runmanage

Runmanage is a term used to describe software systems and practices for controlling the lifecycle of computational runs—individual executions, experiments, or jobs—across diverse environments such as local workstations, clusters, and cloud platforms. It emphasizes reproducibility, reliability, and traceability by coordinating submission, execution, monitoring, and result collection.

Core capabilities include scheduling and queuing, resource allocation, execution orchestration, error handling, and automatic retries. Runmanage solutions typically capture metadata about each run, including parameters, environment, and provenance, to enable auditing and reuse.

Typical architecture comprises a run scheduler or orchestrator, one or more executors or workers, a resource manager, and a metadata store, often with user interfaces or APIs for submission and monitoring. Many implementations integrate with version control, data management, experiment tracking, and notification services.

Use cases include scientific computing, data science pipelines, ML experiments, continuous integration and testing, and large-scale simulations where numerous runs with varying configurations must be managed efficiently.

Variants and terminology: runmanage is used broadly; individual projects may implement different interfaces or adapters, and there is no universal standard. Common themes include lifecycle management, provenance, reproducibility, multi-environment support, and interoperability with existing infrastructure.

See also: job scheduling, workflow management, experiment tracking, provenance.