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Carter",{"type":696,"value":697,"toc":986},"minimark",[698,702,705,708,713,723,732,739,743,746,757,760,768,778,781,787,900,903,909,915,921,924,928,931,934,937,940,943,952,956,959,962,969,973,982],[699,700,701],"p",{},"エージェントはコードの記述が得意です。しかし、その周辺システムのナビゲーションとなると話は別です。関連コード、それを実行するパイプライン、リリースするデプロイ、要求元の作業アイテム、そして担当チーム——こうした要素間のつながりを把握することが、現在のAI支援エンジニアリングが直面する課題です。",[699,703,704],{},"大規模なモノリポでは、このギャップが無駄なイテレーション、膨れ上がったトークン予算の消費、そして一見正しく見えても結局リバートされるコードとして現れます。複数リポジトリにまたがる場合はさらに深刻です。エージェントが答えにたどり着く前にコンテキストウィンドウが埋まり、タスクが完全に失敗します。エージェントの出力を修正するのに、エージェントが節約した時間以上をチームが費やすことになります。",[699,706,707],{},"現在パブリックベータ版として提供中のGitLab Orbitは、このギャップを解消します。Orbitは、コード、マージリクエスト、パイプライン、デプロイ、脆弱性、オーナーシップのすべてを含むクエリ可能なライブグラフです。チームの作業に合わせて、要素間のすべての関係性をリアルタイムで最新の状態に保ちます。エージェントは複数のツール呼び出しを継ぎ合わせる代わりに、GitLabのファーストパーティデータを直接参照して推論します。エンジニアも同じグラフをData Explorerでクエリし、変更の追跡、インシデントの調査、そして今日では手動で何時間もかかるシステム横断的な問いに答えることができます。",[709,710,712],"h2",{"id":711},"compare-the-marketでの実証","Compare the Marketでの実証",[699,714,715,716,722],{},"Compare the Marketは英国の価格比較プラットフォームです。同社は79件の実際のマージリクエストを対象に、社内AIコードレビュアー向けの",[717,718,721],"a",{"href":719,"rel":720},"https://comparethemarketcareers.com/blog/comparing-context-retrieval-approaches-for-ai-code-review/",[],"4つのコンテキスト取得アプローチを検証","しました。Orbitを活用したレビュアーは約70%の確率で正確なインラインコメントを付与し、RAG（検索拡張生成）の約58%を上回りました。変更の主要ポイントをサマリーに含める割合も68%対66%でOrbitが優位でした。RAGはコンテキストなしを含む他のすべてのアプローチを下回る結果となりました。",[699,724,725,729],{},[726,727,728],"em",{},"「Orbitにより、コードベースを本当に理解するAIコードレビュアーが実現しました。目の前の差分だけでなく、コードベース全体を理解してくれるのです。実際のマージリクエストでRAGをはじめとする複数のアプローチと比較した結果、差は明らかでした。コメントの配置精度が高く、実際の変更内容のサマリーも優れていました。最も自然な解決策と思っていたRAGが、コンテキストなしよりも劣る結果となったことは、それ自体が答えを物語っていました。」",[730,731],"br",{},[733,734,735],"ul",{},[736,737,738],"li",{},"Ryan Harvey、Head of AI Engineering、Compare the Market",[709,740,742],{"id":741},"gitlab-orbitでできること","GitLab Orbitでできること",[699,744,745],{},"以下に、GitLab Orbitを環境に導入した場合の2つのシナリオを紹介します。",[699,747,748,752,754],{},[749,750,751],"strong",{},"シナリオ1：Claude Codeやその他のコーディングエージェントとの連携",[730,753],{},[726,755,756],{},"すでに行っている作業を、より速く正確に",[699,758,759],{},"すでにClaude Codeを使用しているとします。大規模なモノリポに向けると、最初の段階でトークン予算の相当部分を費やしながら、ファイルをクロールしてどこに何があり、何がつながっているかを把握しようとします。大きなコードベースでは、間違ったスレッドを追いかけたり、依存関係を見落としたり、実際の作業を始める前にコンテキストが枯渇したりすることがあります。",[699,761,762,767],{},[717,763,766],{"href":764,"rel":765},"https://about.gitlab.com/topics/ai/model-context-protocol/",[],"MCP","（Model Context Protocol）を通じてClaude CodeをGitLab Orbitに接続すると、クロールが不要になります。エージェントはグラフに直接問いを投げます。「このコードはどこにあるか」「何が依存しているか」「どのテストとパイプラインがカバーしているか」——反復的な探索で再構築しようとしていた問いへの正確な答えが、1〜2回のクエリで返ります。