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Serverless: guides & tutorials

Serverless scraping with queues and short-lived functions. Mind 15-minute Lambda caps while using Apify for managed bursts without always-on servers.

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Serverless scraping uses queues and short-lived functions instead of always-on servers. These guides cover the pattern and its tradeoffs, including the 15-minute Lambda cap on long crawls.

Serverless suits bursty, parallel jobs but struggles with long-running browser crawls, where managed runs help. Apify handles managed bursts without idle servers. Below you will find serverless scraping patterns.

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Frequently asked questions

Frequently Asked Questions

Simple HTTP scrapers work well on AWS Lambda, Google Cloud Functions, or Cloudflare Workers. Browser automation is harder due to binary size limits and cold start times, though AWS Lambda layers with Chromium exist. Apify Cloud is itself a serverless-like platform—actors spin up on demand, run, and terminate without server management.

Pay-per-invocation pricing works well for infrequent or bursty scraping jobs. No idle server costs. Automatic scaling handles traffic spikes. Serverless functions integrate naturally with event-driven architectures—trigger on S3 upload, SQS message, or API Gateway request. Deployment is simple compared to managing container fleets.

Execution time limits (15 minutes on Lambda) constrain long crawls. Cold starts add latency for time-sensitive jobs. Binary size limits make full Chromium deployments challenging. Stateless execution requires external queue and storage. For complex, stateful crawls, a persistent platform like Apify is simpler than stitching together Lambda, SQS, and S3.

Apify provides an end-to-end platform—no Lambda function deployment, no SQS configuration, no S3 bucket management. The Apify SDK handles queue management and storage. Lambda DIY typically costs less compute per invocation but requires significant infrastructure setup time. For teams without dedicated infrastructure engineers, Apify is usually more economical overall.