Steep 5.1.0 has just been released

I’m very happy to announce that Steep 5.1.0 has just been released. This version introduces a new web-based user interface, which looks very modern, is responsive, and provides many features that make work with workflows and process chains easier. Steep 5.1.0 also adds new HTTP endpoints and stores information about created VMs in the database. The version has been thoroughly tested in practice over the last couple of months.

Steep is a scientific workflow management system that can execute data-driven workflows in the Cloud. It is very well suited to harness the possibilities of distributed computing in order to parallelise work and to speed up your data processing workflows, no matter how complex they are and regardless of how much data you need to process. Steep is an open-source software developed at Fraunhofer IGD. You can download the binaries and the source code of Steep from its GitHub repository.

New features

  • New web-based user interface
    • Modern look
    • Responsive (works on mobile devices)
    • Filters for workflows, process chains, etc. (e.g. show only failed process chains)
    • … many more features
  • Add possibility to configure a pool of remote agents for which to create VMs
  • Cloud VMs are now kept in the database
  • Add HTTP endpoint for VMs
    • Access information about created VMs
    • Get reason why a VM was destroyed
    • Fetch VMs by status
  • Improved HTTP endpoint for workflows
    • Add possibility to fetch workflows by status
    • Provide required capabilities of workflows
  • Add support for Cross-Origin Resource Sharing (CORS)
  • Allow multiple SSH commands to be executed in parallel while creating new VMs
  • Add possibility to disable controller
  • Log agent capabilities on startup
  • Add interface for initializer plugins

Maintenance

  • Speed up discovery of plugins and service metadata
  • Update Gradle to 6.3
  • Update Kotlin to 1.3.72

Bug fixes

  • Include conf directory in distribution
  • Allow the Steep start script to be run from anywhere
  • Include results of partially succeeded submissions in the HTTP response

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Posted by Michel Krämer
on 15 May 2020


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Two new cloud-based data processing papers published

My latest research papers about “Capability-based Scheduling of Scientific Workflows in the Cloud” and “Scalable processing of massive geodata in the cloud” are now available.

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GeoRocket: A scalable and cloud-based data store for big geospatial files

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