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The name Kubernetes originates from the Greek κυβερνήτης (kubernḗtēs), meaning 'governor', 'helmsman' or 'pilot'. Kubernetes is often abbreviated as K8s, counting the eight letters between the K and the s (a numeronym). [6]
Dask Bag is used to parallelize computation of semi-structured or unstructured data, such as JSON records, text data, log files or user-defined Python objects using operations such as filter, fold, map and groupby. Dask Bags can be created from an existing Python iterable or can load data directly from text files and binary files in the Avro ...
Airflow is written in Python, and workflows are created via Python scripts. Airflow is designed under the principle of "configuration as code". While other "configuration as code" workflow platforms exist using markup languages like XML, using Python allows developers to import libraries and classes to help them create their workflows.
Azure Linux is being developed by the Linux Systems Group at Microsoft for its edge network services and as part of its cloud infrastructure. [5] The company uses it as the base Linux for containers in the Azure Stack HCI implementation of Azure Kubernetes Service. [4]
Python is a widely used general-purpose, high-level, interpreted, programming language. [16] Python supports multiple programming paradigms, including object-oriented, imperative, functional and procedural paradigms. It features a dynamic type system, automatic memory management, a standard library, and strict use of whitespace. [17]
The open-source Pulumi CLI and SDKs allows users to manage cloud infrastructure resources [3] in Cloud Providers such as AWS, Azure, Google Cloud, and Kubernetes. [4] using programming languages such as Go, JavaScript, TypeScript, [5] Python, Java, C# and YAML. Pulumi's Automation API supports provisioning infrastructure via programmatic ...
Dapr (Distributed Application Runtime) is a free and open source runtime system designed to support cloud native and serverless computing. [2] Its initial release supported SDKs and APIs for Java, .NET, Python, and Go, and targeted the Kubernetes cloud deployment system.
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google.The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development (Kubeflow Notebooks [4]), model training (Kubeflow Pipelines, [5] Kubeflow Training Operator [6]), model serving (KServe [a] [7]), and ...