同じタスク、同じモデルで、最大11倍高速化し、トークン消費を最大4.5分の1に削減し、ハルシネーションを最大45分の1に抑えます。",[699,769,770,773,775],{},[749,771,772],{},"シナリオ2：GitLab Duo Agent Platformとの連携",[730,774],{},[726,776,777],{},"これまで不可能だった問いへの回答",[699,779,780],{},"エージェントにとって本当に答えられなかった問いがあります。答えがコードの中ではなく、コードがパイプライン、デプロイ、脆弱性、システム全体のオーナーシップとどのようにつながっているかにあるからです。GitLab Duo Agent PlatformのエージェントはOrbitをネイティブにクエリするため、これまで4つのツールを横断した手動調査が必要だったことが、直接質問できるようになりました。",[699,782,783,786],{},[749,784,785],{},"パイプライン障害をライフサイクル全体でトリアージする。"," 今日、障害が発生したパイプラインを見るエージェントは、1つのジョブを孤立した状態で見ています。Orbitを使うと、エージェントはその障害を引き起こした変更まで遡り、同じジョブが現在ドリフトしているプロジェクト、そして同じ問題に遭遇する進行中のマージリクエストをトレースできます。ディスカバリーを実行するため、Orbitは次のようなグラフクエリを発行します：",[788,789,794],"pre",{"className":790,"code":791,"language":792,"meta":793,"style":793},"language-cypher shiki shiki-themes github-light","MATCH (job:CiJob {status: \"failed\", name: $job_name})-[:RAN_IN]->(pipeline)-[:FOR]->(mr:MergeRequest)\nRETURN mr.title, mr.author, pipeline.started_at, mr.project_id\nORDER BY pipeline.started_at DESC LIMIT 20\n","cypher","",[795,796,797,873,882],"code",{"__ignoreMap":793},[798,799,802,806,810,813,815,818,822,825,828,830,833,836,839,843,846,850,853,856,859,861,863,866,868,870],"span",{"class":800,"line":801},"line",1,[798,803,805],{"class":804},"sD7c4","MATCH",[798,807,809],{"class":808},"sgsFI"," (job:CiJob ",[798,811,812],{"class":804},"{",[798,814,502],{"class":808},[798,816,817],{"class":804},":",[798,819,821],{"class":820},"sYBdl"," \"failed\"",[798,823,824],{"class":804},",",[798,826,827],{"class":808}," name",[798,829,817],{"class":804},[798,831,832],{"class":808}," $job_name",[798,834,835],{"class":804},"}",[798,837,838],{"class":808},")",[798,840,842],{"class":841},"sYu0t","-",[798,844,845],{"class":804},"[:",[798,847,849],{"class":848},"s7eDp","RAN_IN",[798,851,852],{"class":804},"]",[798,854,855],{"class":841},"->",[798,857,858],{"class":808},"(pipeline)",[798,860,842],{"class":841},[798,862,845],{"class":804},[798,864,865],{"class":848},"FOR",[798,867,852],{"class":804},[798,869,855],{"class":841},[798,871,872],{"class":808},"(mr:MergeRequest)\n",[798,874,876,879],{"class":800,"line":875},2,[798,877,878],{"class":804},"RETURN",[798,880,881],{"class":808}," mr.title, mr.author, pipeline.started_at, mr.project_id\n",[798,883,885,888,891,894,897],{"class":800,"line":884},3,[798,886,887],{"class":804},"ORDER BY",[798,889,890],{"class":808}," pipeline.started_at ",[798,892,893],{"class":804},"DESC",[798,895,896],{"class":804}," LIMIT",[798,898,899],{"class":841}," 20\n",[699,901,902],{},"グループ内のすべてのプロジェクトをまたいで、同じ障害ジョブにヒットする進行中のマージリクエストが1回のクエリで返ります。オンコールチームは3つのチームが3回それぞれ対応する代わりに、1回でインシデントを解決できます。",[699,904,905,908],{},[749,906,907],{},"脆弱性の影響範囲を数分でマッピングする。"," 脆弱なコードを見つけることは容易です。露出範囲をマッピングすること——どのサービスがそのコンポーネントを含み、どのパイプラインがビルドし、どの環境で実行され、どのチームが担当しているか——がチームの足を引っ張ります。