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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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djangoproject

@djangoproject · Post #240 · 01/25/2017, 10:03 AM

http://www.aparat.com/v/4nbc9 This talk gives a quick overview of Python's capabilities as a #data_processing and #machine_learning tool through practical examples: gathering data from the web or a local file, validating/modifying it and finally analyzing it to build models for #classification and #prediction#tasks.