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brightdata-deploy-integration

Plan a Bright Data collection deployment by splitting requests, scraper jobs, snapshot downloads, validation, and delivery into bounded workers. Define queues, permissions, resource limits, approved destinations, rollout checks, and rollback steps in deployment manifests.

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Design and review a bounded Bright Data worker deployment with separate proxy, Browser API, scraper, snapshot, and delivery responsibilities. Use when preparing a runtime topology or deployment manifest. Trigger with: "deploy this Bright Data worker", "design Bright Data queues", "review the Bright Data deployment".

jeremylongshore/tons-of-skills-marketplace2,884 stars(GitHub 2,884 + cccskills 0)

Run score Not tested

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Good for

  • Planning worker roles and queues for a Bright Data deployment
  • Setting per-stage permissions and resource limits
  • Preparing a canary rollout and rollback plan

Files included (2)

  • SKILL.md3.9 KB
  • references/official-docs.md779 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Bright Data Worker Deployment

Overview

Deploy collection as bounded workers instead of one privileged process. Separate synchronous proxy or Browser API requests from scraper triggers, snapshot polling, downloads, and destination delivery so each stage has its own authority, queue, resource ceiling, and rollback.

Prerequisites

  • An approved workload manifest naming targets, fields, products, and destinations
  • Managed secret references and environment-specific Bright Data resources
  • Queue, object-storage, quarantine, and observability facilities

Instructions

Step 1: Inventory runtime responsibilities

Read the application and Grep for proxy requests, Browser API sessions, /datasets/v3/trigger, progress checks, snapshot downloads, and delivery calls. Assign each responsibility to the smallest worker role.

Step 2: Define admission and isolation

Write or Edit deployment manifests with separate queues and identities for request, browser, trigger, poll, download, validate, and delivery workers. Add target allowlists, byte and record ceilings, timeouts, concurrency bounds, and dead-letter routing.

Step 3: Protect data movement

Stream large snapshots to bounded storage, validate schema before downstream use, quarantine unexpected content, and require an approved destination before invoking /datasets/v3/deliver/SNAPSHOT_ID.

Step 4: Make rollout reversible

Specify health signals, queue-depth and error-class alerts, canary capacity, drain behavior, rollback version, secret revocation, and replay rules. Produce manifests and a deployment plan; do not initiate production traffic from this skill.

Tool Discipline

Use Read and Grep for topology and configuration discovery. Use Write and Edit for deployment manifests, queue contracts, policies, tests, and runbooks. This skill does not deploy, rotate credentials, create zones, or send provider requests.

Output

  • Worker and queue topology with explicit trust boundaries
  • Resource, data, and destination controls per stage
  • Canary, drain, rollback, quarantine, and replay plan

Examples

A trigger worker creates one approved scraper job, a poller records state transitions, a downloader streams the completed snapshot to quarantine, a validator enforces the schema, and a delivery worker releases only accepted records to an approved destination.

Error Handling

FailureMeaningResponse
One worker holds every credentialBlast radius is too largeSplit identities and secret scopes
Download memory grows with snapshot sizeTransfer is unboundedStream with byte ceilings and backpressure
Delivery destination is runtime inputExfiltration boundary is openResolve destinations from an approved manifest

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