Orbitのクエリ1回でオーナー別のフルグラフが返ります。セキュリティチームはCVEが判明してから数週間後ではなく、1時間以内に修正計画を提示でき、影響を受けるコンポーネントにはそれぞれのオーナーが割り当て済みです。",[699,910,911,914],{},[749,912,913],{},"システム横断的な問いにオンデマンドで回答する。"," チーム別のサイクルタイムを、パイプライン障害率で分解し、デプロイ頻度と組み合わせる。1つの問いに1つの答え。ダッシュボードへのリクエストも、カスタムSQLも不要です。エンジニアリングマネージャーが経営レビューの場でその場で答えられ、3日後のSlackフォローアップにはなりません。",[699,916,917,920],{},[749,918,919],{},"現在の依存関係に対してマイグレーションをスコープする。"," 今日のマイグレーション計画は、共有コンポーネントを検索し、その検索が下流依存を捉えていることを願うことを意味します。Orbitを使えば、依存するサービス、ジョブ、環境、オーナーのすべてがひとつの結果として返ります。プラットフォームチームはマイグレーション日程を確約してそれを守れます。3週間後に隠れた依存関係を発見することはありません。",[699,922,923],{},"グラフは、チームがシステムのつながりを理解する必要があるあらゆるワークフローに対応します。コードレビュー、インシデント対応、リリース計画、セキュリティ、マイグレーション計画など。",[709,925,927],{"id":926},"gitlab-orbitの仕組み","GitLab Orbitの仕組み",[699,929,930],{},"Orbitは、change-data-captureを通じてソフトウェア開発ライフサイクルのデータをClickHouseに取り込み、Rails内部APIを通じて12言語（Ruby、Java、Kotlin、Python、TypeScript、JavaScript、Rust、Go、C#、C、C++、PHP）のコードをパースし、CypherライクなDSL、MCP、REST、GitLab CLIを通じて統合グラフを提供します。",[699,932,933],{},"GitLab自身のスケールでは、インデクサーは40,000以上のプロジェクト、5億のノード、20億のエッジを45分以内に処理します。イベント駆動エンジンがすべての変更をリリース時にピックアップするため、グラフは常に最新の状態を保ちます。",[699,935,936],{},"インデクシングは独立したサービスとして実行されます。クエリトラフィックはGitLabインスタンスに影響を与えません。認可はGitLabのパーミッションを反映するため、エージェントはUIでユーザーが見られるものと同じ内容を参照します。クエリエンジンはコンパイラのように構築されています。すべてのクエリはデータベースに触れる前に検証、プランニング、最適化、セキュリティのパスを経由するため、データが増えてもクエリ速度は低下しません。",[699,938,939],{},"別途データインフラを構築する必要はありません。OrbitはGitLabがすでに取得しているデータを活用します。イシュー、マージリクエスト、パイプライン、コード、セキュリティ調査結果、デプロイ、インシデントです。新たな計装なしに初日から価値を得られます。",[699,941,942],{},"GitLab Duo Agent PlatformのエージェントはOrbitをネイティブにクエリします。Claude Code、Codex、OpenCodeなどの外部エージェントはMCPとGitLab CLIを通じて接続します。カスタムエージェントや社内ツールはRESTで接続します。ひとつのグラフを、エンジニアリング組織全体で共有します。",[944,945],"iframe",{"src":946,"frameBorder":947,"allow":948,"referrerPolicy":949,"style":950,"title":951},"https://player.vimeo.com/video/1199521642?title=0&byline=0&portrait=0&badge=0&autopause=0&player_id=0&app_id=58479","0","autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share","strict-origin-when-cross-origin","position:absolute;top:0;left:0;width:100%;height:100%;","Orbit GKG Team Demo_Section 2_060526_v4",[953,954],"script",{"src":955},"https://player.vimeo.com/api/player.js",[709,957,958],{"id":958},"エンジニアも同じグラフをクエリできる",[699,960,961],{},"Data Explorerはエンジニア向けのインターフェースです。同じグラフを、エージェントを介さずに直接使えます。固定プロンプトに収まらない作業——インシデントの調査、依存関係がサービス間にどう広がっているかの追跡、コードベースの特定領域でCI障害が続く原因の特定——に役立ちます。