# Job Wrapper v2 Plan

## Status
- Phase 0: Minimal Bootstrap [DONE]
- Phase 1: Core Protocol [MOSTLY DONE - heartbeating and metrics implemented]
- Phase 2: Platform Support [FUTURE]
- Phase 3: Production Hardening [FUTURE]  
- Phase 4: Advanced Features [FUTURE]

## Required Reading

Before implementing this plan, engineers should thoroughly understand these design documents:

- **[DESIGN.md](../DESIGN.md)** - Overall DataBuild architecture and job execution model
- **[design/core-build.md](../design/core-build.md)** - Core build semantics and job lifecycle state machines
- **[design/observability.md](../design/observability.md)** - Observability strategy and telemetry requirements
- **[design/build-event-log.md](../design/build-event-log.md)** - Event sourcing model and BEL integration
- **[databuild.proto](../databuild/databuild.proto)** - System interfaces and data structures

## Overview
The job wrapper is a critical component that mediates between DataBuild graphs and job executables, providing observability, error handling, and state management. This plan describes the next generation job wrapper implementation in Rust.

## Architecture

### Core Design Principles
1. **Single Communication Channel**: Jobs communicate with graphs exclusively through structured logs [DONE]
2. **Platform Agnostic**: Works identically across local, Docker, K8s, and cloud platforms [PARTIAL - local only]
3. **Zero Network Requirements**: Jobs don't need to connect to any services [DONE]
4. **Fail-Safe**: Graceful handling of job crashes and fast completions [PARTIAL - basic handling only]

### Communication Model
```
Graph → Job: Launch with JobConfig (via CLI args/env)
Job → Graph: Structured logs (stdout)
Graph: Tails logs and interprets into metrics, events, and manifests
```

## Structured Log Protocol

### Message Format (Protobuf) [DONE]
```proto
message JobLogEntry {
  string timestamp = 1;
  string job_id = 2;
  string partition_ref = 3;
  uint64 sequence_number = 4;  // Monotonic sequence starting from 1 [DONE]
  
  oneof content {
    LogMessage log = 5;           // [DONE]
    MetricPoint metric = 6;       // [FUTURE]
    JobEvent event = 7;           // [DONE - WrapperJobEvent]
    PartitionManifest manifest = 8; // [DONE]
  }
}

message LogMessage {               // [DONE]
  enum LogLevel {
    DEBUG = 0;
    INFO = 1;
    WARN = 2;
    ERROR = 3;
  }
  LogLevel level = 1;
  string message = 2;
  map<string, string> fields = 3;
}

message MetricPoint {              // [FUTURE]
  string name = 1;
  double value = 2;
  map<string, string> labels = 3;
  string unit = 4;
}

message JobEvent {                 // [DONE - as WrapperJobEvent]
  string event_type = 1;  // "task_launched", "heartbeat", "task_completed", etc
  google.protobuf.Any details = 2;
  map<string, string> metadata = 3;
}
```

### Log Stream Lifecycle
1. Wrapper emits `config_validate_success` event (sequence #1) [DONE]
2. Wrapper validates configuration [DONE]
3. Wrapper emits `task_launch_success` event (sequence #2) [DONE]
4. Job executes, wrapper captures stdout/stderr (sequence #3+) [DONE]
5. Wrapper emits periodic `heartbeat` events (every 30s) [DONE]
6. Wrapper detects job completion [DONE]
7. Wrapper emits `task_success`/`task_failed` event [DONE]
8. Wrapper emits `PartitionManifest` message (final required message with highest sequence number) [DONE]
9. Wrapper exits [DONE]

The PartitionManifest serves as the implicit end-of-logs marker - the graph knows processing is complete when it sees this message. Sequence numbers enable the graph to detect missing or out-of-order messages and ensure reliable telemetry collection. [DONE - sequence numbers implemented]

## Wrapper Implementation [PARTIAL]

### Interfaces [DONE]
```rust
trait JobWrapper {
    // Config mode - accepts PartitionRef objects
    fn config(outputs: Vec<PartitionRef>) -> Result<JobConfig>; // [DONE]
    
    // Exec mode - accepts serialized JobConfig
    fn exec(config: JobConfig) -> Result<()>; // [DONE]
}
```

### Exit Code Standards [PARTIAL]

Following POSIX conventions and avoiding collisions with standard exit codes:

Reference: 
- https://manpages.ubuntu.com/manpages/noble/man3/sysexits.h.3head.html
- https://tldp.org/LDP/abs/html/exitcodes.html

```rust
// Standard POSIX codes we respect: [PARTIAL - basic forwarding only]
// 0   - Success
// 1   - General error
// 2   - Misuse of shell builtin
// 64  - Command line usage error (EX_USAGE)
// 65  - Data format error (EX_DATAERR)
// 66  - Cannot open input (EX_NOINPUT)
// 69  - Service unavailable (EX_UNAVAILABLE)
// 70  - Internal software error (EX_SOFTWARE)
// 71  - System error (EX_OSERR)
// 73  - Can't create output file (EX_CANTCREAT)
// 74  - Input/output error (EX_IOERR)
// 75  - Temp failure; retry (EX_TEMPFAIL)
// 77  - Permission denied (EX_NOPERM)
// 78  - Configuration error (EX_CONFIG)

// DataBuild-specific codes (100+ to avoid collisions): [FUTURE]
// 100-109 - User-defined permanent failures
// 110-119 - User-defined transient failures  
// 120-129 - User-defined resource failures
// 130+    - Other user-defined codes

enum ExitCodeCategory {  // [FUTURE]
    Success,              // 0
    StandardError,        // 1-63 (shell/system)
    PosixError,          // 64-78 (sysexits.h)
    TransientFailure,    // 75 (EX_TEMPFAIL) or 110-119
    UserDefined,         // 100+
}
```

## Platform-Specific Log Handling

### Local Execution [DONE]
- Graph spawns wrapper process [DONE]
- Graph reads from stdout pipe directly [DONE]
- PartitionManifest indicates completion [DONE]

### Docker [FUTURE]
- Graph runs `docker run` with wrapper as entrypoint
- Graph uses `docker logs -f` to tail output
- Logs persist after container exit

### Kubernetes [FUTURE]
- Job pods use wrapper as container entrypoint
- Graph tails logs via K8s API
- Configure `terminationGracePeriodSeconds` for log retention

### Cloud Run / Lambda [FUTURE]
- Wrapper logs to platform logging service
- Graph queries logs via platform API
- Natural buffering and persistence

## Observability Features

### Metrics Collection [FUTURE]

For metrics, we'll use a simplified StatsD-like format in our structured logs, which the graph can aggregate and expose via Prometheus format:

```json
{
  "timestamp": "2025-01-27T10:30:45Z",
  "content": {
    "metric": {
      "name": "rows_processed",
      "value": 1500000,
      "labels": {
        "partition": "date=2025-01-27",
        "stage": "transform"
      },
      "unit": "count"
    }
  }
}
```

The graph component will: [FUTURE]
- Aggregate metrics from job logs
- Expose them in Prometheus format for scraping (when running as a service)
- Store summary metrics in the BEL for historical analysis

For CLI-invoked builds, metrics are still captured in the BEL but not exposed for scraping (which is acceptable since these are typically one-off runs).

### Heartbeating [DONE]

Fixed 30-second heartbeat interval (configurable via `DATABUILD_HEARTBEAT_INTERVAL_MS`):

```json
{
  "timestamp": "2025-01-27T10:30:45Z", 
  "content": {
    "JobEvent": {
      "event_type": "heartbeat",
      "metadata": {
        "memory_usage_mb": "1024.256",
        "cpu_usage_percent": "85.200"
      }
    }
  }
}
```

**Implementation Details:**
- Uses sysinfo crate for cross-platform process monitoring
- Heartbeat thread communicates via channels with main thread
- Includes memory usage (MB) and CPU usage (%) with 3 decimal precision
- Configurable interval for testing (default 30s, test environments use 100ms)
- Proper dependency injection via LogSink trait for testability

### Log Bandwidth Limits [FUTURE]

To prevent log flooding:
- Maximum log rate: 1000 messages/second
- Maximum message size: 1MB
- If limits exceeded: Wrapper emits rate limit warning and drops messages
- Final metrics show dropped message count

## Testing Strategy

### Unit Tests [MOSTLY DONE]
- Log parsing and serialization [DONE - protobuf serde]
- State machine transitions [DONE - JobLogEntry sequence validation]
- Heartbeat functionality [DONE - with dependency injection]
- CPU/memory metrics collection [DONE - with configurable intervals]
- Exit code categorization [FUTURE]
- Rate limiting behavior [FUTURE]

### Integration Tests [PARTIAL]
- Full job execution lifecycle [DONE - via e2e tests]
- Resource metrics validation [DONE - CPU-intensive workload testing]
- Platform-specific log tailing [PARTIAL - local only]
- Fast job completion handling [DONE]
- Large log volume handling [FUTURE]

