Agent skill

Collectors Prometheus Profiles

by netdata in netdata/netdata

Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs.

GPL-3.0Auto-check passedDevOps & Cloud

Install Collectors Prometheus Profiles

skills CLI
$ npx skills add netdata/netdata --skill collectors-prometheus-profiles -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install netdata/netdata collectors-prometheus-profiles --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/netdata/netdata.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/collectors-prometheus-profiles .claude/skills/collectors-prometheus-profiles && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
collectors-prometheus-profiles
GitHub stars
81k
Token cost
~4.7k tokens
SKILL.md length
2,248 words
Files
16 (incl. scripts)
Skills in repo
27
Repo updated
First seen
Licence
GPL-3.0

At a glance

Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs.

  • Works in 8 steps: Establish the evidence boundary.… → Design the operator model before YAML… → Classify labels and cardinality… → …
  • Profile authoring scripts and explicitly requested capture
  • SKILL.md covers Authorities, Choose the workflow, Authoring workflow and Stock contribution rule sheet, plus 3 more sections
  • Runs Python scripts from its folder; calls python3 and go

What it does

Collectors Prometheus Profiles is an agent skill from netdata/netdata. Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs. Also use for profile authoring scripts and explicitly requested capture, installation or live verification.

Its SKILL.md is about 4.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts (for example `chart-design.md`, `how-tos/build-synthetic-fixture.md` and `how-tos/capture-metrics-dump.md`).

It sits in DevOps & Cloud, covering Monitoring and alerting. It works with Prometheus. The repository describes itself as: The fastest path to AI-powered full stack observability, even for lean teams. The licence is GPL-3.0.

When your agent uses it

  • Profile authoring scripts and explicitly requested capture
  • Live verification

Example prompts

  • “/collectors-prometheus-profiles”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Establish the evidence boundary. Inventory metric families, types, labels, optional modes, and source revisions.
  2. Design the operator model before YAML (chart-design.md). Answer, in causal order: is the service available and
  3. Classify labels and cardinality (chart-design.md, "Assign labels by role"; docs/NIDL-Framework.md when
  4. Choose truthful aggregation (chart-design.md, "Aggregation when labels are omitted"). One reducer per chart;
  5. Choose collection policy. match detects the exporter and bounds the profile's source namespace; prefer
  6. Encode the profile. Nested groups express hierarchy: child context_namespace segments join with ., child
  7. Run the objective validator and the ToC ("Scripts" below). PASS proves schema and the exercised production
  8. Review as an operator (chart-design.md, "Semantic review"). For a stock profile continue with

What it can do on your machine

Read from SKILL.md and the folder at commit a7f3cf9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 7 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • go

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Collectors Prometheus Profiles loads about 4.7k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 2,248 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~4.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from netdata/netdata at commit a7f3cf9, republished under its GPL-3.0 licence (© netdata). 2,248 words, ~4,718 tokens.

Download SKILL.mdSave it as .claude/skills/collectors-prometheus-profiles/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
name
collectors-prometheus-profiles
description
Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs. Also use for profile authoring scripts and explicitly requested capture, installation or live verification.

Prometheus profile authoring

A profile is an operator dashboard design backed by source evidence, not a mechanical metric-name translation. The author decides the entity grain, chart comparisons, cardinality boundary, hierarchy, and collection policy; the validator proves only the contracts code can establish.

Authorities

Use these owners for format and runtime contracts. Verify affected enforcement claims against the current code and tests; the lists below are a source map, not evidence that a changed implementation still behaves that way:

  • src/go/plugin/go.d/collector/prometheus/profile-format.md: the envelope, the runtime processing order, the stock contribution policy for autogen.selector and relabeling, chart-template rules, job-side profile selection.
  • src/go/plugin/framework/charttpl/README.md: every group and chart field, the validation rules, engine-derived behavior.
  • src/go/pkg/relabel/README.md: relabel actions, stage order, histogram and summary safety, profile precedence.
  • src/go/tools/prometheus-profile-validation/README.md: the validator CLI, safe job policy, what PASS establishes (one finding code per objective check), the warning classes.
  • src/go/internal/promprofile/README.md: framework boundary, authority model, compile and replay flow, support composition, the latest-testdata model.
  • src/go/plugin/go.d/collector/prometheus/profile-proofs/README.md and src/go/tools/prometheus-profile-proof/README.md: proof artifact contract, evidence boundary, external testdata contract, the evidence-dirs and verify commands.
  • docs/NIDL-Framework.md: the NIDL model (families, contexts, instances, dimensions, labels).

src/go/plugin/go.d/collector/prometheus/README.md is a symlink to a generated integration page and is not an authority.

