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Ability to move fully trained STT models between separate instances (i.e. DEV vs. PROD or separate accounts)

  • Customers for best practice reasons keep environments separate (DEV vs. PROD) for security, performance, testing & availability of the model. 
  • Training STT models can take hours to train.
  • Not utilizing fully trained models results in delays in providing updated STT models in PROD
  • Duplication of effort in DEV & PROD, increases operational impact & costs.
  • Avatar32.5fb70cce7410889e661286fd7f1897de Guest
  • Sep 11 2018
  • Future consideration
Who would benefit from this IDEA? Customer DEV teams need to quickly move fully trained STT models between instances (DEV to PROD)
  • Attach files
  • Admin
    Marco Noel commented
    14 Nov, 2019 08:28pm

    This is under investigation for 2020

  • Avatar40.8f183f721a2c86cd98fddbbe6dc46ec9
    Guest commented
    27 Sep, 2018 01:29pm


    The ability to propagate models through the various dev/ops stages is something Enterprise clients with rigid change control and management are looking for.  

  • Avatar40.8f183f721a2c86cd98fddbbe6dc46ec9
    Guest commented
    24 Sep, 2018 04:13am

    This feature is currently in needed, especially by customers consuming STT with acoustic models which can be time consuming to retrain. From a dev ops governance standpoint customers need a way to cascade or copy the binary files only to insure all copies perform identically to the original.

  • Avatar40.8f183f721a2c86cd98fddbbe6dc46ec9
    Guest commented
    11 Sep, 2018 09:40pm

    Having something that could be incorporated into a DevOps pipeline will move STT from a "curiosity" to something that we can claim we have a real SW engineering discipline around.  

    If this capability becomes available, then service availability in ANY environment could be guaranteed using a simple blue/green DevOps deployment technique.

  • Avatar40.8f183f721a2c86cd98fddbbe6dc46ec9
    Guest commented
    11 Sep, 2018 05:34pm

    Service may be unavailable during cut over which would impact Customer's using this service experience

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