Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 02:02 UTC

datadog / datadog-lambda-python

The Datadog AWS Lambda Layer for Python

Python · ShellApache-2.0★ 101 stars⑂ 51 forkssince Apr 2019View on GitHub ↗
KindLibraryhow this is determined

datadog/datadog-lambda-python holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Vitality (93/100) and lowest on AI Readiness (34/100). It was last updated 3 days ago. 5 contributors account for most of its recent work.

90
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.

90
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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

Datadog, Inc.Organization
3,222 followers1,194 public repossince Aug 2010

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdatadog_lambda8.126.0-1193 days agodatadogawslambdalayer

Metrics by category

Vitality

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

93Exceptional · 21% of overall

Development activity

95Exceptional
How it's scored
36/36Push recency — last push 3 days ago
31.2/36Commit cadence — 45/52 weeks with commits
18/18Commit volume — 139 commits in the last year
10/10OpenSSF Scorecard: Maintained — 25 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year139
human_commit_share—
days_since_last_push3
active_weeks_last_year45

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 3 days ago
27/27Release cadence — a release every ~27.2 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv8.126.0
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases27.2

Community & Adoption

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

64Moderate · 17% of overall

Popularity & adoption

53Moderate
How it's scored
32.4/60Stars — 101 stars
14.2/25Forks — 51 forks
6.2/15Watchers — 14 watchers
Inputs used
forks51
stars101
watchers14
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
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_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

93Exceptional · 23% of overall

Maintainer resilience (bus factor)

89Excellent
How it's scored
45.9/54Bus factor — 5 contributor(s) cover half of all commits
19.7/22.5Commit distribution — top contributor authored 13% of commits
13.5/13.5Contributor breadth — 63 contributors
10/10OpenSSF Scorecard: Contributors — project has 15 contributing companies or organizations
Inputs used
bus_factor5
contributors_sampled63
top_contributor_share0.126

Issue & PR responsiveness

87Excellent
How it's scored
39.8/42Issue resolution — 95% of issues closed
23.6/30PR acceptance — 540/687 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-Review — Found 25/29 approved changesets -- score normalized to 8
Inputs used
merged_prs540
open_issues7
closed_issues128
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.948
closed_unmerged_prs147
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

100Exceptional
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
25/25Owner reach — 3,222 followers of DataDog
25/25Track record — 1,194 public repos, account ~15 yr old
Inputs used
followers3,222
owner_typeOrganization
is_verified—
owner_loginDataDog
public_repos1,194
account_age_days5,814
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 119 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdatadog_lambda
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — .flake8
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 26 out of 27 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

55Moderate
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
docs_sitehttps://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

52Moderate · 16% of overall

Security posture

52Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5CI-Tests — 26 out of 27 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 25/29 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 15 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 25 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
3.5/5SAST — SAST tool detected but not run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 15 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Packaging. Remaining weights renormalized.

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.

34At Risk · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

52Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .flake8
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespackage-lock.json, poetry.lock, yarn.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
52.9/55Manageable file sizes — 2/52 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes158,439
source_files_sampled52
oversized_source_files2

Key facts

101GitHub stars
63contributors
139commits, last 12 months
3days since last push
100releases
5bus factor
7open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 5.2 / 10
5.2aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-17 02:02 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
9CI-Tests26 out of 27 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 25/29 approved changesets -- score normalized to 8
10Contributorsproject has 15 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained25 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
7SASTSAST tool detected but not run on all commits
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities15 existing vulnerabilities detected
Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPIdatadog>=0.51.0,<1.0.0pyproject.toml
PyPIwrapt^1.11.2pyproject.toml
PyPIddtrace—pyproject.toml
PyPIujson—pyproject.toml
PyPIurllib3—pyproject.toml
PyPIbotocore^1.34.0pyproject.toml
PyPIrequests—pyproject.toml
PyPIpytest—pyproject.toml
PyPIpytest-benchmark^4.0pyproject.toml
PyPIflake8^5.0.4pyproject.toml
All dependencies 141

