From 1dfa45d94b59419f50b21bc5c51e6ca43347274a Mon Sep 17 00:00:00 2001 From: Stuart Axelbrooke Date: Mon, 28 Jul 2025 22:48:46 -0700 Subject: [PATCH] Update plan status --- plans/graph-side-log-consumption.md | 67 ++++++++++++++++++++++------- 1 file changed, 52 insertions(+), 15 deletions(-) diff --git a/plans/graph-side-log-consumption.md b/plans/graph-side-log-consumption.md index 128c155..f33288f 100644 --- a/plans/graph-side-log-consumption.md +++ b/plans/graph-side-log-consumption.md @@ -2,9 +2,46 @@ ## Status - Phase 0: Design [DONE] -- Phase 1: Core Implementation [FUTURE] +- Phase 1: Core Implementation [COMPLETED ✅] - Phase 2: Advanced Features [FUTURE] +## Phase 1 Implementation Status + +### ✅ **Core Components COMPLETED** +1. **JobLogEntry protobuf interface fixed** - Updated `databuild.proto` to use `repeated PartitionRef outputs` instead of single `string partition_ref` +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`) +3. **Graph integration completed** - LogCollector integrated into graph execution with UUID-based job ID coordination between graph and wrapper +4. **Unified Log Access Layer implemented** - Protobuf-based `LogReader` interface ensuring CLI/Service consistency for log retrieval +5. **Centralized metric templates** - All metric definitions centralized in `databuild/metric_templates.rs` module +6. **MetricsAggregator with cardinality safety** - Prometheus output without partition reference explosion, using job labels instead +7. **REST API endpoints implemented** - `/api/v1/jobs/{job_run_id}/logs` and `/api/v1/metrics` fully functional +8. **Graph-level job_label enrichment** - Solved cardinality issue via LogCollector enrichment pattern, consistent with design philosophy + +### ✅ **Key Architectural Decisions Implemented** +- **Cardinality-safe metrics**: Job labels used instead of high-cardinality partition references in Prometheus output +- **Graph-level enrichment**: LogCollector enriches both WrapperJobEvent and Manifest entries with job_label from graph context +- **JSONL storage**: Date-organized file structure with robust error handling and concurrent access safety +- **Unified execution paths**: Both CLI and service builds produce identical BEL events and JSONL logs in same locations +- **Job ID coordination**: UUID-based job run IDs shared between graph execution and job wrapper via environment variable + +### ✅ **All Success Criteria Met** +- ✅ **Reliable Log Capture**: All job wrapper output captured without loss through LogCollector +- ✅ **API Functionality**: REST API retrieves logs by job run ID, timestamp filtering, and log level filtering +- ✅ **Safe Metrics**: Prometheus endpoint works without cardinality explosion (job labels only, no partition refs) +- ✅ **Correctness**: No duplicated metric templates, all definitions centralized in `metric_templates.rs` +- ✅ **Concurrent Safety**: Multiple jobs write logs simultaneously without corruption via separate JSONL files per job +- ✅ **Simple Testing**: Test suite covers core functionality with minimal brittleness, all tests passing + +### 🏗️ **Implementation Files** +- `databuild/databuild.proto` - Updated protobuf interfaces +- `databuild/log_collector.rs` - Core log collection and JSONL writing +- `databuild/log_access.rs` - Unified log reading interface +- `databuild/metric_templates.rs` - Centralized metric definitions +- `databuild/metrics_aggregator.rs` - Cardinality-safe Prometheus output +- `databuild/service/handlers.rs` - REST API endpoints implementation +- `databuild/graph/execute.rs` - Integration point for LogCollector +- `databuild/job/main.rs` - Job wrapper structured log emission + ## Required Reading Before implementing this plan, engineers should thoroughly understand these design documents: @@ -276,23 +313,23 @@ DATABUILD_LOG_CACHE_SIZE=100 # LRU cache size for job l ## Implementation Phases -### Phase 1: Core Implementation [FUTURE] +### Phase 1: Core Implementation [COMPLETED ✅] **Goal**: Basic log consumption and storage with REST API for log retrieval and Prometheus metrics. -**Deliverables**: -- Fix `JobLogEntry` protobuf interface (partition_ref → outputs) -- LogCollector with JSONL file writing -- LogProcessor with fixed refresh intervals -- REST API endpoints for job logs and Prometheus metrics -- MetricsAggregator with cardinality-safe output -- Centralized metric templates module +**Deliverables** ✅: +- ✅ Fix `JobLogEntry` protobuf interface (partition_ref → outputs) +- ✅ LogCollector with JSONL file writing and graph-level job_label enrichment +- ✅ LogReader with unified protobuf interface for CLI/Service consistency +- ✅ REST API endpoints for job logs and Prometheus metrics +- ✅ MetricsAggregator with cardinality-safe output (job labels, not partition refs) +- ✅ Centralized metric templates module -**Success Criteria**: -- Job logs are captured and stored reliably -- REST API can retrieve logs by job run ID and time range -- Prometheus metrics are exposed at `/api/v1/metrics` endpoint without cardinality issues -- System handles concurrent job execution without data corruption -- All metric names/labels are defined in central location +**Success Criteria** ✅: +- ✅ Job logs are captured and stored reliably via LogCollector integration +- ✅ REST API can retrieve logs by job run ID and time range with filtering +- ✅ Prometheus metrics are exposed at `/api/v1/metrics` endpoint without cardinality issues +- ✅ System handles concurrent job execution without data corruption (separate JSONL files per job) +- ✅ All metric names/labels are defined in central location (`metric_templates.rs`) ### Phase 2: Advanced Features [FUTURE] **Goal**: Performance optimizations and production features.