1import{_ as a}from"./Bb4eqU7i.js";import{u as n}from"./DYGLacVr.js";import{e as r,o as t,q as s}from"./DlpDSASA.js";const g=r({__name:"CortexComparisonFaqSection",setup(i){const e=[{question:"Is Oobeya an alternative to Cortex?",answer:"Yes. Oobeya can be evaluated as a Cortex alternative when organizations need SDLC analytics, engineering intelligence, AI-assisted insights, reporting, and deployment control beyond service catalog and scorecard workflows."},{question:"Where can Cortex fit well?",answer:"Cortex may fit well for teams focused on service catalog ownership, scorecards, developer portal workflows, standards tracking, and engineering operations programs."},{question:"How is Oobeya different from a developer portal?",answer:"Oobeya focuses on engineering intelligence across delivery, quality, security, testing, workflow, AI adoption, and leadership reporting rather than primarily cataloging services and ownership metadata."},{question:"Can Oobeya use data from multiple engineering tools?",answer:"Yes. Oobeya connects data from source control, CI/CD, project management, code quality, testing, security, and related systems to create a broader SDLC operating view."},{question:"Which should engineering leaders choose?",answer:"Choose Cortex when service catalog and scorecard governance are the primary need. Choose Oobeya when leaders need SDLC-wide measurement, AI insights, reporting, and enterprise deployment flexibility."}];return n(e),(c,l)=>{const o=a;return t(),s(o,{"comparison-name":"Oobeya vs Cortex",items:e})}}});export{g as default};
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.