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Greptile Overview

Greptile Summary

Replaces in-memory service graph processing with SQL-based daemon architecture that runs in compactor every hour, completely decoupling service graph from trace ingestion.

Major Changes:

• Addedprocessor.rs (202 lines) - SQL daemon that queries trace streams using DataFusion with CTE for client/server edge extraction and percentile calculations
• Addedaggregator.rs (155 lines) - Writes SQL-aggregated edges to_o2_service_graph internal stream via bulk ingestion
• Modifiedapi.rs - Queries_o2_service_graph stream for last 60 minutes, returnsavailableStreams for filtering
• Modifiedcompactor.rs - Integrated service_graph_processor job with configurable interval
• Modifiedtraces/mod.rs - Removed ALL inline processing during trace ingestion (lines 398-399)
• Frontend updated to support stream filtering via query params

Architecture Benefits:

• Zero impact on trace ingestion performance
• SQL aggregation leverages DataFusion for efficient processing
• Configurable processing interval (default: 1 hour) and query window (default: 60 min)
• Graceful error handling per stream (failures don't block other streams)

Configuration:

• O2_SERVICE_GRAPH_ENABLED=true
• O2_SERVICE_GRAPH_PROCESSING_INTERVAL_SECS=3600
• O2_SERVICE_GRAPH_QUERY_TIME_RANGE_MINUTES=60

Confidence Score: 4/5

• Safe to merge with attention to SQL query assumptions and companion PR requirement
• Clean architectural refactor with proper error handling and feature gating. Score reflects: (1) SQL query assumespeer_service field exists in trace schema, (2) requires companion o2-enterprise PR for business logic, (3) no validation onstream_filter query parameter for SQL injection prevention
• Pay close attention tosrc/service/traces/service_graph/processor.rs - SQL query assumes peer_service field exists

Important Files Changed

File Analysis

Sequence Diagram

sequenceDiagram    participant Client as Frontend Client    participant API as Service Graph API    participant Compactor as Compactor Job    participant Processor as SQL Processor    participant DataFusion as DataFusion Query Engine    participant TraceStream as Trace Streams    participant ServiceGraphStream as _o2_service_graph Stream        Note over Compactor,Processor: Daemon runs every processing_interval_secs (default: 3600s)        Compactor->>Processor: process_service_graph()    Processor->>Processor: get_trace_streams() - List all orgs & trace streams        loop For each trace stream        Processor->>DataFusion: Execute SQL with CTE        Note right of DataFusion: WITH edges AS (<br/>  SELECT client, server, duration, span_status<br/>  WHERE span_kind IN ('2','3')<br/>  AND peer_service IS NOT NULL<br/>)<br/>SELECT COUNT(*), percentiles<br/>GROUP BY client, server        DataFusion->>TraceStream: Query last 60min of traces        TraceStream-->>DataFusion: Span records        DataFusion-->>Processor: Aggregated edges (p50/p95/p99)        Processor->>ServiceGraphStream: write_sql_aggregated_edges()        Note right of ServiceGraphStream: Bulk ingest via logs API<br/>to _o2_service_graph    end        Note over Client,API: User queries topology (independent of daemon)        Client->>API: GET /topology/current?stream_name=X    API->>ServiceGraphStream: SQL query last 60min    ServiceGraphStream-->>API: Edge records    API->>API: build_topology() - Convert to nodes/edges    API-->>Client: {nodes, edges, availableStreams}