Choose the workflow

Read the row for the work at hand, not the whole skill.

WorkRead
Review a profile or proof changeAffected sections of chart-design.md, metric-types.md and profile-schema.md; stock changes also need ownership-proof.md, proof-authoring.md and the rule sheet below. Consult existing design and proof evidence, without creating authoring artifacts merely to review.
Create or redesign a user profilechart-design.md, metric-types.md; profile-schema.md for where each field is documented
Create or change a stock profilethe above, then ownership-proof.md, proof-authoring.md, and the rule sheet below
Build stock fixtureshow-tos/build-synthetic-fixture.md, proof-authoring.md
Capture private evidencehow-tos/capture-metrics-dump.md
Answer a schema or runtime questionthe owner named in profile-schema.md, then the authority itself
Install or live-test a profile"Delivery and live verification"; sqlite-metadata-reset.md only when a reset is proposed
Relate a stock profile to integration metadata.agents/skills/integrations-lifecycle/how-tos/prometheus-profile-metadata.md
Change the scripts"Scripts" below

Loading this skill for review or explanation does not authorize capture, installation, database reset or generation. Apply the authoring criteria to the assigned change; execute operational procedures only within the actual request.

Authoring workflow

  1. Establish the evidence boundary. Inventory metric families, types, labels, optional modes, and source revisions. Separate exposition facts (names, HELP, TYPE, labels, observed values), source facts (lifecycle, units, label domains, relationships, optionality), and design judgments (grain, composition, hierarchy, exclusions). A captured endpoint is private input: never commit it unless deliberately sanitized from public source contracts, and never commit credentials, customer identities, private endpoints, or deployment data. Missing source evidence is a real limitation; one observed fixture is not a universal exporter contract.
  2. Design the operator model before YAML (chart-design.md). Answer, in causal order: is the service available and doing useful work; what load is it serving; is latency, error rate, or saturation worsening; which bounded entity or category explains it; which resource or dependency is responsible. For each view state one operator question, one entity grain, the smallest stable identity, the labels compared as dimensions, the labels kept for filtering, the labels omitted with the reducer that keeps the omission truthful, and the exact source signals with units, lifecycle, and inter-dimension relationship. Do not build an aggregate view Netdata derives by grouping the detailed one; choose the finest operator-useful grain whose cardinality and churn stay acceptable.
  3. Classify labels and cardinality (chart-design.md, "Assign labels by role"; docs/NIDL-Framework.md when choosing a monitored component, instance grain, dimension set, or label role). Give every relevant label a role: required identity, optional identity, dimension, promoted metadata, routing only, or omitted with a stated lost comparison. Estimate cardinality from the exporter contract, not the fixture; raw user IDs, addresses, request IDs, URLs, exception text, and hashes are normally too high-cardinality for identity or dimensions.
  4. Choose truthful aggregation (chart-design.md, "Aggregation when labels are omitted"). One reducer per chart; never merge gauges and counters into one rendered dimension, although a chart may hold distinct authored dimensions of different kinds when the shared comparison is intentional, each keeping its runtime-derived algorithm; quantiles are not mergeable. In a stock profile write aggregation explicitly wherever a deliberate many-to-one projection can occur, including deliberate sum, and omit it for collision-free routes.
  5. Choose collection policy. match detects the exporter and bounds the profile's source namespace; prefer exporter-unique families for detection: generic runtime families (process_*, python_*, http_*) may still be charted, but naming them in match makes unrelated endpoints eligible. Profile relabeling normalizes or drops exporter-owned families after selection (recover bounded identity encoded in metric names, normalize label values such as status classes, remove an established useless family class such as a source-wide *_created, or another source-backed transformation), only with a source-backed contract and a bounded result, never as a substitute for an identity or aggregation decision; the first applicable selected profile owns each original family and every selected template consumes the shared result. Profile fallback_type classifies untyped scalars the exporter owns, as narrowly as the evidence allows. autogen.selector shapes only the generic fallback charts. Job selector, job relabeling, and job fallback_type are deployment policy and are never a hidden prerequisite of a stock profile. Unknown future families inside a wildcard namespace stay eligible for generic fallback; a bounded, source-proven alias may route a future input to an authored metric only when an explicit future_inputs case proves that branch.
  6. Encode the profile. Nested groups express hierarchy: child context_namespace segments join with ., child family segments with /. Omit the root family when it would only repeat the resolved application; the named child groups then become top-level families, nested groups still need family, and a chart directly under a transparent root needs its own family. Keep a meaningful root on reusable instrumentation profiles that compose into other applications. Use base units; convert bytes to bits only where the operator convention is bandwidth. Omit algorithm (the runtime kind resolves it), type for line charts and histogram buckets (forced to heatmap), and multiplier and divisor defaults; use area and stacked only for the meanings in chart-design.md, "Choose chart types for visual meaning". Status values are dimensions from the source's closed state mapping, not chart instances. Gauge families ending in _info are skipped by the writer and never reach metrix (metric-types.md, "Info families").
  7. Run the objective validator and the ToC ("Scripts" below). PASS proves schema and the exercised production collector, planner, and emitter path; it does not prove operator usefulness, source semantics, cardinality outside the evidence, or additivity. Resolve every warning with evidence; never silence one mechanically.
  8. Review as an operator (chart-design.md, "Semantic review"). For a stock profile continue with ownership-proof.md and proof-authoring.md; stock work is complete only when the source contract, design, descriptor, fixtures, production profile, and integration metadata reconcile.

