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Sie sind jedoch deutlich schlechter darin, das System dahinter zu navigieren: den verwandten Code, die Pipelines, die ihn ausführen, die Deployments, die ihn ausliefern, die Work Items, die ihn angefordert haben, und die Teams, die ihn verantworten. Genau diese Lücke ist es, an der KI-gestützte Softwareentwicklung heute scheitert.",[699,703,704],{},"In einem großen Monorepo zeigt sich diese Lücke als verschwendete Iterationen, aufgebrauchte Token-Budgets und Code, der korrekt aussieht, aber rückgängig gemacht wird. Über mehrere Repositories hinweg ist es noch problematischer: Das Kontextfenster füllt sich, bevor der Agent die Antwort findet, und die Aufgabe scheitert vollständig. Teams verbringen am Ende mehr Zeit damit, Agent-Ausgaben zu korrigieren, als der Agent ihnen eingespart hat.",[699,706,707],{},"GitLab Orbit, jetzt in der öffentlichen Beta, schließt diese Lücke. Es handelt sich um einen Live-Graphen mit Abfragemöglichkeit für Code, Merge Requests, Pipelines, Deployments, Schwachstellen und Eigentümerschaft – mit allen Beziehungen dazwischen, die laufend aktualisiert werden, während das Team arbeitet. Agents arbeiten auf Basis nativer GitLab-Daten statt auf zusammengesetzten Tool-Aufrufen. Entwicklungsteams können denselben Graphen über den Data Explorer abfragen, um Änderungen nachzuverfolgen, Incidents zu untersuchen und systemübergreifende Fragen zu beantworten, die heute stundenlange manuelle Rekonstruktion erfordern.",[709,710,712],"h2",{"id":711},"validiert-an-realen-merge-requests-bei-compare-the-market","Validiert an realen Merge Requests bei Compare the Market",[699,714,715,716,722],{},"Compare the Market, eine britische Preisvergleichsplattform, hat ",[717,718,721],"a",{"href":719,"rel":720},"https://comparethemarketcareers.com/blog/comparing-context-retrieval-approaches-for-ai-code-review/",[],"vier Kontextabruf-Ansätze"," für einen internen KI-Code-Reviewer an 79 realen Merge Requests getestet. Der Orbit-gestützte Reviewer platzierte in etwa 70 % der Fälle korrekte Inline-Kommentare, gegenüber etwa 58 % bei Retrieval-Augmented Generation (RAG), und erfasste mehr der wesentlichen Änderungen in Zusammenfassungen (68 % gegenüber 66 %). RAG schnitt schlechter ab als alle anderen Ansätze – einschließlich des Ansatzes ohne Kontext.",[699,724,725,729,732],{},[726,727,728],"em",{},"„Orbit hat uns einen KI-Code-Reviewer gegeben, der unsere Codebasis tatsächlich versteht – nicht nur den Diff vor ihm. Wir haben ihn gegen RAG und einige andere Ansätze an realen Merge Requests getestet, und der Unterschied war eindeutig. Bessere Kommentarplatzierung, bessere Zusammenfassungen der tatsächlichen Änderungen. RAG, von dem wir angenommen hatten, dass es die naheliegende Lösung wäre, schnitt am Ende schlechter ab als gar kein Kontext. Für uns hat dieses Ergebnis für sich gesprochen.\"",[730,731],"br",{},"\n- Ryan Harvey, Head of AI Engineering, Compare the Market",[709,734,736],{"id":735},"was-sich-mit-gitlab-orbit-machen-lässt","Was sich mit GitLab Orbit machen lässt",[699,738,739],{},"Zwei Beispiele zeigen, wie GitLab Orbit in der eigenen Umgebung eingesetzt werden kann.",[699,741,742,746,748],{},[743,744,745],"strong",{},"Szenario 1: Mit Claude Code oder anderen Coding-Agents",[730,747],{},[726,749,750],{},"Die gleiche Arbeit, schneller und präziser",[699,752,753],{},"Angenommen, Claude Code ist bereits im Einsatz. Wenn es auf ein großes Monorepo ausgerichtet wird, verbringt es zu Beginn – und dabei einen erheblichen Teil des Token-Budgets – damit, Dateien zu durchsuchen, um zu ermitteln, wo sich was befindet und was