[{"data":1,"prerenderedAt":1205},["ShallowReactive",2],{"/de-de/blog/agentic-coding-only-as-good-as-context":3,"navigation-de-de":439,"banner-de-de":858,"footer-de-de":867,"blog-post-authors-de-de-Jessica Taylor":1106,"blog-related-posts-de-de-agentic-coding-only-as-good-as-context":1120,"blog-promotions-de-de":1143,"next-steps-de-de":1195},{"id":4,"title":5,"authors":6,"body":8,"category":420,"date":421,"description":422,"extension":423,"externalUrl":424,"featured":425,"heroImage":426,"meta":427,"navigation":425,"path":428,"seo":429,"slug":432,"stem":433,"tags":434,"template":437,"updatedDate":424,"__hash__":438},"blogPosts/de-de/blog/agentic-coding-only-as-good-as-context.md","Agentisches Coding ist nur so gut wie sein Kontext",[7],"Jessica Taylor",{"type":9,"value":10,"toc":407},"minimark",[11,20,23,26,29,34,56,63,70,93,99,117,120,126,132,136,139,160,165,168,171,175,178,181,197,200,208,211,226,232,239,251,257,263,269,273,282,285,288,291,295,298,301,321,325,328,334,343,349,367,371,374,383,392],[12,13,14,15,19],"p",{},"Jede Woche zeigt eine neue Demo eines Coding-Agenten, wie ein Prompt in unter\nfünf Minuten zu einem Pull Request wird. Diese Demos konzentrieren sich oft auf\neinen engen Anwendungsfall, der noch nicht in der Produktion ist, und überspringen\nalles, was ",[16,17,18],"em",{},"nach"," dem Commit passiert.",[12,21,22],{},"Der Pull Request enthält keinen Link zu dem Issue, das er lösen sollte. Die\nCI/CD-Pipeline schlägt fehl, weil der Agent nichts von einer kürzlich\nhinzugefügten Linter-Regel wusste. Ein Security-Scan markiert eine Abhängigkeit,\ndie der Agent eingezogen hat, ohne die genehmigte Liste des Projekts zu prüfen.",[12,24,25],{},"Das sind Kontextfehler – und sie entscheiden darüber, ob agentisches Coding die\nAuslieferung beschleunigt oder Nacharbeit erzeugt. Wenn Entwicklungsteams\nCoding-Agenten mit GitLab einsetzen, greifen die Agenten auf die Issues,\nPipelines und Security-Policies zurück, die bereits in der Plattform vorhanden\nsind, erkennen Probleme und beheben sie im Developer-Flow.",[12,27,28],{},"Dieser Artikel zeigt, was sich ändert, wenn einem Coding-Agenten schrittweise\nmehr Lifecycle-Kontext gegeben wird – vom reinen Repository bis zur vollständigen\nPlattform-Sichtbarkeit – anhand zweier aktueller GitLab-Tutorials. Dabei wird\ndeutlich, wie Plattform-Kontext Code-Qualität, Security-Bewertungen und\nReview-Zyklen verbessert und was Platform-Teams heute tun können, um die Lücke\nzu schließen.",[30,31,33],"h2",{"id":32},"kontext-in-der-praxis","Kontext in der Praxis",[12,35,36,37,43,44,49,50,55],{},"Die GitLab-Tutorials zeigen, was passiert, wenn einem externen Coding-Agenten\nschrittweise mehr vollständiger Plattform-Kontext gegeben wird. Das erste\nTutorial illustriert\n",[38,39,42],"a",{"href":40,"rel":41},"https://about.gitlab.com/de-de/blog/claude-code-and-gitlab/",[],"drei Workflows mit Claude Code",":\ndas Beheben eines C++-Sensor-Absturzes, das Anreichern der Session mit dem\n",[38,45,48],{"href":46,"rel":47},"https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_server/",[],"GitLab-MCP-Server","\nund den Einsatz von Claude Code als externem Agenten innerhalb eines Merge\nRequests zur Bearbeitung von Review-Feedback. Das zweite Tutorial folgt derselben\nProgression mit\n",[38,51,54],{"href":52,"rel":53},"https://about.gitlab.com/de-de/blog/fix-bugs-with-codex-and-gitlab/",[],"Codex und GitLab","\n– diesmal beim Beheben eines Rust-WebSocket-Filterbugs in denselben drei Szenarien.",[12,57,58,62],{},[59,60,61],"strong",{},"Szenario 1: Der Agent sieht nur das Repository","\nDer Agent wird auf die Codebase gerichtet, das Problem im Prompt beschrieben.