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I would like to know whether it is advisable to deploy in production a rule-based model created with IBM Watson Knowledge Studio (WKS), as it is an experimental feature.

IBM documentation clearly recommends not to use its experimental features in production: https://console.bluemix.net/docs/services/watson-knowledge-studio/troubleshooting.html#experimental .

However, an old post IBM Watson Knowledge Studio 2.0 - deploying a rule-based model is experimental. What does that mean? seems to guarantee that this feature is actually stable and won't be removed in the future. At the same time a more recent post at https://developer.ibm.com/answers/questions/440983/is-my-wks-experimental-data-lost/ shows what happened to someone who deployed its experimental WKS project and then lost it (even though that post is not about rule-based models).

Thank you in advance!

Rosa
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2 Answers2

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Experimental features means a number of things in relation to a production solution.

  • How it works may change at a later time.
  • No guarantee it will be available at a later time.
  • It is generally unsupported if issues occur.

One of your links refers to "Experimental service". These should never be used in a production environment, because when they go live the experimental service will stop working. Live versions may not be fully compatible as well.

Simon O'Doherty
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  • Thank you, now I understand that the last link was talking about an experimental service and not an experimental feature. However, do you also recommend me to never use in production experimental features? Because for this particular case it seems from my second link that there is some guarantee. – Rosa Sep 17 '18 at 20:33
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Thank you for your question. I re-read my original answer and I admit that it was a bit ambiguous, for which I apologize. I updated my original answer. To be more clear:

  • IBM experimental services and experimental features are NOT suitable for production use. Period.
  • We encourage using experimental services/features because the purpose of experimental releases is to learn from client's real use. But this encouragement to experiment with non-GA services/features still does not mean that they are suitable for production use.
  • The Knowledge Studio rules-only models, deployable to runtime services like Natural Language Understanding and Discovery, are Experimental. The Rules within Knowledge Studio (rules editor and rules pre-annotator) is a GA feature. This is why I was saying that Rules are here to stay, while the rules-only models are not protected agains breaking changes. For example, we may decide to pull off the market the rules-only models when we introduce hybrid models (rules + machine-learning in the same runtime model) or if we don't see good adoption of the rules-only models. At the same time the Rules-based pre-annotation has proven to be a valuable and well accepted feature that we plan to enhance.

My apologies for the initial confusion. I hope that this answer is more clear than my previous one.

Kind regards,

Stefan

stzanev
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