[{"data":1,"prerenderedAt":718},["ShallowReactive",2],{"/ja-jp/blog/gitlab-duo-self-hosted-enterprise-ai-built-for-data-privacy/":3,"navigation-ja-jp":41,"banner-ja-jp":456,"footer-ja-jp":469,"Susie Bitters-Aathira Nair":679,"next-steps-ja-jp":703},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"seo":8,"content":16,"config":30,"_id":34,"_type":35,"title":36,"_source":37,"_file":38,"_stem":39,"_extension":40},"/ja-jp/blog/gitlab-duo-self-hosted-enterprise-ai-built-for-data-privacy","blog",false,"",{"title":9,"description":10,"ogTitle":9,"ogDescription":10,"noIndex":6,"ogImage":11,"ogUrl":12,"ogSiteName":13,"ogType":14,"canonicalUrls":12,"schema":15},"GitLab Duo Self-Hosted：セキュリティ境界内で実現するエンタープライズ向けAI","GitLab Duo Self-Hostedを使用すれば、エンタープライズレベルのデータレジデンシーとプライバシーを維持しながら、生成AIの力を活用できます。セキュリティやガバナンスの要件が厳格でも、GitLab Duoをセルフマネージドのインフラ上に安全に導入できるようになりました。","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097840/Blog/Hero%20Images/Blog/Hero%20Images/Self-Hosted%201800x945_1dL1II2ITh2PteObA9DBLD_1750097839679.png","https://about.gitlab.com/blog/gitlab-duo-self-hosted-enterprise-ai-built-for-data-privacy","https://about.gitlab.com","article","\n                        {\n        \"@context\": \"https://schema.org\",\n        \"@type\": \"Article\",\n        \"headline\": \"GitLab Duo Self-Hosted：セキュリティ境界内で実現するエンタープライズ向けAI\",\n        \"author\": [{\"@type\":\"Person\",\"name\":\"Susie Bitters\"},{\"@type\":\"Person\",\"name\":\"Aathira Nair\"}],\n        \"datePublished\": \"2025-02-27\",\n      }",{"title":9,"description":10,"authors":17,"heroImage":11,"date":20,"body":21,"category":22,"tags":23,"updatedDate":29},[18,19],"Susie Bitters","Aathira Nair","2025-02-27","このたび、Gitab Duo Self-Hostedの一般提供を開始しました。この機能はGitLab Duoコード提案およびGitLab Duo Chatで利用可能です。これにより、組織はエンタープライズレベルの AI機能を活用しながら、データを自社のインフラ内で保持できるようになります。GitLab Duo Self-Hostedはオンプレミス、インターネット未接続（エアギャップ）環境、セキュアなクラウド設定に対応しており、 機密データや知的財産を厳重に管理しながら、チームが AI を活用して革新を促進できるよう支援します。\n\nセキュリティに関する懸念は、規制の厳しい業界でAIを導入する上で大きな障壁となっています。こちらの[グローバルDevSecOpsレポート](https://about.gitlab.com/ja-jp/developer-survey/2024/ai/)によると、回答者の半数以上が、ソフトウェア開発ライフサイクルにAIを組み込むことはリスクが伴うと答えています。[GitLab Duo](https://about.gitlab.com/ja-jp/gitlab-duo/)により、組織がソフトウェア開発ライフサイクル全体でAIを活用し、より安全で迅速なソフトウェアデリバリーを実現できるようになります。\n\n17.9のリリースでは、厳格なデータプライバシー要件を持つ組織の特定のニーズに対応するためにGitLab Duo Self-Hostedの機能を拡張し、生成AIの大規模言語モデル（LLM）を含む柔軟なモデルデプロイメントが可能になりました。