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Pipeline Status
๐Ÿ”ด Failing
Success Rate (7d)
77.8%
Builds (7d)
54
Median Duration
31m
P95: 44m
DORA Level
High
Deployment Frequency
10.4 / week
elite
How often builds are deployed. Elite: >7ร—/week, High: 1โ€“7ร—/week, Medium: monthly, Low: less than monthly.
Lead Time
33m
elite
Time from commit to production. Elite: <1h, High: <1d, Medium: <1wk, Low: >1wk.
Change Failure Rate
6.1%
high
Percentage of deployments causing a failure. Elite: <5%, High: <10%, Medium: <15%, Low: โ‰ฅ15%.
MTTR
81.1h
medium
Mean time to restore service after a failure. Elite: <1h, High: <1d, Medium: <1wk, Low: >1wk.

Monthly Overview

Success Rate (MoM)
92.8%
โ–ผ -2.3% vs prior month
Total Builds (MoM)
349
โ–ฒ +55 vs prior month
Avg Duration (MoM)
26.2 min
โ–ฒ +5.7 min vs prior month
DORA Level
Medium
This month

Monthly Overview

Monthly Build Outcomes
Monthly Build Duration
Monthly Success Rate by Repo
DORA Level Trend
Build Success Rate
Daily Build Outcomes
Build Duration Trends
Avg Duration by Repo
Failure Category Breakdown
MTTR
81.1h
Mean Time to Recovery
MTBF
15.6h
Mean Time Between Failures
Flakiness Leaderboard โ€” Top 10 Flaky Jobs
# Job Name Repo Runs Failures Failure Rate Flakiness Index Last Failure Top Failing Step
1 Build Beta Images (aurora) / image (nviโ€ฆ aurora 118 61 5169.5%
0.407
4mo ago Build Image
2 Build Beta Images (aurora) / image (nviโ€ฆ aurora 118 63 5339.0%
0.395
4mo ago Build Image
3 Build Beta Images (aurora) / Check all โ€ฆ aurora 118 63 5339.0%
0.395
4mo ago Check Jobs
4 Build Beta Images (aurora) / image (maiโ€ฆ aurora 118 37 3135.6%
0.282
4mo ago Build Image
5 Build Beta Images (aurora) / image (maiโ€ฆ aurora 118 35 2966.1%
0.260
4mo ago Build Image
6 Build Stable ISOs / Build ISOs (amd64, โ€ฆ iso 115 34 2956.5%
0.259
6d ago Push ISO to GHCR via ORAS
7 Build Stable ISOs / Build ISOs (amd64, โ€ฆ iso 115 36 3130.4%
0.252
6d ago Build ISO
8 Build Stable Images (aurora) / image (mโ€ฆ aurora 461 88 1908.9%
0.251
3mo ago Build Image
9 Build Stable Images (aurora) / image (nโ€ฆ aurora 461 90 1952.3%
0.251
3mo ago Build Image
10 Build Stable Images (aurora) / Check alโ€ฆ aurora 734 151 2057.2%
0.250
1mo ago Check Jobs

OpenSSF Scorecard

Scores from OpenSSF Scorecard. Click a card to view the full report.

Builds Per Day
Avg Queue Wait Time
Build Trigger Breakdown
Builder Comparison โ€” All Repos
Repo Success Rate 7d Success Rate 30d Avg Duration Total Runs (7d) Last Stream Status
aurora 75.6% 89.7% 32m 41 ๐ŸŸข success
common 100.0% 97.4% 2m 6 ๐ŸŸข success
iso 71.4% 82.9% 24m 7 ๐ŸŸข success

Stream Health

Repo Stream 7d Rate 30d Rate Runs (7d) Avg Duration Last Run Status
aurora build-image-beta 0.0% 0.0% 0 30m 149d ago ๐ŸŸข
build-image-latest-main 79.2% 90.6% 24 32m <1h ago ๐ŸŸข
build-image-stable 70.6% 88.5% 17 32m <1h ago ๐ŸŸข
common build 100.0% 97.4% 6 2m 12h ago ๐ŸŸข
iso build-iso-stable 71.4% 82.9% 7 24m 5d ago ๐ŸŸข