Stock contribution rule sheet

Stock profiles live under src/go/plugin/go.d/config/go.d/prometheus.profiles/default/<name>.yaml with a proof directory beside the collector. The "review by hand" table is contribution policy that the runtime format permits in user profiles. The validator has no user mode: its contributor-policy checks below apply to every profile it validates.

The code enforces
  • Validator (tools/prometheus-profile-validation, finding codes in src/go/tools/prometheus-profile-validation/README.md#what-pass-establishes): no autogen.selector.allow; every deny names one exact family (open_ended_profile_fallback_deny), and under CLI validation that family must appear in the fixture (unproven_profile_fallback_deny; under proof replay the coverage discharge below covers it); current evidence yields zero generic fallback and zero unmatched series (unmatched series downgrade to the profile_suppressed_series warning when a selected profile's autogen.selector explains every one); the relabel grammar and name-provenance rules (under proof replay, three specific checks are deferred to warnings, one branch each of open_ended_relabel_name_rewrite, unpreserved_relabel_name_identity, and unbounded_relabel_discard; the other branches emitting the first two codes stay errors); a lifecycle cap that discards observed entities or dimensions; a chart with no visible dimension; bucket charts use observations/s and no algorithm other than incremental (omitting it is fine); explicit area or stacked raises a semantic-review warning; a selected series carrying a label the chart neither uses nor excludes raises a warning.
  • Proof loaders and compiler (internal/promprofile/semantics): documentation.title and summary required; the closed evidence kind set; the outcome literals drop_before_writer and retain_writable_unrendered, with metadata_only bound to the latter; a reusable component, label, or reduction policy in either document needs two consumers (compile stage, semantics/evidence.go); every production autogen.selector.deny family is discharged by a retain_writable_unrendered exclusion naming it (coverage.go); metadata_only requires the conditions in metric-types.md, "Info families"; supports are accepted only in PROFILE-DESIGN.composition.supports; no other strict schema has the field.
  • Integrations projection (integrations/prometheus_profile_docs.py, run by gen_integrations.py and integrations/tests/test_prometheus_profile_docs.py): every stock profile, supporting ones included, needs a direct row under some module in the top-level profile_coverage.modules of the Prometheus collector metadata.yaml (generation raises Stock Prometheus profiles without an integration mapping otherwise); the projection resolves the support closure from the design; the key is accepted only on go.d.plugin/prometheus modules (a Python check, not the JSON schema); an unknown module id under it is recorded as a warning by _common.py, and gen_integrations.py ends with fail_on_warnings(), so the generation run still fails; a semantic view and its runtime chart must agree on family and chart identity (also enforced by the proof compiler, semantics/replay_route.go); the view question is never rendered.
Show full SKILL.md (737 more words)Show less
Review by hand
SurfaceStock rule
chart idomit when the context-derived ID is sufficient
priorityset chart_defaults.priority at the nearest group only where operator navigation needs one order for that subtree; chart-local priority only for a deliberate exception; otherwise omit (runtime default 70000)
instances.by_labels: ['*']avoid; use explicit source-backed identity
lifecycle capsomit; coverage must not depend on silently dropping observed or future entities
options.floatomit when the runtime metric is already floating point
algorithm, type, multiplier, divisoromit defaults; algorithm only for a deliberate source-lifecycle override (metric-types.md)
aggregationexplicit wherever a many-to-one projection can occur; omitted for collision-free routes
root familyomit when it only repeats the application; keep for reusable instrumentation profiles
stock metadata.yaml examplemust show that auto-selection suffices: no profiles, app, job selector, job relabeling, or job fallback_type; such a field in a stock example is evidence that profile ownership is incomplete
profile-required normalizationlives in profile relabeling, never duplicated as an optional job recipe
profile_coverage.modules rowlists the stock profiles the module owns, never a service's own supports: a repeated support is projected as primary with no activation sentence, and nothing rejects it
PROFILE-DESIGN.yaml documentationoperator-facing title and summary; every composition.supports entry has an activation sentence
integration copythe generated coverage table groups rows by top-level family (metric, family and chart title, dimension, unit, entity scope); metrics_description carries a short operator-model brief, not the chart ledger

