Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-12 14:50 UTC

redhat-performance / cloud-governance

The Next generation of cloud management and security

PythonApache-2.0★ 18 stars⑂ 19 forkssince Dec 2020View on GitHub ↗

redhat-performance/cloud-governance holds a health index of 80 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (89/100) and lowest on Security (52/100). It was last updated today. A single contributor accounts for most of its recent work.

80
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

80
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02).

Ownership

216 followers138 public repossince Jun 2015

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIcloud-governance1.1.4794,4769030 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

70Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
25.6/36Commit cadence — 37/52 weeks with commits
18/18Commit volume — 201 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year201
human_commit_share0.54
days_since_last_push0
active_weeks_last_year37
How it's scored
27/27Ships releases — 1 releases published
0/36Release recency — latest release 1,475 days ago
12.6/27Release cadence — cadence unknown (single release)
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count1
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release1,475
mean_days_between_releases—

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

55Moderate · 17% of overall
How it's scored
20/60Stars — 18 stars
10.5/25Forks — 19 forks
2.7/15Watchers — 4 watchers
Inputs used
forks19
stars18
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescoveralls.io, github.com, readthedocs.org, shields.io
has_pull_request_templateyes
How it's scored
48.7/80Monthly downloads — 4,476 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagescloud-governance
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,476
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

69Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
6.3/22.5Commit distribution — top contributor authored 72% of commits
13.5/13.5Contributor breadth — 11 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled11
top_contributor_share0.721
How it's scored
31.8/42Issue resolution — 76% of issues closed
28.5/30PR acceptance — 952/1,002 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs952
open_issues9
closed_issues28
prs_merged_7d3
prs_decided_7d3
prs_merged_30d10
prs_decided_30d10
issue_closed_ratio0.757
closed_unmerged_prs50
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
16.8/25Owner reach — 216 followers of redhat-performance
25/25Track record — 138 public repos, account ~11 yr old
Inputs used
followers216
owner_typeOrganization
is_verifiedno
owner_loginredhat-performance
public_repos138
account_age_days4,149

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 903 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescloud-governance
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

89Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 2 topics
10/10Wiki
Inputs used
topicscloud-governance, openshift
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

52Moderate · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestscloud-governance-mcp/requirements.txt, cloudsensei/requirements.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyyes
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories68
affected_packages5
assessed_packages44
unassessed_packages21
affected_by_severitycritical 1, high 1, moderate 3
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 44 resolved dependencies against OSV. 21 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

70Good · 4% of overall
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 50 of 54 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.926
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes8,520
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
10/10Demonstrated agent practice — 41 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.41
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
54.9/55Manageable file sizes — 1/495 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes65,325
source_files_sampled495
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

18GitHub stars
11contributors
201commits, last 12 months
0days since last push
1releases
1bus factor
9open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:cloud-governance@1.1.479; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 19 ⇿
0Stars
19Forks
1Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

0481216201922021-062023-092025-12
Major 0Minor 1Patch 0

Each point covers 5 days.

All dependencies 65

Full resolved dependency set from the GitHub dependency graph: 0 direct and 65 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp3.13.3indirect
PyPIattrs21.4.0indirect
PyPIazure-functions—indirect
PyPIazure-identity—indirect
PyPIazure-identity1.16.1indirect
PyPIazure-mgmt-billing6.0.0indirect
PyPIazure-mgmt-compute—indirect
PyPIazure-mgmt-compute30.1.0indirect
PyPIazure-mgmt-costmanagement3.0.0indirect
PyPIazure-mgmt-monitor6.0.2indirect
PyPIazure-mgmt-network25.0.0indirect
PyPIazure-mgmt-resource23.0.1indirect
PyPIazure-mgmt-subscription3.1.1indirect
PyPIboto31.26.1indirect
PyPIboto31.42.89indirect
PyPIbotocore1.42.89indirect
PyPIcoverage—indirect
PyPIelasticsearch—indirect
PyPIelasticsearch7.11.0indirect
PyPIelasticsearch8.17.0indirect
PyPIfreezegun1.5.1indirect
PyPIgoogle-api-python-client2.57.0indirect
PyPIgoogle-auth-httplib20.1.0indirect
PyPIgoogle-auth-oauthlib0.5.2indirect
PyPIgoogle-cloud-bigquery3.41.0indirect
PyPIgoogle-cloud-billing1.19.0indirect
PyPIgoogle-genai—indirect
PyPIibm-cloud-sdk-core3.24.4indirect
PyPIibm-cos-sdk2.16.1indirect
PyPIibm-platform-services0.75.0indirect
PyPIibm-schematics1.0.1indirect
PyPIibm-vpc0.33.0indirect
PyPIjinja23.1.5indirect
PyPIjira—indirect
PyPImcp—indirect
PyPImoto5.1.22indirect
PyPImyst-parser1.0.0indirect
PyPInest-asyncio—indirect
PyPInumpy—indirect
PyPIoauthlib—indirect
PyPIopensearch-py—indirect
PyPIopensearch-py3.2.0indirect
PyPIpandas—indirect
PyPIpre-commit3.5.0indirect
PyPIprotobuf5.29.6indirect
PyPIpyathena3.0.5indirect
PyPIpygithub1.55indirect
PyPIpytest—indirect
PyPIpytest-runner—indirect
PyPIpython-dotenv—indirect
PyPIpython-ldap3.4.2indirect
PyPIpytz—indirect
PyPIrequests—indirect
PyPIrequests2.32.2indirect
PyPIrequests2.33.1indirect
PyPIretry0.9.2indirect
PyPIsetuptools—indirect
PyPIsoftlayer6.0.0indirect
PyPIsphinx5.0.0indirect
PyPIsphinx-rtd-theme1.0.0indirect
PyPIstreamlit—indirect
PyPItypeguard2.13.3indirect
PyPItyping3.7.4.3indirect
PyPIurllib32.6.3indirect
PyPIwheel—indirect
Dependency advisories 5

This repository publishes no package the index resolves, so its own dependency graph was assessed — 44 packages, which also include development and test pins that never ship: 5 carry known advisories, of which 0 are direct. 21 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
aiohttp3.13.3indirectcritical483.14.3
urllib32.6.3indirecthigh102.8.0
jinja23.1.5indirectmoderate23.1.6
python-ldap3.4.2indirectmoderate43.4.5
requests2.32.2indirectmoderate42.33.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.