new webhook
  • GET /webhooks/{id} - Retrieve webhook details
  • PUT /webhooks/{id} - Update webhook configuration
  • DELETE /webhooks/{id} - Remove webhook
• Data Access: Reads/writes to Webhook Metadata DB

2. Event Trigger Service

• Responsibility: Receive events and initiate webhook processing
• Flow:
  1. Receive events from event queue
  2. Query Webhook Metadata DB for matching webhooks
  3. Create execution tasks and enqueue to execution queue
• Caching: Uses cache layer for frequently accessed webhook configurations

3. Execution Queue

• Technology: Message queue (e.g., Kafka, RabbitMQ, SQS)
• Purpose: Decouple event reception from webhook delivery
• Features:
  • Persistent storage for durability
  • Support for message prioritization
  • Dead letter queue for failed deliveries

4. Worker Pool

• Responsibility: Process webhook deliveries
• Characteristics:
  • Horizontally scalable
  • Pull messages from execution queue
  • Make HTTP requests to webhook endpoints
  • Record execution results to delivery log DB
• Error Handling:
  • Implement retry logic based on webhook configuration
  • Update delivery status in logs
  • Route permanently failed deliveries to monitoring system

5. Retry Service

• Responsibility: Handle failed webhook deliveries
• Retry Strategies:
  • Exponential backoff
  • Fixed interval
  • Custom retry schedules
• Configuration: Per-webhook retry policy settings

6. Monitoring Manager

• Responsibility: Provide observability into webhook operations
• Features:
  • Dashboard for webhook status
  • Execution metrics and analytics
  • Alert generation for failures
  • Historical trend analysis

7. Load Balancer

• Purpose: Distribute incoming requests across service instances
• Targets:
  • Webhook Manager API
  • Event Trigger Service
  • Monitoring endpoints

Data Stores

Webhook Metadata Database

Schema:

Webhook {
  web_hook_id: UUID (PK)
  url: String
  auth: JSON (credentials, tokens)
  event_type: String[]
  user_id: UUID
  expire_at: Timestamp
  status: Enum (active, inactive, expired)
  retry_type: Enum (exponential, fixed, custom)
  created_at: Timestamp
  updated_at: Timestamp
}

Characteristics:

• Relational DB for ACID properties
• Indexed on user_id, event_type for fast queries

Webhook Delivery Log Database

Schema:

execution_log {
  event_id: UUID (PK)
  event_type: String
  webhook: JSON (snapshot of webhook config)
  status: Enum (pending, success, failure, retrying)
  response_code: Integer
  response_body: Text
  attempt_count: Integer
  executed_at: Timestamp
  next_retry_at: Timestamp
}

Characteristics:

• High write throughput optimization
• Time-series optimized storage
• Partitioned by date for efficient querying

Cache Layer

• Purpose: Reduce database load for frequently accessed webhooks
• Cached Data:
  • Active webhook configurations
  • Event-to-webhook mappings
• Cache Invalidation: On webhook updates/deletions

Data Flow

Webhook Registration Flow

User → Load Balancer → Webhook Manager → Webhook Metadata DB
                                      ↓
                                    Cache (update)

Event Processing Flow

Event Source → Events Queue → Event Trigger Service
                                    ↓
                          Query Cache/Metadata DB
                                    ↓
                            Execution Queue → Worker Pool → Webhook Endpoint
                                                    ↓
                                          Delivery Log DB
                                                    ↓
                                    (if failure) → Retry Service

Monitoring Flow

User → Load Balancer → Monitoring Manager → Delivery Log DB
                                                  ↓
                                         (analytics & metrics)

Key Design Decisions

1. Queue-Based Architecture

• Rationale: Decouples event generation from delivery, enabling better scalability and fault tolerance
• Trade-off: Adds latency but improves reliability

2. Worker Pool Pattern

• Rationale: Allows independent scaling of webhook delivery capacity
• Implementation: Workers compete for messages from execution queue

3. Execution Log Persistence

• Rationale: Enables audit trails, debugging, and monitoring
• Optimization: Consider time-based archival for old logs

4. Cache Integration

• Rationale: Reduces database load for hot webhook configurations
• Strategy: Cache-aside pattern with TTL-based expiration

5. Retry Service Separation

• Rationale: Specialized handling of failed deliveries without blocking main worker pool
• Pattern: Scheduled retry jobs with exponential backoff

Scaling Considerations

Horizontal Scaling Components

• Webhook Manager (stateless API)
• Event Trigger Service
• Worker Pool (most critical for throughput)
• Monitoring Manager

Bottleneck Mitigation

• Database: Read replicas for webhook metadata, sharding for delivery logs
• Queue: Partitioned topics/queues for parallel processing
• Workers: Auto-scaling based on queue depth

Security Measures

1. Authentication:
   • Support for multiple auth methods (API keys, OAuth, JWT)
   • Encrypted storage of credentials
2. Request Validation:
   • HMAC signatures for webhook payloads
   • Timestamp validation to prevent replay attacks
3. Rate Limiting:
   • Per-webhook delivery rate limits
   • Circuit breaker pattern for problematic endpoints
4. Data Protection:
   • TLS for all communications
   • PII handling compliance

Monitoring & Alerting

Key Metrics

• Delivery success rate
• Average delivery latency
• Queue depth
• Worker utilization
• Retry rate
• Endpoint availability

Alerts

• High failure rate for specific webhooks
• Queue backup/overflow
• Worker pool saturation
• Database connection issues

Future Enhancements

1. Advanced Filtering: Allow complex event filtering based on payload content
2. Webhook Templates: Pre-configured webhook patterns for common use cases
3. Delivery Guarantee Options: Support for at-most-once and exactly-once semantics
4. Payload Transformation: Allow users to customize webhook payload format
5. Multi-region Deployment: Geographic distribution for lower latency
6. Webhook Testing: Sandbox environment for webhook validation

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Document Version: 1.0
Last Updated: November 1, 2025
Author: Copilot