Architecture Comparison

amd64
55.6%
7d success rate
26mavg duration18jobs (7d)
iso55.6%
x86_64
72.1%
7d success rate
20mavg duration172jobs (7d)
aurora72.1%
Publish Reliability
Repos at Full Coverage
1/3
โ‰ฅ95% success rate (7d)
Overall 7d Success Rate
82.3%
Avg across all repos
Repos with Recent Activity
3/3
Total runs > 0 (7d)

Publish step tracking requires live build data โ€” shown after first successful CI run.

Supply Chain Security

aurora
Cosign Signing
100.0%
30d success rate
SBOM Coverage
97.7%
30d success rate
common
Cosign Signing
100.0%
30d success rate
SBOM Coverage
0.0%
30d success rate
iso
Cosign Signing
100.0%
30d success rate
SBOM Coverage
100.0%
30d success rate

Rates computed from workflow step names over last 30 days. Steps not detected in pipeline are shown as โ€”.

Recent Builds
Repo Workflow Branch Trigger Duration Started Jobs
๐ŸŸข aurora Latest Images backport-2923-to-stable-f44 PR 28m 2026-09-24T05:49:41Z 6/6 โœ“
๐ŸŸข aurora Stable Images backport-2923-to-stable-f44 PR 29m 2026-09-24T05:49:41Z 6/6 โœ“
๐ŸŸข aurora Latest Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 26m 2026-09-24T03:51:03Z 6/6 โœ“
๐ŸŸข aurora Stable Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 30m 2026-09-24T03:51:03Z 6/6 โœ“
๐ŸŸข common Build gh-readonly-queue/main/pr-276-1432d9b3e8c2420bcb02f601754d0d676e90e59f other <1m 2026-09-23T18:33:46Z 1/1 โœ“
๐Ÿ”ด aurora Latest Images backport-2906-to-stable-f44 PR 14m 2026-09-23T05:50:15Z 1/6 โœ—
๐Ÿ”ด aurora Stable Images backport-2906-to-stable-f44 PR 13m 2026-09-23T05:50:15Z 1/6 โœ—
๐ŸŸข aurora Latest Images stable-f44 push 42m 2026-09-23T05:14:32Z 6/6 โœ“
๐ŸŸข aurora Latest Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 86m 2026-09-23T03:49:42Z 6/6 โœ“
๐ŸŸข aurora Stable Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 72m 2026-09-23T03:49:42Z 6/6 โœ“
๐ŸŸข aurora Latest Images stable-f44 push 30m 2026-09-22T07:50:37Z 6/6 โœ“
๐ŸŸข aurora Latest Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 30m 2026-09-22T07:13:05Z 6/6 โœ“
๐ŸŸข aurora Stable Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 39m 2026-09-22T07:13:38Z 6/6 โœ“
๐ŸŸข aurora Stable Images stable-f44 dispatch 47m 2026-09-22T01:20:12Z 6/6 โœ“
๐ŸŸข aurora Latest Images stable-f44 push 27m 2026-09-21T04:23:09Z 6/6 โœ“
๐ŸŸข aurora Latest Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 33m 2026-09-21T03:51:51Z 6/6 โœ“
๐ŸŸข aurora Stable Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 28m 2026-09-21T03:51:51Z 6/6 โœ“
๐ŸŸข aurora Latest Images stable-f44 push 35m 2026-09-20T07:51:22Z 6/6 โœ“
๐ŸŸข aurora Latest Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 27m 2026-09-20T07:23:04Z 6/6 โœ“
๐ŸŸข aurora Stable Images renovate/stable-f44-quay.io-fedora-ostree-desktops-kinoite-44 PR 31m 2026-09-20T07:23:04Z 6/6 โœ“

Further Reading

The metrics on this page are grounded in peer-reviewed research and open standards. These resources explain what each metric means, why it predicts software delivery performance, and how to improve it.

