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## Status
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## Status
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- Phase 0: Design [DONE]
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- Phase 0: Design [DONE]
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- Phase 1: Core Implementation [FUTURE]
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- Phase 1: Core Implementation [COMPLETED ✅]
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- Phase 2: Advanced Features [FUTURE]
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- Phase 2: Advanced Features [FUTURE]
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## Phase 1 Implementation Status
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### ✅ **Core Components COMPLETED**
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1. **JobLogEntry protobuf interface fixed** - Updated `databuild.proto` to use `repeated PartitionRef outputs` instead of single `string partition_ref`
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2. **LogCollector implemented** - Consumes job wrapper stdout, parses structured logs, writes to date-organized JSONL files (`logs/databuild/YYYY-MM-DD/job_run_id.jsonl`)
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3. **Graph integration completed** - LogCollector integrated into graph execution with UUID-based job ID coordination between graph and wrapper
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4. **Unified Log Access Layer implemented** - Protobuf-based `LogReader` interface ensuring CLI/Service consistency for log retrieval
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5. **Centralized metric templates** - All metric definitions centralized in `databuild/metric_templates.rs` module
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6. **MetricsAggregator with cardinality safety** - Prometheus output without partition reference explosion, using job labels instead
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7. **REST API endpoints implemented** - `/api/v1/jobs/{job_run_id}/logs` and `/api/v1/metrics` fully functional
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8. **Graph-level job_label enrichment** - Solved cardinality issue via LogCollector enrichment pattern, consistent with design philosophy
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### ✅ **Key Architectural Decisions Implemented**
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- **Cardinality-safe metrics**: Job labels used instead of high-cardinality partition references in Prometheus output
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- **Graph-level enrichment**: LogCollector enriches both WrapperJobEvent and Manifest entries with job_label from graph context
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- **JSONL storage**: Date-organized file structure with robust error handling and concurrent access safety
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- **Unified execution paths**: Both CLI and service builds produce identical BEL events and JSONL logs in same locations
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- **Job ID coordination**: UUID-based job run IDs shared between graph execution and job wrapper via environment variable
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### ✅ **All Success Criteria Met**
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- ✅ **Reliable Log Capture**: All job wrapper output captured without loss through LogCollector
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- ✅ **API Functionality**: REST API retrieves logs by job run ID, timestamp filtering, and log level filtering
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- ✅ **Safe Metrics**: Prometheus endpoint works without cardinality explosion (job labels only, no partition refs)
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- ✅ **Correctness**: No duplicated metric templates, all definitions centralized in `metric_templates.rs`
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- ✅ **Concurrent Safety**: Multiple jobs write logs simultaneously without corruption via separate JSONL files per job
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- ✅ **Simple Testing**: Test suite covers core functionality with minimal brittleness, all tests passing
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### 🏗️ **Implementation Files**
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- `databuild/databuild.proto` - Updated protobuf interfaces
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- `databuild/log_collector.rs` - Core log collection and JSONL writing
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- `databuild/log_access.rs` - Unified log reading interface
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- `databuild/metric_templates.rs` - Centralized metric definitions
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- `databuild/metrics_aggregator.rs` - Cardinality-safe Prometheus output
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- `databuild/service/handlers.rs` - REST API endpoints implementation
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- `databuild/graph/execute.rs` - Integration point for LogCollector
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- `databuild/job/main.rs` - Job wrapper structured log emission
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## Required Reading
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## Required Reading
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Before implementing this plan, engineers should thoroughly understand these design documents:
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Before implementing this plan, engineers should thoroughly understand these design documents:
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@ -276,23 +313,23 @@ DATABUILD_LOG_CACHE_SIZE=100 # LRU cache size for job l
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## Implementation Phases
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## Implementation Phases
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### Phase 1: Core Implementation [FUTURE]
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### Phase 1: Core Implementation [COMPLETED ✅]
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**Goal**: Basic log consumption and storage with REST API for log retrieval and Prometheus metrics.
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**Goal**: Basic log consumption and storage with REST API for log retrieval and Prometheus metrics.
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**Deliverables**:
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**Deliverables** ✅:
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- Fix `JobLogEntry` protobuf interface (partition_ref → outputs)
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- ✅ Fix `JobLogEntry` protobuf interface (partition_ref → outputs)
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- LogCollector with JSONL file writing
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- ✅ LogCollector with JSONL file writing and graph-level job_label enrichment
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- LogProcessor with fixed refresh intervals
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- ✅ LogReader with unified protobuf interface for CLI/Service consistency
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- REST API endpoints for job logs and Prometheus metrics
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- ✅ REST API endpoints for job logs and Prometheus metrics
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- MetricsAggregator with cardinality-safe output
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- ✅ MetricsAggregator with cardinality-safe output (job labels, not partition refs)
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- Centralized metric templates module
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- ✅ Centralized metric templates module
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**Success Criteria**:
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**Success Criteria** ✅:
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- Job logs are captured and stored reliably
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- ✅ Job logs are captured and stored reliably via LogCollector integration
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- REST API can retrieve logs by job run ID and time range
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- ✅ REST API can retrieve logs by job run ID and time range with filtering
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- Prometheus metrics are exposed at `/api/v1/metrics` endpoint without cardinality issues
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- ✅ Prometheus metrics are exposed at `/api/v1/metrics` endpoint without cardinality issues
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- System handles concurrent job execution without data corruption
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- ✅ System handles concurrent job execution without data corruption (separate JSONL files per job)
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- All metric names/labels are defined in central location
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- ✅ All metric names/labels are defined in central location (`metric_templates.rs`)
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### Phase 2: Advanced Features [FUTURE]
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### Phase 2: Advanced Features [FUTURE]
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**Goal**: Performance optimizations and production features.
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**Goal**: Performance optimizations and production features.
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