Phlo is a modular lakehouse platform for ingestion, quality, transformation, orchestration, and data access.
flowchart TD
project["Phlo project"]
subgraph core["Core runtime"]
cli["CLI and config"]
hooks["Hooks and plugin discovery"]
workflows["Ingestion, quality, transforms"]
end
subgraph data["Lakehouse data plane"]
storage["Object storage + table format"]
catalog["Catalog + metadata store"]
query["Query engine"]
orch["Orchestrator"]
end
subgraph optional["Optional operator-facing surfaces"]
hasura["Hasura"]
postgrest["PostgREST"]
openmetadata["OpenMetadata"]
observability["Observability backends"]
end
project --> core
core --> data
data --> optional
- Getting Started: install, run, first pipeline.
- Guides: workflows, patterns, and cross-package how-to material.
- Architecture: public system shape, topology, and platform boundaries.
- Packages: what each installable package contributes to the platform.
- Setup: operator runbooks for optional external surfaces that need extra configuration after install.
- Reference: canonical contracts, commands, configuration, and API surfaces.
- Python Reference: generated symbol-level API and docstring reference for the core runtime.
- Operations: production operation, troubleshooting, and maintenance.
- Platform Topology
- Public System Design
- Choosing Components
- Deployment Profiles
- Setup
- Production Readiness
Phlo can expose optional surfaces around the core data plane and runtime stack.
- Hasura and PostgREST for external API exposure
- OpenMetadata for catalog and metadata workflows
- Observability for logs, traces, and metrics routing
- Security for authentication, secrets, and hardening
Use Packages for component detail and Reference for commands, config, and contracts.
- New project: Installation Guide, then Quickstart Guide
- Building workflows: Developer Guide
- Understanding the platform model: Core Concepts
- Running the stack: Operations Guide
- Looking for a specific package: Packages
- Looking for commands and settings: Reference