\nDer Agent liest Dateien, schlägt einen Fix vor und führt den Build aus. Der Fix\nfunktioniert, basiert aber nur auf dem, was der Agent aus lokalen Dateien und\ndem Prompt ableitet. Er kennt den organisationalen Kontext nicht: die\nAbnahmekriterien des Issues, die nicht-funktionalen Anforderungen oder die\nReview-Standards in der CI-Konfiguration. Der Code compiliert – ist aber\nmöglicherweise nicht das, was das Team braucht.",[12,64,65],{},[66,67],"img",{"alt":68,"src":69},"Szenario 1. Der Agent sieht nur das Repository","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986318/cykpoimst2bhiqxkmkyi.png",[12,71,72,75,76,79,80,84,85,88,89,92],{},[59,73,74],{},"Szenario 2: Der Agent sieht Repository und GitLab-Issue","\nMit dem verbundenen\n",[38,77,48],{"href":46,"rel":78},[],"\nkann der Agent das Issue abrufen, bevor er Code schreibt. Jetzt liest er die\nfunktionalen Anforderungen, Implementierungsnotizen, Labels und Milestones. Im\nCodex-und-GitLab-Tutorial fügt der Agent ",[81,82,83],"code",{},"Closes #32"," in die\nMerge-Request-Beschreibung ein, weil er die Beziehung zwischen Code-Änderung\nund Issue versteht. Im Claude-Code-Tutorial verwendet der Agent ",[81,86,87],{},"get_issue",", um\nden Bug-Report abzurufen, dann ",[81,90,91],{},"create_merge_request",", um den MR mit den\nrichtigen Referenzen zu erstellen. Diesmal ist der Fix das, was das Team geplant\nhat.",[12,94,95],{},[66,96],{"alt":97,"src":98},"Szenario 2. Der Agent sieht Repository und GitLab-Issue","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986319/wvbxpdm79ucuicyqmbhx.png",[12,100,101,104,105,110,111,116],{},[59,102,103],{},"Szenario 3: Der Agent arbeitet innerhalb des Merge Requests","\nSobald der MR existiert, läuft der\n",[38,106,109],{"href":107,"rel":108},"https://docs.gitlab.com/user/duo_agent_platform/flows/foundational_flows/code_review/",[],"GitLab Code Review Flow","\nautomatisch und postet Feedback. In beiden Tutorials wird der Coding-Agent als\n",[38,112,115],{"href":113,"rel":114},"https://docs.gitlab.com/user/duo_agent_platform/agents/external/",[],"externer Agent","\ninnerhalb des MR aufgerufen, um das Review-Feedback zu adressieren. Er fügt\nfehlende Tests hinzu, aktualisiert Dokumentationskommentare und behebt\nValidierungslücken, die das Review gefunden hat. Der Agent committed direkt in\nden MR-Branch, CI/CD-Pipelines laufen automatisch auf dem neuen Commit, und\nein Reviewer kann das Ergebnis prüfen, ohne das Werkzeug zu wechseln.",[12,118,119],{},"In diesem Szenario demonstrieren beide Tutorials weniger Review-Runden und\nkürzere Zeit bis zum Merge.",[12,121,122],{},[66,123],{"alt":124,"src":125},"Szenario 3. Der Agent arbeitet innerhalb des Merge Requests","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986318/wnijcgfsh06rrxkyex09.png",[12,127,128],{},[66,129],{"alt":130,"src":131},"Weiteres zu Szenario 3. Der Agent arbeitet innerhalb des Merge Requests","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986318/sbybw7hs3dkbxplqblgj.png",[30,133,135],{"id":134},"die-bedeutung-von-plattform-sichtbarkeit-für-agentisches-coding","Die Bedeutung von Plattform-Sichtbarkeit für agentisches Coding",[12,137,138],{},"Platform-Teams entscheiden, wie KI-gestützte Entwicklung über die gesamte\nOrganisation funktioniert: welche Agenten erlaubt sind, auf welche Werkzeuge\nsie