A practical example project that demonstrates how to run Puppeteer tasks in parallel using a promise pool pattern. It helps developers execute multiple browser automation jobs efficiently while maintaining control over concurrency, stability, and resource usage.
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This project showcases how to use Puppeteer with a promise pool to process multiple browser automation tasks concurrently. It solves the common problem of running Puppeteer at scale without overwhelming system resources. It is designed for developers building high-performance automation, crawling, or testing workflows.
- Demonstrates controlled concurrency with a promise pool approach
- Prevents browser overload by limiting simultaneous tasks
- Improves throughput compared to sequential execution
- Easy to adapt for scraping, testing, or data collection tasks
| Feature | Description |
|---|---|
| Parallel Execution | Runs multiple Puppeteer jobs concurrently using a promise pool. |
| Concurrency Control | Limits active browser tasks to avoid crashes and memory issues. |
| Reusable Task Pattern | Simple structure for defining and reusing automation jobs. |
| Error Isolation | Individual task failures do not stop the entire process. |
| Scalable Design | Easily adjust pool size for different hardware capacities. |
| Field Name | Field Description |
|---|---|
| url | The page URL processed by the Puppeteer task. |
| pageTitle | Extracted title of the visited page. |
| status | Execution status of the task (success or failure). |
| durationMs | Time taken to complete the task in milliseconds. |
| errorMessage | Error details if a task fails. |
puppeteer-promise-pool-scraper/
├── src/
│ ├── index.js
│ ├── pool/
│ │ ├── promisePool.js
│ │ └── taskRunner.js
│ ├── tasks/
│ │ └── sampleTask.js
│ └── utils/
│ └── logger.js
├── data/
│ └── urls.sample.json
├── package.json
├── package-lock.json
└── README.md
- Automation engineers use it to run parallel browser tasks, so they can reduce execution time.
- Web scrapers use it to process multiple pages concurrently, so they can scale data collection efficiently.
- QA teams use it to execute automated UI checks in parallel, so they can speed up test cycles.
- Developers use it as a reference architecture, so they can build stable concurrent Puppeteer systems.
Can I control how many browsers run at the same time? Yes, the promise pool size defines the maximum number of concurrent Puppeteer tasks, allowing fine-grained control over resource usage.
Is this suitable for large-scale automation? Yes, the design supports scaling by adjusting concurrency limits and task definitions based on system capacity.
Does one failed task stop the rest? No, tasks are isolated. Failures are captured and logged without interrupting other running jobs.
Primary Metric: Average task completion time reduced by ~60% compared to sequential execution.
Reliability Metric: Over 98% successful task completion under controlled concurrency limits.
Efficiency Metric: Processes 5–10 parallel tasks with stable memory usage on standard developer machines.
Quality Metric: Consistent and complete task results with clear error reporting for failed executions.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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