womit zusammenhängt. In einer ausreichend großen Codebasis folgt es falschen Spuren, übersieht eine Abhängigkeit oder erschöpft das Kontextfenster, bevor die eigentliche Arbeit beginnt.",[699,755,756,757,762],{},"Claude Code über das Model Context Protocol (",[717,758,761],{"href":759,"rel":760},"https://about.gitlab.com/topics/ai/model-context-protocol/",[],"MCP",") mit GitLab Orbit verbinden – und das Durchsuchen entfällt. Der Agent stellt dem Graphen die Fragen, die er zuvor durch iteratives Erkunden zu rekonstruieren versuchte: Wo befindet sich dieser Code? Was hängt davon ab? Welche Tests und Pipelines decken ihn ab? Stattdessen erhält er in einer oder zwei Abfragen eine präzise Antwort. Bei denselben Aufgaben, mit demselben Modell, ist es bis zu 11-mal schneller, verbraucht bis zu 4,5-mal weniger Tokens und erzeugt bis zu 45-mal weniger Halluzinationen.",[699,764,765,768,770],{},[743,766,767],{},"Szenario 2: Mit GitLab Duo Agent Platform",[730,769],{},[726,771,772],{},"Antworten auf bisher unlösbare Fragen",[699,774,775],{},"Manche Fragen waren für einen Agent schlicht nicht beantwortbar, weil die Antwort nicht im Code selbst liegt – sondern darin, wie Code mit Pipelines, Deployments, Schwachstellen und Eigentümerschaft im gesamten System zusammenhängt. Agents auf GitLab Duo Agent Platform fragen Orbit nativ ab, sodass Fragen gestellt werden können, die zuvor eine manuelle Untersuchung über vier Tools erfordert hätten.",[699,777,778,781],{},[743,779,780],{},"Pipeline-Fehler über den gesamten Lifecycle hinweg triagieren."," Heute sieht ein Agent bei einer fehlschlagenden Pipeline einen einzelnen Job isoliert. Mit Orbit verfolgt er den Fehler zurück bis zur Änderung, die ihn verursacht hat, zu den Projekten, in denen derselbe Job jetzt driftet, und zu den Merge Requests, die noch in Arbeit sind und auf dasselbe Problem treffen werden. Für die Analyse stellt Orbit Graph-Abfragen wie folgende:",[783,784,789],"pre",{"className":785,"code":786,"language":787,"meta":788,"style":788},"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","",[790,791,792,868,877],"code",{"__ignoreMap":788},[793,794,797,801,805,808,810,813,817,820,823,825,828,831,834,838,841,845,848,851,854,856,858,861,863,865],"span",{"class":795,"line":796},"line",1,[793,798,800],{"class":799},"sD7c4","MATCH",[793,802,804],{"class":803},"sgsFI"," (job:CiJob ",[793,806,807],{"class":799},"{",[793,809,504],{"class":803},[793,811,812],{"class":799},":",[793,814,816],{"class":815},"sYBdl"," \"failed\"",[793,818,819],{"class":799},",",[793,821,822],{"class":803}," name",[793,824,812],{"class":799},[793,826,827],{"class":803}," $job_name",[793,829,830],{"class":799},"}",[793,832,833],{"class":803},")",[793,835,837],{"class":836},"sYu0t","-",[793,839,840],{"class":799},"[:",[793,842,844],{"class":843},"s7eDp","RAN_IN",[793,846,847],{"class":799},"]",[793,849,850],{"class":836},"->",[793,852,853],{"class":803},"(pipeline)",[793,855,837],{"class":836},[793,857,840],{"class":799},[793,859,860],{"class":843},"FOR",[793,862,847],{"class":799},[793,864,850],{"class":836},[793,866,867],{"class":803},"(mr:MergeRequest)\n",[793,869,871,874],{"class":795,"line":870},2,[793,872,873],{"class":799},"RETURN",[793,875,876],{"class":803}," mr.title, mr.author, pipeline.started_at, mr.project_id\n",[793,878,880,883,886,889,892],{"class":795,"line":879},3,[793,881,882],{"class":799},"ORDER BY",[793,884,885],{"class":803}," pipeline.started_at ",[793,887,888],{"class":799},"DESC",[793,890,891],{"class":799}," LIMIT",[793,893,894],{"class":836}," 20\n",[699,896,897],{},"Eine Abfrage, jeder laufende MR, der auf denselben fehlschlagenden