zugreifen dürfen, wie Ausgaben verifiziert werden und wo menschliche\nEntscheidungen im Prozess getroffen werden.",[12,140,141,142,147,148,153,154,159],{},"Der Agent braucht Kontext, um Änderungen zu produzieren, denen die Organisation\nvertrauen kann – und dieser Kontext lebt in der DevSecOps-Plattform. Der\nIssue-Tracker listet Anforderungen auf. Die\n",[38,143,146],{"href":144,"rel":145},"https://docs.gitlab.com/topics/build_your_application/",[],"CI/CD-Konfiguration","\nsetzt den Qualitätsstandard. ",[38,149,152],{"href":150,"rel":151},"https://docs.gitlab.com/development/code_review/",[],"Code-Review-Anweisungen","\nkodifizieren Style und Standards des Teams.\n",[38,155,158],{"href":156,"rel":157},"https://docs.gitlab.com/user/application_security/detect/",[],"Security-Scanner","\nsetzen Schwachstellen-Richtlinien durch. Und der Merge Request ist der Ort, wo\nalles zusammenkommt – das finale menschliche Gate.",[12,161,162],{},[66,163],{"alt":152,"src":164},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986319/iq9yeutzn7qqzyl3wckf.png",[12,166,167],{},"Ein Agent mit Plattform-Kontext folgt demselben Workflow, den Entwicklungsteams\nverwenden – und innerhalb derselben Leitplanken. Der Unterschied zeigt sich in\nReview-Zyklen, Pipeline-Erfolgsquoten und Zeit bis zum Merge.",[12,169,170],{},"Ein IDE- oder Terminal-basierter Agent, so leistungsfähig er auch sein mag,\nsieht nur die Dateien, die ihm übergeben werden. Die Plattform hat Zugriff auf\nden vollständigen Lifecycle: vom Issue, der Pipeline und der Security-Policy\nbis zum Deployment-Ziel und den Freigabe-Regeln. Diese Sichtbarkeitslücke ist\nder Grund, warum die Plattform – nicht der Agent – bestimmt, was sicher\nausgeliefert wird.",[30,172,174],{"id":173},"die-auswirkungen-auf-die-sicherheit-wenn-agenten-mehr-code-produzieren","Die Auswirkungen auf die Sicherheit, wenn Agenten mehr Code produzieren",[12,176,177],{},"In allen Tutorials laufen CI/CD-Pipelines und Code-Review automatisch bei\njedem Merge Request, den der Coding-Agent erstellt. Security Scanning ist Teil\nder Pipelines, auch wenn die Tutorials sich auf Code-Qualität und nicht auf\nSecurity-Findings konzentrieren. Für Platform-Teams wird Kontext noch\nentscheidender, wenn Security im Spiel ist.",[12,179,180],{},"Coding-Agenten produzieren mehr Code, schneller. Mehr Code bedeutet mehr\neingeführte Schwachstellen, mehr von Scannern markierte Findings und mehr\nFix-MRs.",[182,183,184,191],"ul",{},[185,186,187,190],"li",{},[59,188,189],{},"Früher:"," Vor dem Einzug von KI-Coding-Agenten in den Workflow lag der Engpass\nauf der Seite derApplication-Security: scannen, Findings priorisieren, wichtige\nan Entwickler eskalieren, auf einen Fix warten.",[185,192,193,196],{},[59,194,195],{},"Heute:"," Dank Agenten, die Code-Produktion und Remediation beschleunigen,\nverschiebt sich der Engpass. Der Workflow entwickelt sich weiter von „Welche\nSchwachstelle sollten wir zuerst beheben?\" zu „Welchen KI-generierten Fix-MR\nsollte ein Mensch zuerst prüfen und freigeben?