Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 09:05 UTC

DataDog / datadog-lambda-python

The Datadog AWS Lambda Layer for Python

Python · ShellApache-2.0★ 101 stars⑂ 52 forkssince Apr 2019View on GitHub ↗

DataDog/datadog-lambda-python holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Sustainability & Governance (93/100) and lowest on AI Readiness (54/100). It was last updated 5 days ago. 5 contributors account for most of its recent work.

overall / 100

Exceptional

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.

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)

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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

Datadog, Inc.Organization · verified domain

3,293 followers1,202 public repossince Aug 2010

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	datadog_lambda	8.127.0	2,444,330	120	36 days ago	datadog aws lambda layer

Metrics by category

Vitality

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

92Excellent · 21% of overall

Development activity

93Exceptional

How it's scored

36/36	Push recency — last push 5 days ago
29.1/36	Commit cadence — 42/52 weeks with commits
18/18	Commit volume — 128 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 15 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	128
human_commit_share	0.98
days_since_last_push	5
active_weeks_last_year	42

Release discipline

90Excellent

How it's scored

27/27	Ships releases — 100 releases published
36/36	Release recency — latest release 36 days ago
27/27	Release cadence — a release every ~27.2 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	100
latest_release_tag	v8.127.0
releases_from_tags	no
days_since_latest_release	36
mean_days_between_releases	27.2

Community & Adoption

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

73Good · 17% of overall

Popularity & adoption

53Moderate

How it's scored

32.4/60	Stars — 101 stars
14.2/25	Forks — 52 forks
6.2/15	Watchers — 14 watchers

Inputs used

forks	52
stars	101
watchers	14
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	4
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	github.com, shields.io
has_pull_request_template	yes

Ecosystem adoption (downloads)

100Exceptional

How it's scored

80/80	Monthly downloads — 2,444,330 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	datadog_lambda
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	2,444,330
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?

93Exceptional · 23% of overall

Maintainer resilience (bus factor)

89Excellent

How it's scored

45.9/54	Bus factor — 5 contributor(s) cover half of all commits
19.6/22.5	Commit distribution — top contributor authored 13% of commits
13.5/13.5	Contributor breadth — 60 contributors
10/10	OpenSSF Scorecard: Contributors — project has 15 contributing companies or organizations

Inputs used

bus_factor	5
contributors_sampled	60
top_contributor_share	0.128

Issue & PR responsiveness

87Excellent

How it's scored

39.9/42	Issue resolution — 95% of issues closed
23.5/30	PR acceptance — 546/698 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15	OpenSSF Scorecard: Code-Review — Found 24/28 approved changesets -- score normalized to 8

Inputs used

merged_prs	546
open_issues	7
closed_issues	129
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	2
prs_decided_30d	2
issue_closed_ratio	0.949
closed_unmerged_prs	152
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

100Exceptional

How it's scored

30/30	Ownership backing — organization-owned
20/20	Verified domain
25/25	Owner reach — 3,293 followers of DataDog
25/25	Track record — 1,202 public repos, account ~16 yr old

Inputs used

followers	3,293
owner_type	Organization
is_verified	yes
owner_login	DataDog
public_repos	1,202
account_age_days	5,868

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 36 days ago
20/20	Version history — 120 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	datadog_lambda
ecosystems	pypi
any_deprecated	no
min_days_since_publish	36

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

92Excellent

How it's scored

24/24	CI workflows — 4 workflow(s)
24/24	Tests present
16/16	Linter config — .flake8
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
18/20	OpenSSF Scorecard: CI-Tests — 26 out of 27 merged PRs checked by a CI test -- score normalized to 9

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

55Moderate

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
10/10	Repository description
0/10	Topics
0/10	Wiki

Inputs used

topics	—
has_wiki	no
homepage	https://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
docs_site	https://docs.datadoghq.com/integrations/amazon_lambda/#installing-and-using-the-datadog-layer
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
3/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.2/2.5	CI-Tests — 26 out of 27 merged PRs checked by a CI test -- score normalized to 9
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5	Code-Review — Found 24/28 approved changesets -- score normalized to 8
2.5/2.5	Contributors — project has 15 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 15 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
3.5/5	SAST — SAST tool detected but not run on all commits
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 19 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	17
scorecard_version	v5.5.0
checks_inconclusive	1
scorecard_aggregate	5.2

Excluded from scoring (no data or not applicable): Packaging. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	13
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:datadog_lambda@8.127.0 runtime dependency closure — what installing the published package pulls in — 13 packages. 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.