公共部門や規制の厳しい業界（金融サービス、自動車、医療）の組織は、AI を活用した開発ツールを自社の閉じた環境にシームレスに統合できるようになり、セキュリティチームは必要な制御を維持しながら、AIによる競争優位性を得ることができます。\n\nある米国政府機関は次のように述べています。\n「DevSecOpsプラットフォームの基盤としてGitLabを選定した後、ソフトウェアファクトリー機能をさらに強化するためにGitLab Duo Self-Hostedを採用することにしました。\nGitLab Duoはエアギャップ環境で利用でき、データに対して詳細な制御が可能なため、セキュアなAI機能の実現に不可欠でした。\nGitLab Duoの統一されたアプローチにより、ワークフローの効率化、セキュリティ強化、AI 活用による生産性向上を実現するとともに、厳格なコンプライアンス要件を満たすことができるようになりました」\n\n![GitLab Duo Self-Hosted モデル](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097848/Blog/Content%20Images/Blog/Content%20Images/image4_aHR0cHM6_1750097848329.png)\n\n## セキュアなAI導入を設計\n\nGitLab Duo Self-Hostedは、Anthropic、Mistral、OpenAIなどの主要な生成AIモデルをサポート対象としており、GitLab Duoのユースケースやプロンプトライブラリに最適なパフォーマンスを発揮するモデルを選択できます。現在サポート対象となっているLLMは次のとおりです。\n\n* オンプレミス：vLLMサービングプラットフォームを使用したMistralモデル\n* AWS：AWS Bedrockを介したMistralおよびAnthropic Claude 3.5 Sonnet\n* Microsoft Azure：Azure AIを介したMistralおよびOpenAI GPTモデル\n\n今後サポート予定のモデルを評価中です。[サポートしているLLMについての詳細は、こちらをご覧ください。](https://docs.gitlab.com/administration/gitlab_duo_self_hosted/supported_models_and_hardware_requirements/)\n\nGitLab Duo Self-Hostedは、オープンソースのvLLMフレームワークを活用したオンプレミスインストールや、AWS BedrockやMicrosoft Azure AIなどのサービスを利用したプライベートクラウドデプロイメントを含む、多様なオプションをサポートしています。\nこの柔軟性により、組織は自社のセキュリティ、コンプライアンス、パフォーマンス要件に合わせた最適なAIソリューションを設計できます。\n\n## AI/MLの実装を簡単に\n\nAI抽象化レイヤーは、AI/MLテクノロジーの実装に必要なエンジニアリング作業を省き、選択した大規模言語モデル（LLM）への統合を標準化および簡素化します。\n企業は複数のツールを統合・維持する複雑さから解放され、AI導入プロセスを効率化するとともに、デベロッパーエクスペリエンスを向上させることができます。\n\n![GitLab Duo Self-Hosted AI機能](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097848/Blog/Content%20Images/Blog/Content%20Images/image1_aHR0cHM6_1750097848330.png)\n\n## データレジデンシー要件を満たす\n\nGitLabインスタンス、AIゲートウェイ、LLMを独自の環境や選択した国に分離することで、機密データや知的財産を指定された境界内に保持することができます。\nデータローカリティ（データが物理的に保存される場所）を細かく制御することにより、厳格なデータレジデンシー規制を遵守しつつ、エアギャップ環境などの安全な設定でAI機能を導入することが可能になります。\n外部APIへの依存をなくすことで、すべてのリクエストと応答のログに対して完全な可視性を確保でき透明性が向上します。公共部門の組織でも、最も厳格なコンプライアンス要件に準拠しながら AI機能を安全に導入できるようになります。\n\n**下の画像をクリックしてデモ（クリックスルー）をご覧ください。**\n\n[![GitLab Duo Self-Hosted tour screenshot](https://res.cloudinary.com/about-gitlab-com/image/upload/v1750097848/Blog/Content%20Images/Blog/Content%20Images/Screenshot_2025-02-20_at_7.00.34_AM_aHR0cHM6_1750097848332.png)](https://gitlab.navattic.com/gitlab-duo-self-hosted)\n\n## GitLab Duo 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