\"",[12,198,199],{},"Diese Entscheidung erfordert Kontext, den der Coding-Agent nicht hat: den\numgebenden Projektcode, den vollständigen Datenfluss, das Deployment-Ziel und\ndie Security-Policies, die über die gesamte Organisation gelten.",[182,201,202],{},[185,203,204,207],{},[59,205,206],{},"Mit Kontext"," schärft sich die Priorisierung: Ein Agent, der im umgebenden\nCode, Datenfluss und anwendbaren Policies verankert ist, kann Findings nach\nrealer Exposition in der eigenen Umgebung einordnen – statt nach generischen\nSchweregrad-Scores – und zeigt, was wichtig ist, bevor Reviewer Zyklen darauf\nverwenden.",[12,209,210],{},"Genau wie der Coding-Agent im zweiten Szenario besseren Code produzierte, als\ner das GitLab-Issue lesen konnte, liefert die Security-Schicht bessere\nBewertungen, wenn sie den vollständigen Anwendungskontext lesen kann statt\neiner einzelnen Datei.",[12,212,213,214,219,220,225],{},"GitLabs Security-Schicht analysiert Findings mit vollständigem Projektkontext,\n",[38,215,218],{"href":216,"rel":217},"https://docs.gitlab.com/user/application_security/vulnerabilities/false_positive_detection/",[],"filtert erkannte False Positives","\nund markiert bestätigte Schwachstellen. Wenn eine Schwachstelle bestätigt ist,\nliest die\n",[38,221,224],{"href":222,"rel":223},"https://docs.gitlab.com/user/application_security/vulnerabilities/agentic_vulnerability_resolution/",[],"agentische SAST-Schwachstellenbehebung","\nden verwundbaren Code und umgebenden Kontext aus dem Repository und erstellt\nautomatisch einen Merge Request mit einem vorgeschlagenen Fix. Die Pipeline\nläuft zur Validierung. Ein Reviewer prüft und trifft die finale Merge-Entscheidung.\nDer Agent übernimmt die Remediation – das Governance-Modell bleibt intakt.",[12,227,228,229],{},"CI/CD-Quality-Gates, Code-Review-Anweisungen und Security Scanning laufen alle\nim Merge Request – und dort arbeiten Coding-Agenten. ",[59,230,231],{},"Je effektiver diese\nKontrollen am Punkt der Code-Erstellung sind, desto weniger Schwachstellen\nerreichen die Produktion.",[30,233,235,236],{"id":234},"benutzerdefinierte-anweisungen-mit-agentsmd","Benutzerdefinierte Anweisungen mit ",[81,237,238],{},"AGENTS.md",[12,240,241,242,244,245,250],{},"Beide Tutorials nutzen ",[81,243,238],{},"-Dateien im Repository. Das sind\n",[38,246,249],{"href":247,"rel":248},"https://docs.gitlab.com/user/duo_agent_platform/customize/agents_md/",[],"benutzerdefinierte Anweisungen","\nfür Agenten: wie das Projekt strukturiert ist, welche Befehle ausgeführt werden\nsollen und wie die Code-Qualitätsanforderungen aussehen – einschließlich was\nnicht angefasst werden soll.",[12,252,253,254,256],{},"Im Codex-und-GitLab-Tutorial definierte die ",[81,255,238],{},"-Datei alles von der\nRust-Edition bis zum asynchronen Nebenläufigkeitsmuster und der\nCI-Image-Pinning-Policy. Der Agent brauchte keinen im Prompt wiederholten\nKontext. Er las die Datei und folgte den Regeln.",[12,258,259],{},[66,260],{"alt":261,"src":262},"Lokales Toolchain-Setup","https://res.cloudinary.com/about-gitlab-com/image/upload/v1779986319/bciynqcmc1gumgcx4mjo.png",[12,264,265,266,268],{},"Diese einmalige Investition zahlt sich bei jeder Agenten-Interaktion aus –\nob der Agent lokal im Terminal läuft, via MCP verbunden ist oder als externer\nAgent innerhalb eines Merge Requests arbeitet. Die Standardisierung von\n",[81,267,238],{}," über Projekte hinweg verbessert die Qualität der Agenten-Ausgaben,\nda jede Agenten-Session – lokal oder remote – dieselben Regeln liest.",[30,270,272],{"id":271},"grenzen-des-kontextfensters","Grenzen des Kontextfensters",[12,274,275,276,281],{},"Große Sprachmodelle haben begrenzte Kontextfenster, und Forschungsergebnisse\nzeigen, dass die\n",[38,277,280],{"href":278,"rel":279},"https://vercel.com/blog/we-removed-80-percent-of-our-agents-tools",[],"Modellleistung abnimmt, wenn die Kontextauslastung 30–40 % übersteigt",".