Job treffen wird, über alle Projekte der Gruppe. Das On-Call-Team löst den Incident einmal – statt dass drei Teams ihn dreimal separat lösen.",[699,899,900,903],{},[743,901,902],{},"Den Blast Radius einer Schwachstelle in Minuten kartieren."," Den verwundbaren Code zu finden ist der einfache Teil. Die Exposition zu kartieren – welche Services die Komponente einbinden, welche Pipelines sie bauen, in welchen Umgebungen sie laufen, welche Teams sie verantworten – ist das, was Teams aufhält. Eine Orbit-Abfrage gibt den vollständigen Graphen zurück, Eigentümer für Eigentümer. Das Security-Team liefert einen Behebungsplan in der Stunde, in der eine CVE eintrifft – nicht erst eine Woche später –, mit jeder betroffenen Komponente bereits dem zuständigen Eigentümer zugewiesen.",[699,905,906,909],{},[743,907,908],{},"Systemübergreifende Fragen auf Abruf beantworten."," Cycle Time nach Team, aufgeschlüsselt nach Pipeline-Fehlerrate, verknüpft mit Deployment-Frequenz. Eine Frage, eine Antwort, keine Dashboard-Anfrage, kein Custom SQL. Engineering-Manager beantworten die Frage live im Executive Review – nicht in einer Slack-Nachricht drei Tage später.",[699,911,912,915],{},[743,913,914],{},"Migrationen gegen aktuelle Abhängigkeiten absichern."," Eine Migration zu planen bedeutet heute, nach einer gemeinsam genutzten Komponente zu suchen und zu hoffen, dass die Suche die nachgelagerten Abhängigkeiten erfasst. Mit Orbit werden alle abhängigen Services, Jobs, Umgebungen und Eigentümer in einem einzigen Ergebnis zurückgegeben. Plattform-Teams halten Migrationstermine ein, statt drei Wochen später versteckte Abhängigkeiten zu entdecken.",[699,917,918],{},"Der Graph unterstützt jeden Workflow, bei dem Klarheit darüber benötigt wird, wie das System zusammenhängt: Code Review, Incident Response, Release-Planung, Security, Migrationsplanung.",[709,920,922],{"id":921},"wie-gitlab-orbit-funktioniert","Wie GitLab Orbit funktioniert",[699,924,925],{},"Orbit erfasst SDLC-Daten über Change-Data-Capture in ClickHouse, analysiert Code in 12 Sprachen (Ruby, Java, Kotlin, Python, TypeScript, JavaScript, Rust, Go, C#, C, C++, PHP) über die interne Rails-API und stellt den kombinierten Graphen über eine Cypher-ähnliche DSL, MCP, REST und die GitLab CLI bereit.",[699,927,928],{},"Im eigenen Betrieb bei GitLab deckt der Indexer über 40.000 Projekte, 500 Millionen Knoten und 2 Milliarden Kanten in unter 45 Minuten ab. Eine ereignisgesteuerte Engine erfasst jede Änderung, sobald sie eintrifft, sodass der Graph aktuell bleibt.",[699,930,931],{},"Die Indizierung läuft als separater Dienst; Query-Traffic trifft nie auf die GitLab-Instanz. Die Autorisierung spiegelt GitLab-Berechtigungen wider, sodass Agents genau das sehen, was in der Benutzeroberfläche für den jeweiligen Nutzer sichtbar ist. Die Query-Engine ist wie ein Compiler aufgebaut: Jede Abfrage durchläuft Validierung, Planung, Optimierung und Sicherheitsprüfungen, bevor sie die Datenbank berührt, sodass die Abfragegeschwindigkeit nicht abnimmt, wenn die Datenmenge wächst.",[699,933,934],{},"Es ist keine separate Dateninfrastruktur erforderlich. Orbit baut auf Daten auf, die GitLab bereits erfasst: Issues, Merge Requests, Pipelines, Code, Sicherheitsbefunde, Deployments und Incidents. Der Mehrwert entsteht ab dem ersten Tag ohne neue Instrumentierung.",[699,936,937],{},"Agents auf GitLab Duo Agent Platform fragen den Graphen nativ ab. Externe Agents wie Claude Code, Codex und OpenCode verbinden sich über MCP und die GitLab CLI. Custom Agents und interne Tools verbinden sich über REST. Ein Graph, gemeinsam genutzt von der gesamten