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Source channel @githubtrending · Post #14992 · Jul 23

#go#aws#azure#cncf#cost#cost_optimization#finops#gcp#k8s#kubernetes#monitoring#opencost#prometheus OpenCost is a free, open-source tool that helps you see and understand the costs of running Kubernetes clusters and cloud services in real time. It breaks down costs by cluster, node, namespace, pod, and more, across multiple cloud providers like AWS, Azure, and GCP, and even supports on-premises setups. This lets you track where your money is going, spot expensive resources, and manage your cloud spending better. It integrates with Prometheus for metrics and offers a user-friendly web interface and APIs for easy cost monitoring and exporting. Using OpenCost helps you control and optimize your cloud and Kubernetes expenses efficiently[1][2][3][4]. https://github.com/opencost/opencost

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AI & Law

@ai_and_law · Post #130 · 10/04/2023, 07:04 AM

Google Empowers Web Publishers with Data Control Hello, everyone! Google has introduced a new tool called Google-Extended, allowing website publishers to opt out of using their data to train Google's AI models, all while maintaining accessibility through Google Search. This tool provides a solution for publishers who wish to have their sites indexed by Google's web crawlers but prefer not to contribute their data to the development of AI models like Bard and Vertex AI generative APIs. Bard, Google's AI chatbot, has been undergoing training using publicly available web data. With Google-Extended, publishers can now manage their site's participation in this process. Google-Extended is integrated into the robots.txt file, which is used to inform web crawlers about site accessibility. It grants web publishers the ability to control AI model training access and content availability. #AIandLaw#GoogleAI#WebPublishers#AIModels