\nJe mehr Werkzeuge, Dateien und Anweisungen in eine Session gepackt werden,\ndesto weniger zuverlässig reasoning der Agent.",[12,283,284],{},"Reichhaltiger Lifecycle-Kontext ist wertvoll: Issue, Review-Anweisungen,\nPipeline-Historie und Security-Policy. Entscheidend ist aber, dass dieser\nKontext strukturiert, relevant und effizient bereitgestellt wird.",[12,286,287],{},"Statt jede Agenten-Session Kontext von Grund auf rekonstruieren zu lassen –\ndurch das Lesen von Dateien und unnötige API-Aufrufe, die das Kontextfenster\nverwässern und Token verbrauchen –, kann eine Plattform, die die Beziehungen\nzwischen Code, Issues, Pipelines und Deployments versteht, den richtigen\nKontext zum richtigen Zeitpunkt liefern. GitLab erfasst viele dieser Beziehungen\nüber den gesamten Lifecycle und ist damit in der Position, Kontext strukturierter\nbereitzustellen. Wenn die Plattform weiß, welches Issue ein Merge Request\nadressiert, welche Services eine Code-Änderung betrifft und welche Pipelines\ndas Ergebnis validieren, kann sie dieses Wissen als strukturierten Kontext\nliefern – statt es aus Fragmenten zusammenzusetzen.",[12,289,290],{},"Die Effizienz KI-gestützter Entwicklungsworkflows hängt davon ab, wie gut die\nPlattform strukturierten Kontext liefert – nicht von der Größe des\nModell-Kontextfensters.",[30,292,294],{"id":293},"agenten-verkürzen-den-loop","Agenten verkürzen den Loop",[12,296,297],{},"Wenn ein Coding-Agent Review-Feedback innerhalb eines Merge Requests adressiert,\nhandelt er auf das Review hin. Der Agent liest das Feedback, nimmt die\ngewünschten Änderungen vor, committed sie und lässt CI/CD das Ergebnis\nvalidieren. Der Reviewer prüft das Ergebnis, genehmigt oder fordert weitere\nÄnderungen und trifft die finale Merge-Entscheidung.",[12,299,300],{},"Freigabe-Regeln, Code-Owner, Security-Policies und Audit-Trails bleiben alle\nerhalten. Der Agent beschleunigt den Revisions-Zyklus, ohne die Kontrollen\ndrumherum zu umgehen.",[12,302,303,304,308,309,314,315,320],{},"Externe Agenten in\n",[38,305,307],{"href":113,"rel":306},[],"GitLab Duo Agent Platform","\nlassen sich über\n",[38,310,313],{"href":311,"rel":312},"https://docs.gitlab.com/user/duo_agent_platform/triggers/",[],"Event-Trigger","\nund\n",[38,316,319],{"href":317,"rel":318},"https://docs.gitlab.com/user/duo_agent_platform/flows/custom/",[],"Custom Flows","\nweiter integrieren und geben Platform-Teams Kontrolle darüber, wann und wie\nAgenten im Workflow agieren.",[30,322,324],{"id":323},"erste-schritte-mit-agentischem-coding","Erste Schritte mit agentischem Coding",[12,326,327],{},"Wer evaluiert, wie Coding-Agenten in den Entwicklungsworkflow der Organisation\npassen:",[12,329,330,333],{},[59,331,332],{},"Einen sichtbaren Bug in einem echten Projekt wählen:"," Das erwartete Verhalten\nin einem GitLab-Issue mit klaren Anforderungen definieren. Dieselbe Progression\nwie in den Tutorials durchlaufen: lokal mit dem Agenten aus dem Repository\nbeheben, GitLab MCP verbinden, damit der Agent vom Issue aus arbeitet, und den\nAgenten als externen Reviewer einsetzen, um Feedback im Merge Request zu\nadressieren.",[12,335,336,342],{},[59,337,338,339,341],{},"In ",[81,340,238],{}," investieren:"," Dokumentieren, wie das Repository funktioniert,\nwelche Befehle relevant sind und wie die Code-Qualitätsanforderungen aussehen.