Managed execution
Runs pipelines and tasks: jobs execute as workers consume from a queue, with dependencies between jobs.
Flagship product
Dagychu
The execution layer that kept emerging from production systems.
Companies repeatedly solve the same operational problems. Raideria extracted that recurring layer into Dagychu. Your application creates the task; Dagychu owns execution, logs, recovery, and operator visibility.
Self-hostedCommunity + EnterpriseOperational + AI workflows
Origin
Not sold. Extracted.
While building Data Platforms and Execution Systems, the same machinery appeared again and again: queues, workers, retries, schedulers, logs, admin screens. Each team reinvented a weaker version under deadline pressure.
Dagychu is that layer built once, as a product, with the operational discipline Raideria requires of production systems. It is a consequence of the engineering work — not a separate marketing story.
The problem
Your backend should not become an orchestration system.
When applications need imports, exports, reports, AI processing, reconciliation, or bulk updates, teams often build outbox tables, polling workers, status columns, retry scripts, and custom admin screens. That machinery becomes its own system to maintain, and it is rarely observable.
Dagychu is that execution layer, built once and built to be operated. Your application posts a task; Dagychu owns running it and making the result visible.
Why it is a Raideria product
Raideria builds systems. Dagychu powers execution.
Dagychu is one concrete expression of how Raideria thinks about engineering. It is a product of Raideria; it is not the whole company.
What is happening / what changed
Execution state, per-job logs, and history are first-class, not an afterthought.
Who owns it / what next
A scheduler and control plane make ownership and operational state explicit.
How do we recover
Failure and recovery are part of the model: retries, structured outputs, and reconciliation.
What it does
Capabilities.
The list below reflects what Dagychu does today.
Scheduling & triggers
A scheduler dispatches runs and supports safe external triggers and webhooks.
Logs & outputs
Per-job input/output and full logs are captured and readable from the control plane.
Observability
Metrics and an audit trail of scheduler events make execution inspectable.
Recovery
Retries and reconciliation are part of the execution model, not bolted on.
Self-hosted control plane
A React-based control plane runs on your own infrastructure; you own the runtime.
Architecture
A control plane around your workloads.
Simplified for clarity; the running system has more moving parts.
Your application
POST task
Core API
FastAPI
Queue + Workers
run jobs
PostgreSQL
state + history
A separate scheduler dispatches runs, and a React control plane (via a UI backend) provides dashboards, task views, and per-job logs. Job logs are shared with the control plane so full output is readable from the UI. See also the broader reference architecture for how this plane sits in a Data Platform.
Editions
Community or Enterprise?
Both editions run on your infrastructure and provide the core Dagychu execution experience. Community is free to self-host and is not an open-source release of application source — public GitHub hosts distribution materials; Apache License 2.0 applies only where those materials are so marked.
Community
Free · self-hosted
For teams that need to run and monitor their own jobs and pipelines.
Use Community when you want to bring scheduled and background workloads under control without building execution infrastructure into your applications.
- Shared core: pipelines, tasks, job runs, scheduler, workers, logs
- Operational monitoring dashboard (charts)
- Self-hosted control plane on your infrastructure
- Free to use — no artificial task or run quotas
Enterprise
Commercial
For organizations that use Dagychu as shared production infrastructure.
Choose Enterprise when multiple people or teams operate workloads and you need stronger organizational controls.
- Roles & RBAC — control who can view, run, modify, and administer workloads
- Monitoring Overview — a centralized operational view across executions, failures, workers, and pipelines
- Enterprise support — help with deployment and operating Dagychu in production
- Also includes Execution map, API Security, External Execution API (/ext/*), and workspace dashboards
Start with Community. Move to Enterprise when Dagychu becomes infrastructure your organization depends on.
Contact
Talk to Raideria about Dagychu.
Questions about Community, Enterprise, or how Dagychu fits your execution architecture — email us.