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  2. Spinnaker (software) - Wikipedia

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

    Website. www.spinnaker.io. Spinnaker is a free and open-source continuous delivery software platform originally developed by Netflix and extended by Google. [2] It is designed to work with Kubernetes, Google Cloud Platform, AWS, Microsoft Azure and Oracle Cloud. Spinnaker was developed by Netflix as a successor to the internally developed ...

  3. Continuous delivery - Wikipedia

    en.wikipedia.org/wiki/Continuous_delivery

    There are various tools that help accomplish all or part of this process. [7] These tools are part of the deployment pipeline which includes continuous delivery. The types of tools that execute various parts of the process include: continuous integration, application release automation, build automation, application lifecycle management. [8]

  4. CI/CD - Wikipedia

    en.wikipedia.org/wiki/CI/CD

    Software development. In software engineering, CI/CD or CICD is the combined practices of continuous integration (CI) and continuous delivery (CD) or, less often, continuous deployment. [1] They are sometimes referred to collectively as continuous development or continuous software development. [2]

  5. Continuous deployment - Wikipedia

    en.wikipedia.org/wiki/Continuous_deployment

    Continuous deployment (CD) is a software engineering approach in which software functionalities are delivered frequently and through automated deployments. [1][2][3] Continuous deployment contrasts with continuous delivery (also abbreviated CD), a similar approach in which software functionalities are also frequently delivered and deemed to be ...

  6. Continuous configuration automation - Wikipedia

    en.wikipedia.org/wiki/Continuous_configuration...

    Evaluations of CCA tools may consider the following: [8] [9] Skills, training, and cost required to implement and maintain tool; Content and support of the Platform and Infrastructure – tool specified for Windows or Linux etc. Delivery method and likening flexibility – important for scalability; Method of interacting with managing system

  7. MLOps - Wikipedia

    en.wikipedia.org/wiki/MLOps

    MLOps is the set of practices at the intersection of Machine Learning, DevOps and Data Engineering. MLOps or ML Ops is a paradigm that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous delivery practice (CI/CD) of DevOps in the software field.

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