Batchwerk

Batchwerk is a software framework designed to orchestrate and execute large-scale batch jobs across computing resources. It emphasizes declarative workflow descriptions, fault tolerance, and observability to enable repeatable, auditable batch runs.

Its architecture centers on the separation of concerns among a scheduler, an executor, and pluggable backends. Workflows are defined as directed acyclic graphs in which nodes represent tasks with dependencies, inputs, and outputs. Tasks may run in containers, on virtual machines, or as local processes. Batchwerk provides configurable retry policies, timeouts, and idempotence guarantees to handle transient failures. State is persisted in a backend store, and events stream to monitoring systems for visibility and alerting.

Key features include parallel and distributed execution, backfilling, dynamic task generation, parameterized templates, and resource-aware scheduling. The system offers logging, metrics, lineage tracking, and rich UI dashboards. It includes adapters for data stores, message queues, and compute clusters, with support for cloud and on-premises deployments. Administrators and developers interact via a command-line interface and a REST API, enabling automation and integration with continuous integration/continuous deployment pipelines.

Typical use cases are ETL pipelines, batch analytics, machine learning model training workflows, and scientific computations that process large datasets. Users register tasks, assemble them into workflows, and trigger runs manually, on a schedule, or in response to events. Batchwerk emphasizes reproducibility and auditability through versioned workflows and run histories.

Development and adoption are driven by a community of contributors and users. The ecosystem features plugins and connectors to popular data storage systems, message buses, and cloud services. Licensing and governance depend on the particular distribution of the software.

See also: Apache Airflow, Prefect, Luigi, Dask.