Patterns
πŸ“‘

Scatter-Gather

Distributes requests to multiple services and collects responses

Complexity: mediumParallelization

🎯 30-Second Overview

Pattern: Broadcast requests to multiple services, then aggregate responses

Why: Maximizes information coverage, improves resilience, leverages diverse capabilities

Key Insight: Request β†’ [Service1, Service2, ServiceN] β†’ Gather β†’ Aggregate β†’ Result

⚑ Quick Implementation

1Identify:Find independent services/resources
2Scatter:Send concurrent requests to all services
3Timeout:Set realistic response deadlines
4Gather:Collect responses as they arrive
5Aggregate:Merge using voting/scoring strategies
Example: query β†’ [service_A, service_B, service_C] β†’ gather_responses β†’ merge_results

πŸ“‹ Do's & Don'ts

βœ…Design consistent interfaces across all services
βœ…Implement circuit breakers for unreliable services
βœ…Use partial result aggregation for resilience
βœ…Cache responses to reduce redundant calls
βœ…Monitor service performance and adapt strategies
❌Create dependencies between services
❌Rely on all services succeeding
❌Use inconsistent request formats
❌Ignore slow or failing service patterns
❌Skip result validation from individual services

🚦 When to Use

Use When

  • β€’ Multiple independent information sources
  • β€’ Need comprehensive coverage
  • β€’ Services have different specializations
  • β€’ Fault tolerance is critical

Avoid When

  • β€’ Services have dependencies
  • β€’ Single service is sufficient
  • β€’ Real-time latency requirements
  • β€’ Resource-constrained environments

πŸ“Š Key Metrics

Service Response Rate
% services responding within timeout
Aggregation Completeness
% expected information gathered
Overall Latency
End-to-end response time
Service Reliability
Individual service uptime
Result Quality
Accuracy vs single-service baseline
Resource Efficiency
Cost vs sequential calls

πŸ’‘ Top Use Cases

Multi-Source Research: Query knowledge bases β†’ gather insights β†’ synthesize report
Price Comparison: Check providers β†’ collect quotes β†’ recommend best option
Service Health Check: Poll endpoints β†’ gather status β†’ aggregate dashboard
Content Enrichment: Query APIs β†’ collect metadata β†’ enhance content
Consensus Building: Poll validators β†’ gather opinions β†’ determine consensus

Pattern Relationships

Discover how Scatter-Gather relates to other patterns

Prerequisites, next steps, and learning progression

Prerequisites

(1)
⏳
Async-Await
lowparallelization

Fundamental concurrent programming for parallel service calls

πŸ’‘ Essential for managing concurrent service requests effectively

Next Steps

(3)
πŸ—ΊοΈ
Map-Reduce
mediumparallelization

Structured parallel processing with explicit chunking and aggregation

πŸ’‘ Natural evolution when you need more structured parallel data processing

🍴
Fork-Join
mediumparallelization

Recursive parallel decomposition with dynamic load balancing

πŸ’‘ Advanced parallelization for complex recursive processing tasks

πŸ•ΈοΈ
Stateful Graph Workflows
very-highplanning execution

Complex service orchestration with state management

πŸ’‘ Enterprise-grade service coordination with sophisticated orchestration

Alternatives

(2)
πŸ—ΊοΈ
Map-Reduce
mediumparallelization

More structured approach with explicit chunking

πŸ’‘ Better when you need systematic data partitioning and processing

⛓️
Sequential Chaining
lowprompt chaining

Linear service calls when parallel execution isn't needed

πŸ’‘ Simpler approach when services must be called in specific order

Industry Applications

Financial Services

Multi-provider data aggregation for comprehensive financial analysis

πŸ“ŠMulti-Criteria Decision Making
βš–οΈLLM-as-Judge

Content & Knowledge

Multi-source information gathering and synthesis

πŸ“šAdvanced RAG
πŸ—‚οΈHierarchical Planning

Software Development

Multi-service integration for comprehensive system monitoring

πŸ’»Code Execution
πŸ”§SWE-Bench Suite

References & Further Reading

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