Amazon SWF Case Studies
RightScale
RightScale uses Amazon SWF to drive their infrastructure automation offerings. According to Thorsten von Eicken, CTO of RightScale, “Using Amazon SWF we are able to reduce the time to market for our higher level infrastructure automation features. We are able to focus on our value-add without having to worry about the challenges that are associated with implementing a distributed workflow engine. In the end we are able to ship new features faster and don't have to concern ourselves with maintaining that engine."
RightScale uses Amazon SWF to drive their infrastructure automation offerings. According to Thorsten von Eicken, CTO of RightScale, “Using Amazon SWF we are able to reduce the time to market for our higher level infrastructure automation features. We are able to focus on our value-add without having to worry about the challenges that are associated with implementing a distributed workflow engine. In the end we are able to ship new features faster and don't have to concern ourselves with maintaining that engine."
Sage Bionetworks
To drive collaboration among researchers, Sage Bionetworks built an on-line environment, called Synapse. Synapse hosts clinical-genomic datasets and provides researchers with a platform for collaborative analyses. Michael Kellen, Director of Technology for Sage Bionetworks states, “Amazon SWF allowed us to quickly decompose analysis pipelines in an orderly way by separating state transition logic from the actual activities in each step of the pipeline. This allowed software engineers to work on the state transition logic and our scientists to implement the activities, all at the same time.” Learn more.
To drive collaboration among researchers, Sage Bionetworks built an on-line environment, called Synapse. Synapse hosts clinical-genomic datasets and provides researchers with a platform for collaborative analyses. Michael Kellen, Director of Technology for Sage Bionetworks states, “Amazon SWF allowed us to quickly decompose analysis pipelines in an orderly way by separating state transition logic from the actual activities in each step of the pipeline. This allowed software engineers to work on the state transition logic and our scientists to implement the activities, all at the same time.” Learn more.
NASA Jet Propulsion Laboratory (JPL)
JPL uses Amazon SWF as an integral part of several missions including the Mars Exploration Rover (MER) and Carbon in the Arctic Reservoir Vulnerability Experiment (CARVE). By making orchestration available in the cloud, Amazon SWF gives JPL the ability to leverage resources inside and outside its environment and seamlessly distribute application execution into the public cloud, enabling their applications to dynamically scale and run in a truly distributed manner. JPL engineers use Amazon SWF data processing of Mars images for tactical operations. They have gained unprecedented control and visibility into the distributed execution of their pipelines. To learn more, read the case study.
JPL uses Amazon SWF as an integral part of several missions including the Mars Exploration Rover (MER) and Carbon in the Arctic Reservoir Vulnerability Experiment (CARVE). By making orchestration available in the cloud, Amazon SWF gives JPL the ability to leverage resources inside and outside its environment and seamlessly distribute application execution into the public cloud, enabling their applications to dynamically scale and run in a truly distributed manner. JPL engineers use Amazon SWF data processing of Mars images for tactical operations. They have gained unprecedented control and visibility into the distributed execution of their pipelines. To learn more, read the case study.
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