Serverless Engineering Benchmarks
Serverless delivery benchmarks are based on 2 merged pull requests in the last 30 days (26 all-time), with 9.3 hours median cycle time, 5.7 hours median review time, and 2 active contributors. AI-related signals appear on 0.0% of recent work.
Median Cycle Time
9.3h
PR open to merge
Median Review Time
5.7h
first review to approval
AI-Related Signals
0.0%
directional signal across recent PRs
Best Signal
Fast Delivery
9.3h
Median cycle time of 9.3h
Repo vs Neon Average
0.0pp
AI Signals
-9.4h
Cycle Time
+3.3h
Review Time
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Cycle Time by AI-Related Signals
55.3h
baseline
PR Breakdown
0 with signals /
3 total PRs
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| Migrate CI to IaC-managed runners | Shugenya | — |
| Stop publishing to JSR, update release process, update some… | jawj | — |
| http connection parameters | jawj | — |
| Support connection parameters in `neon()` function | jawj | — |
| Update release scripts and instructions and add type shims … | jawj | — |
Methodology
Metrics are computed from merged pull request data synced daily from GitHub. AI-related metrics are directional signals inferred from pull request activity patterns and heuristics. Summary metrics use a 30-day rolling window; trends use a 90-day window. Last updated 4 hours, 33 minutes ago.
Updated daily from public GitHub pull requests.
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