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Generative Ai Security And Devops Meet Github

Generative Ai Security And Devops Meet Github

WRITTEN BY GITHUB WITH Generative AI, Security, and DevOps: Meet GitHub Innovate at scale with the world’s leading AI-powered developer platform What’s inside

  • 3 DevOps success in the era of AI and
  • security

  • 5 A better developer experience with
  • innersource

  • 6 GitHub Enterprise: The value of a
  • centralized development platform

  • 7 Build, secure, and ship software faster
  • 7 Increase developer productivity and
  • happiness

  • 10 Why developers love GitHub
  • 13 The tools developers need to build what
  • they want

  • 13 GitHub Advanced Security
  • 15 The explosion of AI adoption in
  • business

  • 16 Responsible use of generative AI
  • 17 GitHub Copilot: The world’s most
  • widely adopted developer tool

  • 21 Ready to get started?
  • 22 Best practices to ensure a successful
  • migration

  • 23 Developers love GitHub
  • 24 Next steps
  • Written by GitHub with PAGE — 3 Organizations require excellence across several domains to remain competitive and relevant. Improving developer satisfaction and talent retention, accelerating software delivery, achieving secure collaboration, enabling cross-team visibility and communication, and embracing AI- readiness, have all become essential for organizations to be seen as an employer of choice among developers. In today’s dynamic business landscape, standing up a strong DevOps practice can help engineering teams collaborate, stay in flow, remove obstacles, stay secure and compliant, and become AI-ready. With emerging technologies on the horizon poised to empower developers to innovate in lockstep with the speed of the market, staying on top of—and ideally ahead of— software development trends is one of the more difficult challenges to tackle. Digital security—dealing with not only applications but the platforms they run on—has been an increasingly visible and complex issue for every organization, regardless of size. Regulatory requirements for securing user data, complying with national and international standards for personal data, and safeguarding personal health and payment card information are just some areas organizations struggle with. Finding ways to ensure all regulatory requirements are met, cybersecurity standards and controls are implemented, and applications are secured can at times be a battle of wills. This is because the need to innovate fast can be met with slowdowns on the security front. DevOps success in the era of AI and security Written by GitHub with DevOps success in the era of AI and security PAGE — 4cONT. By integrating these concerns around development, operations, security, and lines of business into a comprehensive lifecycle, the DevOps of today relies on the participation of various interested parties from the outset. S ecurity is expected to be enabled and embedded in the software development lifecycle at all levels. Using AI-based technologies across all functional areas enables organizations to identify and fix issues fast, while delivering a wealth of innovative tools and content to users with varying technical backgrounds. Working with legacy systems and software remains a challenge. As expertise in aging programming languages declines, maintaining these older systems becomes a burden—let alone modernizing them. Fragmented toolsets and convoluted means of collaboration add more friction and compound these issues. With more developers than ever building software in complex environments, clearing obstacles and optimizing the developer experience has never been more important. A September 2023 article in Forbes magazine regarding the financial software system used by Wall S treet saw GitHub C EO Thomas Dohmke speak about the state of aging legacy codebases: “Currently, many Wall Street institutions are still operating on vulnerable code written as early as the Eisenhower era over half a century ago.” Thomas Dohmke // CEO of GitHub

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