XOps Crossword

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Across
  1. 1. a set of practices that combines software development (Dev) and information-technology operations (Ops) that aims to shorten the systems development life cycle and provide continuous delivery with high software quality.
  2. 2. use of an artifact repository that always contains declarative descriptions of the infrastructure currently desired in the production environment and an automated process to make the production environment match the described state in the repository.
  3. 4. machine learning operations practices meant to standardize and streamline the lifecycle of machine learning in production; orchestrating the movement of machine learning models, data and outcomes between the systems.
  4. 5. a collection of data-analytics technical practices, workflows, cultural norms and architectural patterns that enable: rapid innovation and experimentation; extremely high quality and very low error rates; collaboration across complex arrays of people, technology, and environments; and clear measurement, monitoring and transparency of results. In a nutshell, DataOps applies Agile development, DevOps and lean manufacturing to data-analytics (Data) development and operations (Ops).
  5. 9. Schedule, manage, monitor and maintain models under automation.
  6. 10. The application developer is also the person responsible for operating the app in production; the operational side of application management, including release automation, remediation, error recovery, monitoring, maintenance.
  7. 11. Attain zero downtime based on “continuous operations”; run cloud-based systems in such a way that there’s never the need to take part or all of an application out of service. Software must be updated and placed into production without any interruption in service.
  8. 12. The use of chat clients, chatbots and real-time communication tools to facilitate how software development and operation tasks are communicated and executed.
Down
  1. 1. views security as a shared responsibility integrated from end to end. Emphasizes the need to build a security foundation into DevOps initiatives.
  2. 3. the layer consisting of the management of the physical and virtual environment, which may very well be within a cloud environment. On top of this layer would be Service Operations (‘SvcOps’) and Application Operations (‘AppOps’).
  3. 4. automate the deployment, monitoring, governance and continuous improvement of data analytics models running 24/7 within the enterprise.
  4. 6. DevSecOps for data analytics
  5. 7. Algorithmic IT Operations synonymously titled as “Artificial Intelligence for IT Operations.” Replaces manual IT operations tools with an automated IT operations platform that collects IT data, identifies events and patterns, and reports or remediates issues — all without human intervention.
  6. 8. No IT infrastructure; software and software-defined hardware provisioned dynamically