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Home » platform engineering » Page 2

platform engineering

  • Measuring What Matters: The True Impact of Platform Teams

    April 14, 2025

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    Platform Engineering: DevOps Savior or the Revenge of Centralized IT?

    April 9, 2025

  • platform, IDP, generative ai, AI, responsible ai, automation, AI, human, observability, engineering

    Scaling Responsible AI With Platform Engineering and Advanced Observability

    March 3, 2025

  • build, buy, platform, CI/CD, DevOps 2.0, platform engineering, CoE, AI, IT Ops production environment

    Build vs. Buy: The Platform Engineer’s Conundrum 

    February 28, 2025

  • product manager mindset, product, DevEx, developer, experience, Backstage, developer, GitHub productivity Roadie DevX developer experience DPE open source team lead Agile hybrid developer GitLab DevRel developer GitHub BDD CircleCI Rust developer

    Platform Excellence With a Product Management Mindset

    February 27, 2025

  • observability

    Making Observability Work: How Platform Engineers Can Improve Monitoring

    February 7, 2025

  • kubernetes

    How to Harness Kubernetes for Platform Engineering

    February 6, 2025

  • IDPs, developer, platform, engineering, devops, observability, dynatrace's, scalability, model, DaaS, AI assistants, engineers, DevOps, platform engineering, teams, event-driven. architecture, EDA, platform engineering, software,

    Platform Engineering: Scaling DevOps Through AI-Driven Self-Service

    February 6, 2025

  • zero trust, cybersecurity

    Security at Scale: Embedding Zero Trust in Platform Design

    February 5, 2025

  • platform engineering, myths, developer, developers, UX platforms, engineering, innovative, innovation, platforms, scale, platform engineering developer control plane experience platform

    Platform Engineering is Marketing, Engineering a Platform is Real

    February 5, 2025

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Security in AI

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How would you best describe your organization's current stage of securing the use of generative AI in your applications?(Required)
Have you implemented, or are you planning to implement, zero trust security for the AI your organization uses or develops?(Required)
What are the three biggest challenges your organization faces when integrating generative AI into applications or workflows? (Select up to three)(Required)
How does your organization secure proprietary information used in AI training, tuning, or retrieval-augmented generation (RAG)? (Select all that apply)(Required)
Which of the following kinds of tools are you currently using to secure your organization’s use of generative AI? (select all that apply)(Required)
How valuable do you think it would it be to have a solution that classifies and quantifies risks associated with generative AI tools?(Required)
What are, or do you think would be, the most important reasons for implementing generative AI security measures? (Select up to three)(Required)

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