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  2. Kubernetes - Wikipedia

    en.wikipedia.org/wiki/Kubernetes

    The same API design principles have been used to define an API to harness a program in order to create, configure, and manage Kubernetes clusters. This is called the Cluster API. [ 87 ] A key concept embodied in the API is using Infrastructure as Software , or the notion that the Kubernetes cluster infrastructure is itself a resource / object ...

  3. Kubeflow - Wikipedia

    en.wikipedia.org/wiki/Kubeflow

    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 ...

  4. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    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.

  5. Comparison of cluster software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_cluster_software

    Yes, and native Python Binding: PBS Pro: C/Python: OS Authentication, Munge Any, e.g., NFS, Lustre, GPFS, AFS Limited availability Heterogeneous Yes Yes Fully configurable Yes tested ~50,000 Millions Yes MPI, OpenMP Yes Yes: OpenLava: C/C++ OS authentication None NFS Heterogeneous Linux Yes Yes Configurable Yes Yes, supports preemption based on ...

  6. OpenShift - Wikipedia

    en.wikipedia.org/wiki/OpenShift

    This level of control enables the cluster to support upgrades and patches of the control plane nodes with minimal effort. The compute nodes can be running Red Hat CoreOS, RHEL or even Windows. OpenShift introduced the concept of routes - points of traffic ingress into the Kubernetes cluster. The Kubernetes ingress concept was modeled after this ...

  7. Apache Airflow - Wikipedia

    en.wikipedia.org/wiki/Apache_Airflow

    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.

  8. Red Hat Cluster Suite - Wikipedia

    en.wikipedia.org/wiki/Red_Hat_cluster_suite

    The Red Hat Cluster Suite (RHCS) includes software to create a high availability and load balancing cluster. Both can be used on the same system although this use case is unlikely. Both products, the High Availability Add-On and Load Balancer Add-On, are based on open-source community projects. Red Hat Cluster developers contribute code ...

  9. Google Cloud Platform - Wikipedia

    en.wikipedia.org/wiki/Google_Cloud_Platform

    Google Kubernetes Engine (GKE) or GKE on-prem offered as part of Anthos platform [11] [12] – Containers as a Service based on Kubernetes. Cloud Functions – Functions as a Service to run event-driven code written in Node.js, Java, Python, or Go. Cloud Run – Compute execution environment based on Knative. [13]