DevOps as a Service

One GitHub issue in → a tested pull request out — and when an issue is destructive, the agents stop and ask a human instead. Small engineering teams — two to ten developers, like the five-engineer shop this entry is built for — lose a senior engineer's hour or more to every small, well-defined backlog fix, so the small stuff waits for weeks. DevOps as a Service clears that backlog: file the issue, and a multi-agent workflow returns a reviewed, tested pull request. Measured, not asserted: on the seeded eval set, timed live runs through the Meta Model API passed 3/3 tiers (tests 6 → 9, 6 → 10, 6 → 8) in 94.65s total pipeline wall clock, against a 60-minute manual floor per issue, and live runs opened PRs #16, #17, and #18. The result repeats: the combined live record across three attempts per issue is 9/9 work tiers, and the pipeline also passed live on three unseen codebases (ledgerlite, tests 9 → 13; textkit, tests 10 → 15; gradebook, tests 12 → 18). The seeded bench is now 12 seeded issues — the full researched DevOps/SRE scenario spec — and the whole bench passed in one direct-pipeline session under the all-frontier contest configuration: 12/12 passed, guardrail escalated, growth +42, 433.47s, est. $0.3910 total ($0.0326 per passed issue), muse-wonder-1.0 on every call, fallbacks 0, retries 0. A deterministic guardrail runs before any model call; models never decide safety. Approve-and-resume: validated human decisions; reject / handle-manually close with zero model calls; re-scope is the only resumable path and re-runs the guardrail. Three deterministic gates (plan gate, regression gate, issue-target gate) were each built from a measured live failure, and those failures are recorded in the repo, not hidden. Demo video: a live Judge Mode Tier 1 run under the all-frontier contest configuration (tests 24 → 25 in 34.2s) plus a live guardrail escalation, captioned, with narration, 2:45 at 1080p. Live PRs: https://github.com/josephbolus/devops-as-a-service/pull/16, /pull/17, /pull/18. Eval scorecard: eval-scorecard/SCORECARD.md in the repo.