NEW EXAMPLE SCENARIO: Accelerate digital image-based modeling on Azure

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This post has been republished via RSS; it originally appeared at: MSDN Blogs.

Written by Paulo Marques da Costa. Edited by Nanette Ray. Published by Adam Boeglin from Microsoft patterns & practices.

This example scenario provides architecture and design guidance for any organization that wants to perform image-based modeling on Azure infrastructure-as-a-service (IaaS). The scenario is designed for running photogrammetry software on Azure Virtual Machines using high-performance storage that accelerates processing time. The environment can be scaled up and down as needed and supports terabytes of storage without sacrificing performance.

Accelerate digital image-based modeling on Azure

The concepts in this article apply to any high-performance computing (HPC) workload based on a scheduler and worker nodes managed as infrastructure. For this workload, Avere vFXT was selected for its superior performance during benchmark tests. However, the scenario decouples the storage from the processing so that other storage solutions can be used.

Components included in this example scenario:


Topics covered include:

  • Relevant use cases
  • Architecture
    • Components
    • Alternatives
  • Considerations
    • Security
  • Pricing
  • Deployment
  • Related Resources


For step-by-step instructions for deploying this architecture, including all the prerequisites for using either Avere FxT or BeeGFS, download the ebook: Deploy Agisoft PhotoScan on Azure With Avere vFXT for Azure or BeeGFS.


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