Scripts

Invoke them from the repository root as written below. The two launchers resolve the repository root themselves and make caller-relative file arguments absolute before go run from src/go, so their file arguments may be given relative to wherever you are; profile-toc.py is plain Python and takes the profile path as given. CI runs their unit tests (.github/workflows/prometheus-profile-tests.yml, "Verify authoring launcher"); run them locally with .venv/bin/python3 -m unittest discover -s .agents/skills/collectors-prometheus-profiles/scripts -p 'test_*.py'.

  • .agents/skills/collectors-prometheus-profiles/scripts/validate-profile.py --profile P --dump D [--job J] [--support-profile S]... [--output text|json]: launcher for tools/prometheus-profile-validation. A user profile may use a minimal or deployment-specific job; stock validation uses the jobs its proof cases declare. A dash-prefixed token is never absolutized as an option's value, so a missing value reaches the tool unchanged and is rejected there instead of becoming a bogus path.
  • .venv/bin/python3 .agents/skills/collectors-prometheus-profiles/scripts/profile-toc.py PROFILE [--app APP] [--quiet] (needs PyYAML, which the repository .venv provides): renders the operator-visible family tree with contexts and effective priorities, then advisory UX warnings; it is not a gate. --app defaults to the profile's app:; the root context_namespace is dropped when it equals the app, as the collector does, and the prometheus.<app>. prefix is omitted. A chart with its own family is placed under that child node, as chartengine composes it. Priority 0 inherits, non-positive resolves to 70000. The six warnings, each to investigate and either repair or record as intentional: a one-character family segment (usually a slash label such as I/O split into path segments); all top-level families sharing a prefix, a top-level family equal to the application name, or one starting with it (usually a repeated application or root); a leaf with more than 15 contexts (usually missing intermediate owner structure); a one-context leaf (unnecessary structure or a merge candidate). Do not remove structure only to silence a warning when the parent is an operator entity, module boundary, or release contract; do not add structure only to divide by metric type.
  • .agents/skills/collectors-prometheus-profiles/scripts/proof-bundle.py evidence-dirs | verify [--profile P] [--testdata-root DIR]: launcher for tools/prometheus-profile-proof; injects --repo-root.

Delivery and live verification

  • Keep reusable runtime or instrumentation profiles independent; a service profile declares them in PROFILE-DESIGN.composition.supports and never duplicates their charts.
  • When installation/live verification is requested, install a user profile under the configured user profile directory and verify profile selection, advancing values, chart identity, labels, hierarchy, and cardinality against a live target.
  • Do not reset Netdata's SQLite metadata as routine iteration; identities expire through lifecycle and retention. Read sqlite-metadata-reset.md and obtain explicit production approval before any destructive reset.
  • When editing metadata.yaml, follow integrations-lifecycle: validate current inputs through isolated generation (.agents/skills/integrations-lifecycle/how-tos/preview-collector-page.md). Preserve original generated-page edits and follow the source/runtime delivery boundary; do not restore or discard unrelated work.

