WORKFLOWS & AUTOMATION
Idea. Flow. Action.
Flowable is a locally hosted, container-based automation platform. Build workflows visually, connect ready-made nodes from databases to Kubernetes, and run them on a queue-based engine that scales horizontally and recovers automatically.
Runs locally with Docker Compose · Visual workflows and AI nodes · Under active development
FEATURES & USE CASES
Build workflows as nodes on a canvas, with a command palette, guided setup for complex nodes and a readiness check before execution.
An operations team builds an incident workflow with a webhook, HTTP request, conditional branch and notification without writing code.
Start manually, through a webhook or on a cron schedule, with queue logic that tracks activation and limits requests.
A finance team schedules a nightly workflow that retrieves database data, transforms it and writes a report to storage.
Databases, message queues, search engines and infrastructure combine with LLM nodes, an AI agent and MCP tools. The node catalogue shows available building blocks.
A data engineer chains Kafka, Elasticsearch and a PostgreSQL batch insert into a small ETL pipeline using ready-made adapters.
Queue-based execution with atomic claims and heartbeats. Stateless workers scale horizontally, and interrupted jobs resume automatically instead of being lost.
An operations lead scales up to four workers before a batch window without worrying about duplicate or lost jobs.
See exactly what each node received and produced, with streaming support for large datasets and trace IDs throughout the execution.
A builder investigates a failed nightly run, inspects JSON data node by node and restarts from the exact node that failed.
Seven built-in roles, from viewer to owner, with permission checks on every API call and encrypted credential storage.
A platform administrator gives developers the builder role and on-call staff the operator role, keeping their responsibilities separate.
Optional extensions give a dedicated worker access to Docker, Kubernetes or Terraform without exposing them to the rest of the fleet. A separate emulator profile tests integrations locally without cloud dependencies.
A DevOps engineer enables the Kubernetes extension on one dedicated worker so a specific workflow can safely read cluster logs.
FROM THE INTERFACE