54Moderate · 4% of overall

Agent context & guidance

55Moderate

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15	Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.datadoghq.com/llms.txt)
40/40	Legible commit history — 89 of 98 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	yes
llms_txt_url	https://docs.datadoghq.com/llms.txt
legible_history_share	0.908
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

53Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — .flake8
0/11	Static type checking
10/10	Reproducible environment — Dockerfile, lockfile
10/10	Demonstrated agent practice — 12 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	package-lock.json, poetry.lock, yarn.lock
has_dockerfile	yes
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.12
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

53Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
52.9/55	Manageable file sizes — 2/52 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	162,365
source_files_sampled	52
oversized_source_files	2

Key facts

101GitHub stars

60contributors

128commits, last 12 months

5days since last push

100releases

5bus factor

7open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 52 ⇿

0Stars

52Forks

100Releases

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.

Major 0Minor 39Patch 0

Each point covers 7 days.

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 · 2026-09-09 09:04 UTC

10	Binary-Artifacts	no binaries found in the repo
4	Branch-Protection	branch protection is not maximal on development and all release branches
9	CI-Tests	26 out of 27 merged PRs checked by a CI test -- score normalized to 9
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
8	Code-Review	Found 24/28 approved changesets -- score normalized to 8
10	Contributors	project has 15 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	15 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
7	SAST	SAST tool detected but not run on all commits
0	Security-Policy	security policy file not detected
0	Signed-Releases	Project has not signed or included provenance with any releases.
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	19 existing vulnerabilities detected

Direct dependencies 10

Registry	Package	Version constraint	Manifest
PyPI	datadog	`>=0.51.0,<1.0.0`	pyproject.toml
PyPI	wrapt	`^1.11.2`	pyproject.toml
PyPI	ddtrace	`—`	pyproject.toml
PyPI	ujson	`—`	pyproject.toml
PyPI	urllib3	`—`	pyproject.toml
PyPI	botocore	`^1.34.0`	pyproject.toml
PyPI	requests	`—`	pyproject.toml
PyPI	pytest	`—`	pyproject.toml
PyPI	pytest-benchmark	`^4.0`	pyproject.toml
PyPI	flake8	`^5.0.4`	pyproject.toml

