# daena Collect, buffer, and forward logs and events from Linux to central observability backends. ## Overview Daena is a modular, extensible Linux service that: - Collects logs, events, and telemetry from pluggable sources - Normalizes and processes records through a configurable pipeline - Persists data locally in LMDB for durability, replay, and buffering - Forwards records reliably to one or more remote sinks - Exposes a REST API for management and inspection - Provides a CLI for operational tasks - Degrades gracefully under failures with retry, backoff, and dead-letter queues ## Architecture ``` Sources → [Processors] → Pipeline → Persistence (LMDB) → Sink Dispatcher → Remote ↻ retry queue ``` Key design decisions: - **Plugin architecture**: Sources, processors, and sinks are loaded via Python entry points. Add new ones by installing a package or registering in `pyproject.toml`. - **Pluggable persistence**: The `Backend` protocol abstracts storage. MVP uses LMDB. Future: NATS JetStream. - **Reliability-first**: Records survive restarts, sink failures trigger exponential backoff, and permanently failed records land in a dead-letter queue. ## Quick start ```bash # Prerequisites: pyenv with Python 3.13, uv installed # Clone and set up git clone && cd daena pyenv local 3.13.5 uv sync --extra dev # Run with dummy source/sink (no external dependencies) uv run python -c " import asyncio from daena.config import DaenaConfig, SourceConfig, SinkConfig from daena.core.runtime import DaenaRuntime async def main(): config = DaenaConfig() config.sources = [SourceConfig(name='test', type='dummy', options={'interval': 1.0, 'message': 'hello'})] config.sinks = [SinkConfig(name='log', type='dummy')] config.persistence.lmdb.path = '/tmp/daena_data' runtime = DaenaRuntime(config) await runtime.start() await asyncio.sleep(5) print(f'Records: {runtime.backend.count()}') await runtime.stop() asyncio.run(main()) " # Run tests uv run pytest tests/ -v # Use the CLI (point at a running daena API) uv run daena status uv run daena health uv run daena queue ``` ## Project structure ``` daena/ ├── pyproject.toml # Project metadata, dependencies, entry points ├── config/daena.yaml # Example configuration ├── deploy/daena.service # systemd unit file ├── src/daena/ │ ├── app.py # `daena-serve` entry point (uvicorn) │ ├── config.py # YAML → pydantic config │ ├── logutil.py # structlog setup │ ├── exceptions.py # Domain exceptions │ ├── api/ # FastAPI REST API (v1 versioned) │ ├── cli/ # Typer CLI │ ├── core/ │ │ ├── runtime.py # Service lifecycle │ │ └── pipeline.py # Collection → persist → dispatch │ ├── persistence/ │ │ ├── backend.py # Abstract Backend protocol │ │ ├── models.py # RecordState, StoredRecord │ │ └── lmdb.py # LMDB implementation │ ├── pipeline/ │ │ ├── base.py # Source/Processor/Sink ABCs │ │ ├── record.py # In-memory Record dataclass │ │ ├── sources/ # Built-in sources (dummy) │ │ ├── sinks/ # Built-in sinks (dummy, http) │ │ └── processors/ # Built-in processors (passthrough) │ └── plugins/ │ ├── loader.py # Entry-point discovery │ └── registry.py # Plugin registry └── tests/ ``` ## Configuration Daena loads configuration from `/etc/daena/daena.yaml`, `./daena.yaml`, or `./config/daena.yaml`. See `config/daena.yaml` for a full example. ```yaml logging: level: info format: json api: http: host: 127.0.0.1 port: 8642 persistence: backend: lmdb lmdb: path: /var/lib/daena/data map_size: 104857600 sources: - name: system_logs type: journald # future options: {} processors: - name: add_hostname type: enricher # future options: {} sinks: - name: central type: http options: url: https://logs.example.com/ingest ``` ## REST API The API runs on `http://127.0.0.1:8642/api/v1`: | Endpoint | Description | |----------|-------------| | `GET /system/status` | Service status | | `GET /system/health` | Health check | | `GET /system/config` | Loaded configuration | | `GET /plugins` | Registered plugins | | `GET /queue` | Queue state counts | | `GET /queue/pending` | Pending records | | `GET /queue/dead` | Dead-letter records | | `GET /sinks` | Configured sinks | ## Deployment ### systemd ```bash # Create daena user sudo useradd -r -s /sbin/nologin -d /var/lib/daena daena # Install package uv pip install . # Set up directories sudo mkdir -p /etc/daena /var/lib/daena /var/log/daena /run/daena sudo cp config/daena.yaml /etc/daena/ sudo cp deploy/daena.service /etc/systemd/system/ sudo systemctl daemon-reload sudo systemctl enable --now daena ``` ## Extending Add a new source by creating a class that inherits `daena.pipeline.base.Source` and registering it as an entry point: ```python # my_sources.py from daena.pipeline.base import Source from daena.pipeline.record import Record class MySource(Source): async def start(self): pass async def stop(self): pass ``` ```toml # pyproject.toml [project.entry-points."daena.sources"] my_source = "my_sources:MySource" ``` Same pattern applies for `Processor` and `Sink` base classes. ## Branch workflow - `main` — stable integration branch - `dev` — active development branch Feature work happens on `dev` or topic branches. Merges to `main` represent stable release checkpoints.