Full resolved dependency set from the GitHub dependency graph: 11 direct and 130 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbotocore1.36.8direct
PyPIdatadog0.51.0direct
PyPIddtrace3.19.7direct
PyPIflake85.0.4direct
PyPIpytest8.3.4direct
PyPIpytest-benchmark4.0.0direct
PyPIrequests2.32.4direct
PyPIrequests2.33.1direct
PyPIujson5.10.0direct
PyPIurllib31.26.20direct
PyPIwrapt1.17.2direct
npm2-thenable1.0.0indirect
npm@iarna/toml2.2.5indirect
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npmappdirectory0.1.0indirect
npmbalanced-match1.0.2indirect
npmbluebird3.7.2indirect
npmbrace-expansion1.1.14indirect
npmcamelcase5.3.1indirect
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npmcliui6.0.0indirect
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npmd1.0.2indirect
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npmevent-emitter0.3.5indirect
npmext1.7.0indirect
npmfind-up4.1.0indirect
npmfs-extra10.1.0indirect
npmfs.realpath1.0.0indirect
npmget-caller-file2.0.5indirect
npmglob7.2.3indirect
npmglob-all3.3.1indirect
npmgraceful-fs4.2.11indirect
npmimmediate3.0.6indirect
npminflight1.0.6indirect
npminherits2.0.4indirect
npmis-docker2.2.1indirect
npmis-fullwidth-code-point3.0.0indirect
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npmis-primitive3.0.1indirect
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npmisexe2.0.0indirect
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npmjszip3.10.1indirect
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npmlodash.get4.4.2indirect
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npmnice-try1.0.5indirect
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npmp-limit2.3.0indirect
npmp-locate4.1.0indirect
npmp-try2.2.0indirect
npmpako1.0.11indirect
npmpath-exists4.0.0indirect
npmpath-is-absolute1.0.1indirect
npmpath-key2.0.1indirect
npmprocess-nextick-args2.0.1indirect
npmreadable-stream2.3.8indirect
npmreadable-stream3.6.2indirect
npmrequire-directory2.1.1indirect
npmrequire-main-filename2.0.0indirect
npmrimraf3.0.2indirect
npmsafe-buffer5.1.2indirect
npmsafe-buffer5.2.1indirect
npmsemver5.7.2indirect
npmsemver7.7.4indirect
npmserverless-plugin-datadog2.34.1indirect
npmserverless-python-requirements6.1.2indirect
npmset-blocking2.0.0indirect
npmset-value4.1.0indirect
npmsetimmediate1.0.5indirect
npmsha256-file1.0.0indirect
npmshebang-command1.2.0indirect
npmshebang-regex1.0.0indirect
npmshell-quote1.8.3indirect
npmshell-quote1.8.4indirect
npmsplit23.2.2indirect
npmsprintf-kit2.0.2indirect
npmstream-promise3.2.0indirect
npmstring-width4.2.3indirect
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npmstring_decoder1.3.0indirect
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npmtr460.0.3indirect
npmtype2.7.3indirect
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npmutil-deprecate1.0.2indirect
npmwebidl-conversions3.0.1indirect
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npmwhich1.3.1indirect
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npmwrappy1.0.2indirect
npmy18n4.0.3indirect
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PyPIbytecode0.16.1indirect
PyPIcertifi2024.12.14indirect
PyPIcharset-normalizer3.4.1indirect
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PyPIdeprecated1.2.18indirect
PyPIenvier0.6.1indirect
PyPIexceptiongroup1.2.2indirect
PyPIidna3.10indirect
PyPIimportlib-metadata8.5.0indirect
PyPIiniconfig2.0.0indirect
PyPIjmespath1.0.1indirect
PyPImccabe0.7.0indirect
PyPIopentelemetry-api1.29.0indirect
PyPIpackaging24.2indirect
PyPIpluggy1.5.0indirect
PyPIpy-cpuinfo9.0.0indirect
PyPIpycodestyle2.9.1indirect
PyPIpyflakes2.5.0indirect
PyPIpygments2.20.0indirect
PyPIpython-dateutil2.9.0.post0indirect
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Raw JSON report machine-readable

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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 v0.11.0 — full methodology · metrics wiki.

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