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The Kubernetes API can be extended using Custom Resources, which represent objects that are not part of the standard Kubernetes installation. These custom resources are declared using Custom Resource Definitions (CRDs), which is a kind of resource that can be dynamically registered and unregistered without shutting down or restarting a cluster ...
Its initial release supported SDKs and APIs for Java, .NET, Python, and Go, and targeted the Kubernetes cloud deployment system. [3] [4] The source code is written in the Go programming language. It is licensed under Apache License 2.0 and hosted on GitHub. [5] Dapr is a CNCF project and graduated in November 2024. [6]
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 ...
Attributes can be data, user, session or tools based to deliver the greatest level of flexibility in dynamically granting/denying access to a specific data element. On big data, and distributed file systems such as Hadoop, ABAC applied at the data layer control access to folder, sub-folder, file, sub-file and other granular.
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.
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
FastAPI is a high-performance web framework for building HTTP-based service APIs in Python 3.8+. [3] It uses Pydantic and type hints to validate , serialize and deserialize data. FastAPI also automatically generates OpenAPI documentation for APIs built with it. [ 4 ]
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...