Software Delivery Performance
DORA Metrics โ€” Four Keys

The canonical framework for measuring software delivery: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service. Published by Google Cloud's DevOps Research and Assessment team and validated across thousands of organizations since 2014.

Supply Chain Security
OpenSSF Scorecard

Automated security health checks for open source projects, scoring 0โ€“10 across checks including signed releases, SBOM presence, branch protection, pinned dependencies, and CI test coverage. Produced by the Open Source Security Foundation (OpenSSF), a Linux Foundation project.

Supply Chain Security
SLSA โ€” Supply-chain Levels for Software Artifacts

A graduated framework (L0โ€“L3) for verifiable software build integrity. Each level adds stronger guarantees: L1 means provenance exists, L2 means it is signed by a hosted build platform, L3 means the build environment itself is hardened and isolated. Developed by Google and adopted as an OpenSSF standard.

Supply Chain Security
Sigstore / Cosign

Keyless, identity-based artifact signing backed by a public transparency log (Rekor). Cosign signs and verifies container images and release artifacts using short-lived OIDC certificates โ€” no long-lived private keys to manage or rotate. A CNCF project used by Kubernetes, Tekton, and the Bluefin image pipeline.

Supply Chain Security
SBOM โ€” Software Bill of Materials

A machine-readable inventory of every component and dependency in a software artifact. SBOMs make vulnerability response faster โ€” when a new CVE is published, you can immediately know which of your images are affected. The OpenSSF SBOM Everywhere SIG maintains tooling guidance and naming conventions.

Supply Chain Security
CNCF TAG Security โ€” Supply Chain Best Practices

The CNCF Technical Advisory Group for Security publishes authoritative whitepapers on cloud-native supply chain security. The Software Supply Chain Best Practices paper (v2, 2025) and the Secure Software Factory reference architecture define the practices that the Scorecard and SLSA checks encode.

Platform Engineering
CNCF Platforms White Paper

The authoritative CNCF definition of what internal developer platforms are, what they should measure (user satisfaction, self-service rate, onboarding time), and how platform teams should operate. Published by the TAG App Delivery Platforms Working Group. Recommends DORA metrics as the delivery measurement standard for platform teams.

Platform Engineering
Platform Engineering Maturity Model

A 4-level model (Provisional โ†’ Operational โ†’ Scalable โ†’ Optimizing) across five aspects: Investment, Adoption, Interfaces, Operations, and Measurement. Helps platform teams understand where they are and what practices characterize the next level. Published by the CNCF TAG App Delivery Platforms Working Group.

Platform Engineering
Cloud Native Maturity Model

A 5-level model (Build โ†’ Operate โ†’ Scale โ†’ Improve โ†’ Adapt) across Business Outcomes, People, Process, Policy, and Technology. Maintained by the CNCF Cartografos Working Group. Version 4 (2025) adds AI and FinOps dimensions. Useful for understanding where cloud-native adoption fits in the broader organizational journey.

Research
Accelerate โ€” The Science of Lean Software and DevOps

The peer-reviewed research behind DORA metrics. Nicole Forsgren, Jez Humble, and Gene Kim identified 24 technical, process, and cultural capabilities that predict software delivery performance and organizational outcomes. Required reading for understanding why deployment frequency and lead time matter.

Research
SRE Golden Signals

Google's Site Reliability Engineering book defines four signals sufficient to monitor any user-facing service: Latency, Traffic, Errors, and Saturation. These are the production observability complement to DORA โ€” they define what a "failure" actually is (without them, Change Failure Rate cannot be accurately measured) and predict when MTTR will spike before incidents occur.

Research
SPACE Framework โ€” Developer Productivity

DORA measures what the pipeline does; SPACE measures how developers experience it. Developed by Nicole Forsgren (GitHub), Margaret-Anne Storey, and colleagues at Microsoft Research. Five dimensions: Satisfaction, Performance, Activity, Communication/Collaboration, and Efficiency. Never measure activity in isolation.