Problem Statement

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Distributed Tracing System - Problem Statement

Overview

Design a distributed tracing system like Jaeger or Zipkin that tracks requests across multiple microservices, providing visibility into system performance, debugging capabilities, and dependency analysis. The system must handle high-volume trace data with low overhead.

Functional Requirements

Core Tracing Features

  • Trace Collection: Capture traces from all services
  • Span Management: Track individual operations
  • Context Propagation: Pass trace context across services
  • Trace Assembly: Reconstruct complete request paths
  • Sampling: Intelligent trace sampling strategies
  • Trace Storage: Persist traces for analysis

Trace Data Model

  • Trace ID: Unique identifier for request
  • Span ID: Unique identifier for operation
  • Parent Span: Hierarchical relationships
  • Service Name: Originating service
  • Operation Name: Specific operation
  • Timestamps: Start and end times
  • Tags: Key-value metadata
  • Logs: Structured log events
  • Baggage: Cross-service data

Query and Analysis

  • Trace Search: Find traces by criteria
  • Service Dependency: Visualize service graph
  • Performance Analysis: Identify bottlenecks
  • Error Tracking: Find failed requests
  • Latency Analysis: P50, P95, P99 metrics
  • Comparison: Compare trace patterns

Visualization

  • Trace Timeline: Waterfall view of spans
  • Service Map: Dependency graph
  • Flame Graphs: Performance visualization
  • Gantt Charts: Parallel execution view
  • Heatmaps: Latency distribution

Non-Functional Requirements

Performance Requirements

  • Collection Overhead: <1% application overhead
  • Ingestion Rate: 100K+ spans per second
  • Query Latency: <1 second for trace retrieval
  • Storage Efficiency: 10:1 compression ratio
  • Sampling Overhead: <0.1ms per request

Scalability Requirements

  • Services: 1,000+ microservices
  • Traces: 1 billion traces per day
  • Spans: 10 billion spans per day
  • Retention: 7-30 days of trace data
  • Concurrent Queries: 1,000+ simultaneous queries

Reliability Requirements

  • Availability: 99.9% uptime
  • Data Loss: <0.1% trace loss acceptable
  • Fault Tolerance: Survive collector failures
  • Graceful Degradation: Continue with sampling

Success Metrics

  • Trace Completeness: >99% complete traces
  • Query Performance: P95 <2 seconds
  • Storage Cost: <$0.01 per million spans
  • Application Overhead: <1% CPU/memory
  • Adoption Rate: >90% services instrumented

This problem statement provides the foundation for designing a production-grade distributed tracing system.