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brightdata-rate-limits

brightdata-rate-limits

Analyze and design Bright Data concurrency and backoff controls from observed provider signals and owned budgets instead of invented global limits. Use when handling 429 responses, dataset job ceilings, or uneven proxy pressure. Trigger with: "tune Bright Data concurrency", "handle Bright Data 429", "set a dataset job budget".

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Documentación de la Skill

GitHub

name: brightdata-rate-limits description: 'Analyze and design Bright Data concurrency and backoff controls from observed provider signals and owned budgets instead of invented global limits. Use when handling 429 responses, dataset job ceilings, or uneven proxy pressure. Trigger with: "tune Bright Data concurrency", "handle Bright Data 429", "set a dataset job budget".' allowed-tools: Read, Grep, Write, Edit version: 2.0.0 argument-hint: "[workload-profile]" model: inherit effort: high license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

  • saas
  • web-data
  • bright-data
  • rate-limits
  • operations compatibility: 'Requires an approved Bright Data account or offline fixtures, current Bright Data documentation, and an authorized public-data collection purpose'

Bright Data Adaptive Capacity Control

Overview

Bright Data does not publish one global proxy request limit. Build separate controllers for proxy traffic and dataset jobs, honor current provider signals, and keep target, cost, and policy ceilings stricter than capacity.

Prerequisites

  • A workload profile with target, product, and idempotency classes
  • Observed latency, error, and provider-code samples
  • Owner-approved concurrency, byte, cost, and wall-time ceilings

Instructions

Step 1: Measure the lane

Read recent receipts and Grep for 429, Retry-After, provider error codes, active dataset jobs, per-IP concentration, and queue depth. Do not infer capacity from successful bursts alone.

Step 2: Separate controllers

Write independent limits for proxy requests, Browser API sessions, async triggers, progress polling, downloads, and delivery workers. One product's success must not raise another product's ceiling.

Step 3: Apply evidence-based backoff

Retry only idempotent transient work. Honor provider guidance, use bounded jitter, cap attempts and elapsed time, and open the circuit on policy, authentication, or data errors.

Step 4: Tune gradually

Edit one limit at a time, run an approved canary, compare throughput, error, and cost, and retain the lower limit unless the evidence and owner approve promotion.

Tool Discipline

Use Read and Grep to analyze redacted metrics and documented codes. Use Write and Edit for controller configuration, tests, and runbooks. This skill does not run live traffic or change Bright Data account limits.

Output

  • Per-lane concurrency and queue budgets
  • Retry and circuit matrix by documented failure class
  • Canary comparison with rollback threshold

Examples

If dataset triggers return a tenant-specific parallel-job error, stop launching new jobs and continue bounded progress polling for owned snapshots. If proxy traffic returns a per-IP 429, reduce pressure and review distribution rather than guessing a universal rate.

Error Handling

FailureMeaningResponse
No provider code is retained429 cause is ambiguousImprove redacted instrumentation before tuning
Retries amplify queue depthBackoff lacks admission controlOpen the circuit and drain owned work
Throughput improves but cost or error ceiling failsOptimization violates the budgetRoll back the changed limit

Resources

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