答えはGit、CI、デプロイツール、ダッシュボードを横断した何時間もの手動再構築ではなく、数秒で返ってきます。",[699,963,964],{},[965,966],"img",{"alt":967,"src":968,"title":967},"GitLab Orbit Data Explorer","https://res.cloudinary.com/about-gitlab-com/image/upload/v1780996810/m9i3xengoidonz5vmvdf.png",[709,970,972],{"id":971},"今すぐorbitを試す","今すぐOrbitを試す",[699,974,975,976,981],{},"GitLab OrbitはGitLab.comのPremiumおよびUltimateのお客様向けにパブリックベータ版として提供中です。",[717,977,980],{"href":978,"rel":979},"https://about.gitlab.com/ja-jp/gitlab-orbit",[],"about.gitlab.com/ja-jp/gitlab-orbit","からお申し込みいただけます。",[983,984,985],"style",{},"html pre.shiki code .sD7c4, html code.shiki .sD7c4{--shiki-default:#D73A49}html pre.shiki code .sgsFI, html code.shiki .sgsFI{--shiki-default:#24292E}html pre.shiki code .sYBdl, html code.shiki .sYBdl{--shiki-default:#032F62}html pre.shiki code .sYu0t, html code.shiki .sYu0t{--shiki-default:#005CC5}html pre.shiki code .s7eDp, html code.shiki .s7eDp{--shiki-default:#6F42C1}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}",{"title":793,"searchDepth":875,"depth":875,"links":987},[988,989,990,991,992],{"id":711,"depth":875,"text":712},{"id":741,"depth":875,"text":742},{"id":926,"depth":875,"text":927},{"id":958,"depth":875,"text":958},{"id":971,"depth":875,"text":972},"2026-06-10","GitLab Orbitで、ソフトウェアエージェントは最大11倍高速化し、トークン消費を最大4.5分の1に削減。これまで答えられなかった質問にも対応できます。","md","https://res.cloudinary.com/about-gitlab-com/image/upload/v1780996524/sd1vpl8empy26wizarqj.png",{},"/ja-jp/blog/introducing-gitlab-orbit",{"config":1000,"title":1001,"description":1002},{"noIndex":10},"GitLab Orbit登場：エージェントを最大11倍高速化","GitLab Orbitは、ソフトウェアエージェントを最大11倍高速化し、トークン消費量を最大4.5分の1に削減できます。コード、パイプライン、デプロイ、脆弱性などの全体像をひとつのクエリで把握でき、これまで答えられなかった質問にも対応できます。","introducing-gitlab-orbit","ja-jp/blog/introducing-gitlab-orbit",[1006,9,1007,1008],"product","news","features","BlogPost","2026-06-11","AvKYIZTWk8Ee2Zu-YrLxno_nlaQrQbBQ2Sa11Hq79e0",[1013,1020,1027,1035,1041,1048,1055,1061,1067],{"title":1014,"heroImage":1015,"category":9,"description":1016,"authors":1017,"slug":1019,"externalUrl":6},"GitLab Flex：1つの年間コミットメントで、シートとAI支出を柔軟に調整","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772047747/ntihfmnu2fepamqemaas.png","エージェント型AIの時代には、必要なシート数・AI使用量・利用したい機能を事前に予測することはできません。GitLab Flexなら、再調達なしでシート・AI使用量・新機能を月次で柔軟に調整できる1つの年間コミットメントで、変化するニーズに対応できます。\n",[1018],"Talia Armato-Helle","introducing-gitlab-flex",{"title":1021,"heroImage":1022,"category":9,"description":1023,"authors":1024,"slug":1026,"externalUrl":6},"GitLab：エージェント型エンジニアリング時代のプラットフォーム","https://res.cloudinary.com/about-gitlab-com/image/upload/v1781032585/go3d7pb9opmux7rwhpev.png","GitLab Transcendで発表した内容と、エンタープライズに必要な統制を維持しながらエージェント型の開発スピードを実現する方法をご紹介します。",[1025],"Manav Khurana","gitlab-transcend-announcements",{"title":1028,"heroImage":1029,"category":9,"description":1030,"authors":1031,"slug":1034,"externalUrl":6},"GitLab on Google Cloud - Google Cloud上でフルマネージド運用、コンプライアンス対応、AI活用を実現","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663121/Blog/Hero%20Images/LogoLockupPlusLight.png","Google CloudでGitLabをフルマネージドで運用。