All dependencies 142

Full resolved dependency set from the GitHub dependency graph: 11 direct and 131 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	botocore	`1.36.8`	direct
PyPI	datadog	`0.51.0`	direct
PyPI	ddtrace	`3.19.7`	direct
PyPI	flake8	`5.0.4`	direct
PyPI	pytest	`8.3.4`	direct
PyPI	pytest-benchmark	`4.0.0`	direct
PyPI	requests	`2.32.4`	direct
PyPI	requests	`2.33.1`	direct
PyPI	ujson	`5.10.0`	direct
PyPI	urllib3	`1.26.20`	direct
PyPI	wrapt	`1.17.2`	direct
npm	2-thenable	`1.0.0`	indirect
npm	@iarna/toml	`2.2.5`	indirect
npm	ansi-regex	`5.0.1`	indirect
npm	ansi-styles	`4.3.0`	indirect
npm	appdirectory	`0.1.0`	indirect
npm	balanced-match	`1.0.2`	indirect
npm	bluebird	`3.7.2`	indirect
npm	brace-expansion	`1.1.14`	indirect
npm	brace-expansion	`1.1.18`	indirect
npm	camelcase	`5.3.1`	indirect
npm	child-process-ext	`2.1.1`	indirect
npm	cliui	`6.0.0`	indirect
npm	color-convert	`2.0.1`	indirect
npm	color-name	`1.1.4`	indirect
npm	concat-map	`0.0.1`	indirect
npm	core-util-is	`1.0.3`	indirect
npm	cross-spawn	`6.0.6`	indirect
npm	d	`1.0.2`	indirect
npm	decamelize	`1.2.0`	indirect
npm	duration	`0.2.2`	indirect
npm	emoji-regex	`8.0.0`	indirect
npm	es5-ext	`0.10.64`	indirect
npm	es6-iterator	`2.0.3`	indirect
npm	es6-symbol	`3.1.4`	indirect
npm	esniff	`2.0.1`	indirect
npm	event-emitter	`0.3.5`	indirect
npm	ext	`1.7.0`	indirect
npm	find-up	`4.1.0`	indirect
npm	fs-extra	`10.1.0`	indirect
npm	fs.realpath	`1.0.0`	indirect
npm	get-caller-file	`2.0.5`	indirect
npm	glob	`7.2.3`	indirect
npm	glob-all	`3.3.1`	indirect
npm	graceful-fs	`4.2.11`	indirect
npm	immediate	`3.0.6`	indirect
npm	inflight	`1.0.6`	indirect
npm	inherits	`2.0.4`	indirect
npm	is-docker	`2.2.1`	indirect
npm	is-fullwidth-code-point	`3.0.0`	indirect
npm	is-plain-object	`2.0.4`	indirect
npm	is-primitive	`3.0.1`	indirect
npm	is-stream	`1.1.0`	indirect
npm	is-wsl	`2.2.0`	indirect
npm	isarray	`1.0.0`	indirect
npm	isexe	`2.0.0`	indirect
npm	isobject	`3.0.1`	indirect
npm	jsonfile	`6.2.0`	indirect
npm	jszip	`3.10.1`	indirect
npm	lie	`3.3.0`	indirect
npm	locate-path	`5.0.0`	indirect
npm	lodash.get	`4.4.2`	indirect
npm	lodash.uniqby	`4.7.0`	indirect
npm	lodash.values	`4.3.0`	indirect
npm	log	`6.3.2`	indirect
npm	minimatch	`3.1.5`	indirect
npm	next-tick	`1.1.0`	indirect
npm	nice-try	`1.0.5`	indirect
npm	node-fetch	`2.7.0`	indirect
npm	once	`1.4.0`	indirect
npm	p-limit	`2.3.0`	indirect
npm	p-locate	`4.1.0`	indirect
npm	p-try	`2.2.0`	indirect
npm	pako	`1.0.11`	indirect
npm	path-exists	`4.0.0`	indirect
npm	path-is-absolute	`1.0.1`	indirect
npm	path-key	`2.0.1`	indirect
npm	process-nextick-args	`2.0.1`	indirect
npm	readable-stream	`2.3.8`	indirect
npm	readable-stream	`3.6.2`	indirect
npm	require-directory	`2.1.1`	indirect
npm	require-main-filename	`2.0.0`	indirect
npm	rimraf	`3.0.2`	indirect
npm	safe-buffer	`5.1.2`	indirect
npm	safe-buffer	`5.2.1`	indirect
npm	semver	`5.7.2`	indirect
npm	semver	`7.7.4`	indirect
npm	serverless-plugin-datadog	`2.34.1`	indirect
npm	serverless-python-requirements	`6.1.2`	indirect
npm	set-blocking	`2.0.0`	indirect
npm	set-value	`4.1.0`	indirect
npm	setimmediate	`1.0.5`	indirect
npm	sha256-file	`1.0.0`	indirect
npm	shebang-command	`1.2.0`	indirect
npm	shebang-regex	`1.0.0`	indirect
npm	shell-quote	`1.10.0`	indirect
npm	shell-quote	`1.8.3`	indirect
npm	split2	`3.2.2`	indirect
npm	sprintf-kit	`2.0.2`	indirect
npm	stream-promise	`3.2.0`	indirect
npm	string-width	`4.2.3`	indirect
npm	string_decoder	`1.1.1`	indirect
npm	string_decoder	`1.3.0`	indirect
npm	strip-ansi	`6.0.1`	indirect
npm	tr46	`0.0.3`	indirect
npm	type	`2.7.3`	indirect
npm	uni-global	`1.0.0`	indirect
npm	universalify	`2.0.1`	indirect
npm	util-deprecate	`1.0.2`	indirect
npm	webidl-conversions	`3.0.1`	indirect
npm	whatwg-url	`5.0.0`	indirect
npm	which	`1.3.1`	indirect
npm	which-module	`2.0.1`	indirect
npm	wrap-ansi	`6.2.0`	indirect
npm	wrappy	`1.0.2`	indirect
npm	y18n	`4.0.3`	indirect
npm	yargs	`15.4.1`	indirect
npm	yargs-parser	`18.1.3`	indirect
PyPI	bytecode	`0.16.1`	indirect
PyPI	certifi	`2024.12.14`	indirect
PyPI	charset-normalizer	`3.4.1`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	deprecated	`1.2.18`	indirect
PyPI	envier	`0.6.1`	indirect
PyPI	exceptiongroup	`1.2.2`	indirect
PyPI	idna	`3.10`	indirect
PyPI	importlib-metadata	`8.5.0`	indirect
PyPI	iniconfig	`2.0.0`	indirect
PyPI	jmespath	`1.0.1`	indirect
PyPI	mccabe	`0.7.0`	indirect
PyPI	opentelemetry-api	`1.29.0`	indirect
PyPI	packaging	`24.2`	indirect
PyPI	pluggy	`1.5.0`	indirect
PyPI	py-cpuinfo	`9.0.0`	indirect
PyPI	pycodestyle	`2.9.1`	indirect
PyPI	pyflakes	`2.5.0`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	tomli	`2.2.1`	indirect
PyPI	typing-extensions	`4.12.2`	indirect
PyPI	zipp	`3.20.2`	indirect

Dependency advisories 0

Installing pypi:datadog_lambda@8.127.0 pulls in 13 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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.

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.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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