### Platform Tests [PARTIAL]
- Local process execution [DONE]
- Docker container runs [FUTURE]
- Kubernetes job pods [FUTURE]
- Cloud Run invocations [FUTURE]

### Failure Scenario Tests [PARTIAL]
- Job crashes (SIGSEGV, SIGKILL) [DONE - basic exit code forwarding]
- Wrapper crashes [FUTURE]
- Log tailing interruptions [FUTURE]
- Platform-specific failures [FUTURE]

## Implementation Phases

### Phase 0: Minimal Bootstrap [DONE]
Implement the absolute minimum to unblock development and testing:
- Basic wrapper that only handles happy path [DONE]
- Support for local execution only [DONE]
- Minimal log parsing in graph [DONE - wrapper emits structured logs]
- Integration with existing example jobs [DONE - e2e tests passing]

This phase delivers a working end-to-end system that can be continuously evolved. [DONE]

**Completed Implementation Details:**
- Created databuild/job/src/main.rs with config/exec modes [DONE]
- Uses protobuf types from databuild.proto [DONE]
- Emits JobLogEntry with sequence numbers [DONE]
- Follows core-build.md state diagram exactly [DONE]
- Forwards job stdout/stderr as LogMessage entries [DONE]
- Emits PartitionManifest on successful completion [DONE]
- Properly handles job failures with exit codes [DONE]
- Modified Bazel rules to use job_wrapper [DONE]
- All e2e tests passing [DONE]

### Phase 1: Core Protocol [MOSTLY DONE]
- Define protobuf schemas [DONE - JobLogEntry, LogMessage, WrapperJobEvent]
- Implement structured logger [DONE - JSON serialization to stdout]
- Add error handling and exit codes [PARTIAL - basic forwarding only]
- Implement heartbeating [DONE - with CPU/memory metrics]
- Resource metrics collection [DONE - CPU time, peak memory, runtime]
- Dependency injection for testability [DONE - LogSink trait pattern]
- Graph-side log parser improvements [FUTURE - wrapper emits, graph needs to consume]
- MetricPoint message support [FUTURE]
- Advanced error categorization [FUTURE]

### Phase 2: Platform Support [FUTURE]
- Docker integration [FUTURE]
- Kubernetes support [FUTURE]
- Cloud platform adapters [FUTURE]
- Platform-specific testing [FUTURE]

### Phase 3: Production Hardening [FUTURE]
- Rate limiting [FUTURE]
- Error recovery [FUTURE]
- Performance optimization [FUTURE]
- Monitoring integration [FUTURE]

### Phase 4: Advanced Features [FUTURE]
- In-process config for library jobs [FUTURE]
- Custom metrics backends [FUTURE]
- Advanced failure analysis [FUTURE]

## Success Criteria

1. **Zero Network Dependencies**: Jobs run without any network access [DONE]
2. **Platform Parity**: Identical behavior across all execution platforms [PARTIAL - local only]
3. **Minimal Overhead**: < 100ms wrapper overhead for config, < 1s for exec [DONE - fast execution]
4. **Complete Observability**: All job state changes captured in logs [DONE - core events captured]
5. **Graceful Failures**: No log data loss even in crash scenarios [PARTIAL - basic failure handling]

## Next Steps

1. Implement minimal bootstrap wrapper [DONE]
2. Test with existing example jobs [DONE]
3. Iterate on log format based on real usage [IN PROGRESS - Phase 1 continuation]
4. Gradually add features per implementation phases [IN PROGRESS]

**Phase 1 Achievements:**
- ✅ Heartbeating support with CPU/memory metrics [DONE]
- ✅ Dependency injection for testability (LogSink trait) [DONE]  
- ✅ Resource metrics collection (CPU time, peak memory, runtime) [DONE]
- ✅ Comprehensive test coverage for heartbeats and metrics [DONE]
- ✅ Configurable intervals for different environments [DONE]

**Remaining for Phase 1 Completion:**
- Implement MetricPoint logging [FUTURE]
- Add graph-side structured log consumption [FUTURE]  
- Enhanced error categorization and exit code mapping [FUTURE]

**Recent Implementation Details:**
- Uses sysinfo 0.30 for cross-platform process monitoring
- Thread-safe heartbeat communication via mpsc channels
- Floating-point metrics with 3 decimal precision (f64)
- Environment variable configuration: `DATABUILD_HEARTBEAT_INTERVAL_MS`, `DATABUILD_METRICS_INTERVAL_MS`
- Robust test infrastructure with synthetic CPU-intensive workloads
- Proper CPU time calculation: (average_cpu_percent / 100.0) × wall_clock_time