References

  • chart-design.md: operator model, entity grain, label roles, reducers, hierarchy, presentation, cardinality, review.
  • metric-types.md: parser and writer behavior per Prometheus type and the design consequences.
  • profile-schema.md: which document owns each field group; the notes none of them states.
  • ownership-proof.md: source ownership inventory and reconciliation.
  • proof-authoring.md: stock artifact responsibilities, skeletons, exclusions, verification.
  • how-tos/capture-metrics-dump.md: private evidence capture.
  • how-tos/build-synthetic-fixture.md: public source-complete fixture construction.
  • sqlite-metadata-reset.md: the destructive metadata-reset boundary.

© netdata, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 15 other files (scripts) in .agents/skills/collectors-prometheus-profiles of netdata/netdata.

  • SKILL.md
  • chart-design.md
  • how-tos/build-synthetic-fixture.md
  • how-tos/capture-metrics-dump.md
  • metric-types.md
  • ownership-proof.md
  • profile-schema.md
  • proof-authoring.md
  • scripts/_go_tool_launcher.py
  • scripts/profile-toc.py
  • scripts/proof-bundle.py
  • scripts/test_profile_toc.py
  • scripts/test_proof_bundle.py
  • scripts/test_validate_profile.py
  • scripts/validate-profile.py
  • sqlite-metadata-reset.md

Open the folder on GitHubat commit a7f3cf9

Compare with similar skills

Collectors Prometheus Profiles next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Collectors Prometheus Profiles compared with similar skills
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Happy Infra Metrics and Grafanaslopus/happy24k—~2kAutomated safety check: NotesMIT
Syncmetapawurb/hotpath-rs1.9k—~1.2kAutomated safety check: NotesMIT
WizTelemetry Platform Servicekubesphere/kubesphere17k—~1.8kAutomated safety check: PassCustom licence
Optimize Slurm TopologyNVlabs/alpasim1.3k—~1.6kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Collectors Prometheus Profiles

What does Collectors Prometheus Profiles do?

Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs. Collectors Prometheus Profiles is an agent skill from netdata/netdata. Create, review or validate Netdata Prometheus chart profiles, exporter dashboard design, collection policy and stock semantic proofs.

When should I use Collectors Prometheus Profiles?

Collectors Prometheus Profiles fits situations like: profile authoring scripts and explicitly requested capture; live verification.

How do I install Collectors Prometheus Profiles in Claude Code?

Run `npx skills add netdata/netdata --skill collectors-prometheus-profiles -a claude-code`. Or copy the skill folder (.agents/skills/collectors-prometheus-profiles in netdata/netdata) into .claude/skills/collectors-prometheus-profiles in your project. Claude Code loads it when a task matches its description.

How do I install Collectors Prometheus Profiles in Codex?

Run `npx skills add netdata/netdata --skill collectors-prometheus-profiles -a codex`. Or copy the skill folder (.agents/skills/collectors-prometheus-profiles in netdata/netdata) into .agents/skills/collectors-prometheus-profiles in your project. Codex loads it when a task matches its description.

Can I use Collectors Prometheus Profiles in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add netdata/netdata --skill collectors-prometheus-profiles -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/collectors-prometheus-profiles, .gemini/skills/collectors-prometheus-profiles, .github/skills/collectors-prometheus-profiles and .opencode/skills/collectors-prometheus-profiles in your project.

What does Collectors Prometheus Profiles need to run?

Going by SKILL.md and its folder, Collectors Prometheus Profiles needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and go). Our summary lists: Python 3.

Does Collectors Prometheus Profiles access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Collectors Prometheus Profiles safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Collectors Prometheus Profiles use?

Collectors Prometheus Profiles is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Collectors Prometheus Profiles use?

About 4.7k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Collectors Prometheus Profiles?

Skills that share tags, products or a category with Collectors Prometheus Profiles: KubeEye Cluster Inspection (kubesphere/kubesphere, 17k stars), Happy Infra Metrics and Grafana (slopus/happy, 24k stars), Syncmeta (pawurb/hotpath-rs, 1.9k stars) and WizTelemetry Platform Service (kubesphere/kubesphere, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Collectors Prometheus Profiles?

netdata (a GitHub organization) maintains it in netdata/netdata, which has 80,853 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.

Source: netdata/netdata on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.