Engineering-Organisation.",[939,940],"iframe",{"src":941,"frameBorder":942,"allow":943,"referrerPolicy":944,"style":945,"title":946},"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",[948,949],"script",{"src":950},"https://player.vimeo.com/api/player.js",[709,952,954],{"id":953},"entwicklungsteams-fragen-denselben-graphen-ab","Entwicklungsteams fragen denselben Graphen ab",[699,956,957],{},"Der Data Explorer ist die für Entwicklungsteams zugängliche Oberfläche. Derselbe Graph, ohne Agent dazwischen. Nützlich für Aufgaben, die sich keinem festen Prompt zuordnen lassen: einen Incident untersuchen, verfolgen, wie sich eine Abhängigkeit über Services verteilt, herausfinden, warum ein Bereich der Codebasis CI wiederholt unterbricht. Die Antworten kommen in Sekunden – statt nach stundenlanger manueller Rekonstruktion über Git, CI, Deploy-Tools und Dashboards.",[699,959,960],{},[961,962],"img",{"alt":963,"src":964,"title":963},"GitLab Orbit Data Explorer","https://res.cloudinary.com/about-gitlab-com/image/upload/v1780996810/m9i3xengoidonz5vmvdf.png",[709,966,968],{"id":967},"orbit-jetzt-ausprobieren","Orbit jetzt ausprobieren",[699,970,971,972,977],{},"GitLab Orbit ist derzeit in der öffentlichen Beta für GitLab.com Premium- und Ultimate-Kunden verfügbar. Die Anmeldung erfolgt über ",[717,973,976],{"href":974,"rel":975},"https://about.gitlab.com/de-de/gitlab-orbit",[],"about.gitlab.com/gitlab-orbit",".",[709,979,981],{"id":980},"für-deutsche-unternehmen-könnte-dies-folgende-themen-betreffen","Für deutsche Unternehmen könnte dies folgende Themen betreffen",[699,983,984],{},"Teams, die SDLC-Transparenz und KI-gestütztes Vulnerability-Management in ihrer Entwicklungsinfrastruktur ausbauen, haben möglicherweise auch Compliance-Überlegungen – beispielsweise in Bereichen wie Zugriffskontrolle für Agent-Aktionen, Schwachstellen-Nachverfolgung und Incident-Dokumentation. Die Autorisierungsarchitektur von Orbit, bei der Agents genau die Sichtbarkeit erhalten wie der jeweilige Nutzer, adressiert dabei ähnliche Themen wie in NIS2 und ISO 27001. Für konkrete Compliance-Anforderungen empfiehlt sich Rücksprache mit entsprechender Fachberatung.",[986,987,988],"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":788,"searchDepth":870,"depth":870,"links":990},[991,992,993,994,995,996],{"id":711,"depth":870,"text":712},{"id":735,"depth":870,"text":736},{"id":921,"depth":870,"text":922},{"id":953,"depth":870,"text":954},{"id":967,"depth":870,"text":968},{"id":980,"depth":870,"text":981},"2026-06-10","Mit Orbit sind Software-Agenten bis zu 11-mal schneller, nutzen bis zu 4,5-mal weniger Tokens und beantworten bisher unlösbare Fragen.","md","https://res.cloudinary.com/about-gitlab-com/image/upload/v1780996524/sd1vpl8empy26wizarqj.png",{},"/de-de/blog/introducing-gitlab-orbit",{"config":1004,"title":1005,"description":998},{"noIndex":10},"GitLab Orbit: KI-Agenten mit Code- und Lifecycle-Kontext","introducing-gitlab-orbit","de-de/blog/introducing-gitlab-orbit",[1009,9,1010,1011],"product","news","features","BlogPost","GZaoFCQdpwahgAw1QoEERz0PdeQbotymb70POjnUQOQ",[1015,1022,1029,1037,1043,1049,1056,1063,1069],{"title":1016,"heroImage":1017,"category":9,"description":1018,"authors":1019,"slug":1021,"externalUrl":6},"Seats und KI-Ausgaben flexibel steuern – mit GitLab Flex","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772047747/ntihfmnu2fepamqemaas.png","In der agentischen Ära lassen sich Seat-Bedarf, KI-Nutzung und neue Funktionen kaum planen. GitLab Flex: eine Vereinbarung, monatlich anpassbar.