\nDiese Anweisungen sorgen für höhere Qualität der Agenten-Ausgaben, die sich\nüber Zeit summiert, je mehr Agenten und Entwickler mit dem Projekt interagieren.",[12,344,345,348],{},[59,346,347],{},"Kontextverbrauch beobachten:"," Wenn Agenten-Sessions langsam, teuer oder\noberflächlich sind, liegt das Problem wahrscheinlich am bereitgestellten\nKontext – nicht am Modell selbst. Strukturierter, relevanter Kontext über\nPlattform-Integrationen schlägt rohe Datei-Dumps.",[12,350,351,354,355,360,361,366],{},[59,352,353],{},"Security-Abdeckung prüfen:"," Mit steigender Anzahl von Merge Requests durch\nCoding-Agenten über Projekte hinweg sicherstellen, dass jedes Projekt gescannt\nwird.\n",[38,356,359],{"href":357,"rel":358},"https://docs.gitlab.com/user/application_security/configuration/security_configuration_profiles/",[],"Security Configuration Profiles","\nauf Group-Ebene anwenden, damit Scanner automatisch aktiviert sind, dann mit\ndem\n",[38,362,365],{"href":363,"rel":364},"https://docs.gitlab.com/user/application_security/security_inventory/",[],"Security Inventory","\ndie Abdeckung bestätigen und verstehen, wo sich Schwachstellen konzentrieren.",[30,368,370],{"id":369},"jetzt-mit-agentischem-coding-loslegen","Jetzt mit agentischem Coding loslegen",[12,372,373],{},"Die Organisationen, die das Meiste aus agentischem Coding herausholen, werden\ndiejenigen sein, die über DevSecOps-Plattformen verfügen, die Agenten den\nrichtigen Kontext und die richtigen Kontrollen geben, um sicher auszuliefern.",[12,375,376,377,382],{},"GitLab Duo Agent Platform noch nicht im Einsatz? Mit einer\n",[38,378,381],{"href":379,"rel":380},"https://about.gitlab.com/de-de/gitlab-duo-agent-platform/",[],"kostenlosen Testversion","\nstarten.",[12,384,385,386,391],{},"Wer GitLab bereits im Free Tier nutzt, kann GitLab Duo Agent Platform in\n",[38,387,390],{"href":388,"rel":389},"https://docs.gitlab.com/subscriptions/gitlab_credits/#for-the-free-tier-on-gitlabcom",[],"wenigen einfachen Schritten","\neinrichten.",[12,393,394,395,400,401,406],{},"Für bestehende GitLab Premium- oder Ultimate-Abonnenten genügt es,\n",[38,396,399],{"href":397,"rel":398},"https://docs.gitlab.com/user/duo_agent_platform/turn_on_off/",[],"Duo Agent Platform zu aktivieren","\nund die\n",[38,402,405],{"href":403,"rel":404},"https://docs.gitlab.com/subscriptions/gitlab_credits/#included-credits",[],"enthaltenen GitLab-Promotional-Credits","\nzu nutzen.",{"title":408,"searchDepth":409,"depth":409,"links":410},"",2,[411,412,413,414,416,417,418,419],{"id":32,"depth":409,"text":33},{"id":134,"depth":409,"text":135},{"id":173,"depth":409,"text":174},{"id":234,"depth":409,"text":415},"Benutzerdefinierte Anweisungen mit AGENTS.md",{"id":271,"depth":409,"text":272},{"id":293,"depth":409,"text":294},{"id":323,"depth":409,"text":324},{"id":369,"depth":409,"text":370},"ai","2026-05-28","Coding-Agenten liefern Geschwindigkeit. 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Finde heraus, was das für dich bedeutet.",{"text":1189,"config":1190},"Erfahre, wie GitLab im Vergleich zu GitHub abschneidet",{"href":1191,"dataGaName":1192,"dataGaLocation":651},"/de-de/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":1194},{"src":1168},{"header":1196,"blurb":1197,"button":1198,"secondaryButton":1203},"Beginne noch heute, schneller zu entwickeln","Entdecke, was dein Team mit der intelligenten Orchestrierungsplattform für DevSecOps erreichen kann.\n",{"text":1199,"config":1200},"Kostenlosen Test starten",{"href":1201,"dataGaName":449,"dataGaLocation":1202},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/de-de/","feature",{"text":451,"config":1204},{"href":453,"dataGaName":454,"dataGaLocation":1202},1781392676122]