最新のGeminiモデルを標準搭載し、GitLab認定MSPがデータ主権・コンプライアンス要件に対応した安全な環境を提供。Google CloudコミットメントでGitLabクレジットを活用できます。",[1032,1033],"Regnard Raquedan","Rajesh Agadi","gitlab-expands-google-model-support",{"title":1036,"heroImage":1037,"category":9,"description":1038,"authors":1039,"slug":1040,"externalUrl":6},"MythosクラスのClaude Fable 5がGitLab Duo Agent Platformに登場","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098611/Blog/Hero%20Images/Blog/Hero%20Images/blog-hero-banner-1-0178-820x470-fy25_7JlF3WlEkswGQbcTe8DOTB_1750098611370.png","AnthropicのMythosクラスAIモデルClaude Fable 5がGitLab Duo Agent Platformに登場。長時間にわたる自律的なタスク実行、高い初回精度、より精度の高いコードレビューで、開発チームの生産性を次のレベルへ引き上げます。",[1018],"mythos-class-claude-fable-5-on-gitlab",{"title":1042,"heroImage":1043,"category":9,"description":1044,"authors":1045,"slug":1047,"externalUrl":6},"エージェント型コーディングの品質はコンテキスト次第","https://res.cloudinary.com/about-gitlab-com/image/upload/v1773856365/gsx2c0vqlswox3ldmq88.jpg","エージェント型コーディングはスピードをもたらします。GitLabのライフサイクルコンテキストにより、企業は表面的な修正や長いレビューサイクルといった課題に対処できます。",[1046],"Jessica Taylor","agentic-coding-only-as-good-as-context",{"title":1049,"heroImage":1050,"category":9,"description":1051,"authors":1052,"slug":1054,"externalUrl":6},"GitLab 19.0: マージリクエストを手動作業から自動化ワークフローへ","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779189265/iqzyhhiwagxzwywvjzow.png","GitLab 19.0では、デベロッパーフローがMRライフサイクル全体に拡張されました。レビュアーフィードバックへの対応、自律的なマージコンフリクト解決、ワンクリックリベース＆マージにより、MRにかかる手動作業を大幅に削減します。",[1053],"Corinne Dent","transform-mrs-to-automated-workflow",{"title":1056,"heroImage":1050,"category":9,"description":1057,"authors":1058,"slug":1060,"externalUrl":6},"GitLab Duo Agent Platform Self-HostedでさらなるAIモデルに対応","GitLab 19.0でDuo Agent Platform Self-Hostedのオープンソースモデルサポートが拡充。エアギャップや規制対応環境でも、複雑なエージェント型タスクに対応できる高性能なAIモデルを選択できるようになりました。",[1059],"Jordan Janes","more-ai-models-for-duo-agent-platform-self-hosted",{"title":1062,"heroImage":1043,"category":9,"description":1063,"authors":1064,"slug":1066,"externalUrl":6},"GitLab Duo Agent Platformのカスタムエージェントでデプロイプロセスを自動化する","GitLab Duo Agent Platformのカスタムエージェントを使えば、複雑で反復的なGitOps作業を数分で自動化できます。バージョン管理・ガバナンス・セキュリティはエンタープライズの要件に沿ったまま維持され、スピードとコントロールを両立できます。",[1065],"Cesar Saavedra","automate-deployment-with-duo-agent-platform",{"title":1068,"heroImage":1069,"category":9,"description":1070,"authors":1071,"slug":1073,"externalUrl":6},"Claude CodeとGitLab：リリースまでの3つのワークフロー","https://res.cloudinary.com/about-gitlab-com/image/upload/v1778087000/qdfsf8kz6ebfnopx9v2e.png","エージェント型AIコーディングツールを使用するとコードを素早く書けるようになります。しかし、リリースするのは誰でしょうか？Claude CodeとGitLab Duo Agent Platformを組み合わせることで、バグレポートから本番環境での修正まで一貫して実現できます。本ブログでは、その方法をご紹介します。",[1072],"Michael Friedrich","claude-code-and-gitlab",1781392697669]