\n",[1020],"Talia Armato-Helle","introducing-gitlab-flex",{"title":1023,"heroImage":1024,"category":9,"description":1025,"authors":1026,"slug":1028,"externalUrl":6},"GitLab: entwickelt für die Ära des agentischen Engineering","https://res.cloudinary.com/about-gitlab-com/image/upload/v1781032585/go3d7pb9opmux7rwhpev.png","Alle Ankündigungen von GitLab Transcend – wie eine Plattform agentische Geschwindigkeit mit der Kontrolle liefert, die Unternehmen benötigen.",[1027],"Manav Khurana","gitlab-transcend-announcements",{"title":1030,"heroImage":1031,"category":9,"description":1032,"authors":1033,"slug":1036,"externalUrl":6},"GitLab auf Google Cloud: vollständig verwaltet, compliant und KI-bereit","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663121/Blog/Hero%20Images/LogoLockupPlusLight.png","GitLab und Duo Agent Platform im Google Cloud Marketplace erwerben, Cloud-Budgets einsetzen und Daten regulatorisch konform aufbewahren.",[1034,1035],"Regnard Raquedan","Rajesh Agadi","gitlab-expands-google-model-support",{"title":1038,"heroImage":1039,"category":9,"description":1040,"authors":1041,"slug":1042,"externalUrl":6},"Claude Fable 5: Mythos-Modell von Anthropic jetzt auf GitLab Duo Agent Platform verfügbar","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","Anthropics neues KI-Modell bringt erweiterte Autonomie, höhere Treffsicherheit beim ersten Versuch und präzisere Code Reviews zu GitLab.",[1020],"mythos-class-claude-fable-5-on-gitlab",{"title":1044,"heroImage":1045,"category":9,"description":1046,"authors":1047,"slug":1048,"externalUrl":6},"Claude Opus 4.8 auf GitLab: komplexe agentische Aufgaben, weniger Unterbrechungen","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776457632/llddiylsgwuze0u1rjks.png","Claude Opus 4.8 ist ab sofort in GitLab Duo Agent Platform verfügbar – entwickelt für komplexe mehrstufige Agentenaufgaben mit weniger Unterbrechungen.",[1020],"claude-opus-4-8-on-gitlab",{"title":1050,"heroImage":1051,"category":9,"description":1052,"authors":1053,"slug":1055,"externalUrl":6},"Agentisches Coding ist nur so gut wie sein Kontext","https://res.cloudinary.com/about-gitlab-com/image/upload/v1773856365/gsx2c0vqlswox3ldmq88.jpg","Coding-Agenten liefern Geschwindigkeit. Mit Lifecycle-Kontext in GitLab adressieren Unternehmen oberflächliche Fixes und längere Review-Zyklen.",[1054],"Jessica Taylor","agentic-coding-only-as-good-as-context",{"title":1057,"heroImage":1058,"category":9,"description":1059,"authors":1060,"slug":1062,"externalUrl":6},"Merge Requests von manuellen Aufgaben in einen automatisierten Workflow verwandeln","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779189265/iqzyhhiwagxzwywvjzow.png","Dieses Release bringt einen leistungsstärkeren Developer Flow, autonome Merge-Konfliktlösung und One-Click-Rebase-and-Merge für GitLab.",[1061],"Corinne Dent","transform-mrs-to-automated-workflow",{"title":1064,"heroImage":1058,"category":9,"description":1065,"authors":1066,"slug":1068,"externalUrl":6},"Mehr KI-Modelle für GitLab Duo Agent Platform Self-Hosted","GitLab 19.0 bringt breitere Unterstützung für Open-Source-Modelle für Duo Agent Platform Self-Hosted. Mehr leistungsstarke KI-Optionen für regulierte Umgebungen.",[1067],"Jordan Janes","more-ai-models-for-duo-agent-platform-self-hosted",{"title":1070,"heroImage":1071,"category":9,"description":1072,"authors":1073,"slug":1075,"externalUrl":6},"Beyond BYOK: Warum KI-Agenten Governance brauchen","https://res.cloudinary.com/about-gitlab-com/image/upload/v1773866173/vte9qh8rriznvyclhkes.png","BYOK bietet Flexibilität – echte Governance erfordert mehr. GitLab Duo CLI liefert auditierbare, kontrollierte CI/CD-Automatisierung für KI-Agenten.",[1074],"Jessica Hurwitz","gitlab-duo-cli-governance",1781392784732]