Docker Hub Image Intelligence API | Tags, Pulls & Search

Monitor public Docker Hub repositories and extract critical container updates automatically without the overhead of a headless browser. This tool provides deep image intelligence by leveraging the stable v2 API to scrape pull signals, star counts, and detailed repository metadata directly from the source. Security teams and system administrators rely on this fast, reliable monitor to schedule recurring checks on essential base images like nginx or redis, ensuring they are instantly aware of tag drift or newly published vulnerabilities.

Instead of manually refreshing web pages to check if a new container version is out, you can run this tool on a daily or weekly schedule to track exactly what changes across your targeted repositories. Set up a watchlist of URLs or search queries, and let the scraper extract the latest details seamlessly. The monitor reliably captures crucial data fields including full descriptions, recent tag timestamps, storage sizes, and category assignments.

By pulling this data regularly, infrastructure teams can integrate these tracking results straight into alerting tools or CI/CD pipelines. Whenever you run the task, it captures a precise snapshot of the repository state. This makes it incredibly easy to spot unexpected changes in image tags, monitor repository health, or catch sudden spikes in pull counts that might indicate wider adoption or an urgent patch release.

Store Quickstart

• Start with 2–5 repositories such as library/nginx or redis.
• Keep maxTagsPerRepo around 20–50 on the first run so tag enrichment stays cheap and fast.
• Use searchTerms only when you want discovery; skip them when you already know the repositories you care about.
• After the first useful run, move to the recurring watchlist template for repeat base-image checks, then use the webhook handoff template for tag-drift alerts.

V1 behavior

• Direct repository inputs such as library/nginx or bare names such as nginx (normalized to library/nginx)
• Optional searchTerms via the public Docker Hub search endpoint
• Live repository metadata: description, full_description, pulls, stars, repository type, visibility, timestamps, categories when Docker Hub exposes them, and repository-level storage size when Docker Hub exposes it
• Live tag pagination capped by maxTagsPerRepo, with up to 100 tags fetched per API page
• Per-tag OS / architecture platform normalization
• Honest repository and search statuses: ok, not_found, rate_limited, error

Out of scope

• Docker Scout
• CVEs / vulnerability scanning
• Private repository intelligence beyond explicit public-access warnings

Use Cases

Who	Why
DevOps teams	Review base image freshness, pull signals, and tag sprawl before standardizing images
Platform engineers	Compare competing public repositories with one normalized schema
Security teams	Inventory public repos and tags before deeper image scanning
Analysts	Track vendor or ecosystem container footprints from public metadata

Input

Provide at least one of:

• repositories: exact repository slugs to fetch
• searchTerms: public Docker Hub search queries

Key options:

• includeTags (default true)
• maxTagsPerRepo (default 100, max 500)
• maxSearchResults (default 25, max 250)
• delivery: dataset or webhook
• dryRun

Output

• meta: run summary, scope note, and explicit warnings
• searches: normalized search responses and status per query
• repositories: normalized repository records with tags and tagSummary

When Docker Hub omits fields such as categories or repository storage size, the actor returns null / [] and records an explicit warning instead of silently inventing values.

Output Example

{
  "repository": "library/nginx",
  "status": "ok",
  "description": "Official build of Nginx.",
  "pullCount": 456,
  "starCount": 123,
  "tagSummary": { "total": 2, "truncated": true },
  "tags": [
    {
      "name": "1.27",
      "lastPulledAt": "2025-01-04T00:00:00.000Z",
      "platforms": [{ "os": "linux", "architecture": "amd64" }]
    }
  ],
  "warnings": []
}

Local run

npm test
npm start

npm start reads input.json locally and writes output/result.json.

Related Actors

Pair this actor with other flagship intelligence APIs in the same portfolio:

• NPM Package Intelligence API — audit JavaScript packages that feed the applications inside your images.
• PyPI Package Intelligence API — profile Python dependencies alongside public container repositories.
• Shopify Store Intelligence API — combine storefront research with infrastructure-facing image intelligence.

Pricing & Cost Control

Apify Store pricing is usage-based, so cost mainly follows how many repositories and tags you inspect. Check the Store pricing card for the current per-event rates.

• Keep maxTagsPerRepo and maxSearchResults low for exploratory runs.
• Set includeTags to false when repository-level metadata is enough.
• Use dryRun: true before larger repo watchlists or webhook delivery.
• Prefer dataset delivery while you validate which tag fields matter downstream.

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Bug report or feature request? Open an issue on the Issues tab of this actor.