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Source channel @githubtrending · Post #15057 · Aug 14

#go#external_secrets#hacktoberfest#kubernetes#kubernetes_secrets#secrets_manager External Secrets Operator (ESO) is a Kubernetes tool that connects external secret managers like AWS Secrets Manager, HashiCorp Vault, and others to Kubernetes, automatically injecting secret values into Kubernetes Secrets. However, official releases are paused because the current maintainer team is too small to support ongoing development and community help. You can still use the latest code from the main branch, but no new official versions or support will be provided until more maintainers join. If your team relies on ESO, contributing helps keep the project healthy and ensures future updates. This pause highlights the importance of community support for open-source tools you depend on. Using ESO benefits you by simplifying secure secret management in Kubernetes across multiple cloud providers. https://github.com/external-secrets/external-secrets

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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