Ship scraping infrastructure like software — trigger actors, sync datasets, and deploy crawlers straight from your GitLab pipelines.
Modern data engineering teams treat web scraping as first-class infrastructure. Yet most teams still manage Apify actors and GitLab pipelines in complete isolation — manually triggering runs, copying dataset exports, and deploying actor code without any automated gate. Neotask bridges that gap, letting you orchestrate Apify and GitLab as a unified scraping CI/CD system.
With Neotask, a merge to your main branch in GitLab can automatically kick off an Apify actor run — no custom webhook scripts required. Define the actor ID, input parameters, and dataset destination once; Neotask handles the trigger, monitors the run status, and reports back to the pipeline job. Failed actor runs fail the pipeline stage, giving your team a real quality gate on scraped data before it reaches downstream consumers.
Once an Apify actor completes, Neotask can push the resulting dataset — in JSON, CSV, or JSONL format — directly to a GitLab repository as a committed artifact. This creates a reproducible, versioned record of every crawl tied to the exact pipeline run that produced it. Teams working on Automated Web Testing Pipelines can use this to snapshot reference data, compare crawl outputs across releases, or feed structured datasets into downstream test fixtures.
Neotask monitors GitLab repositories for changes to actor source code. When a push is detected to a designated branch, it triggers a redeployment of the corresponding Apify actor — keeping your production crawlers in sync with your codebase without manual uploads. This closes the loop on Scraping Deployment Automation: write code, push to GitLab, and let the pipeline handle the rest.
Whether you're running competitive intelligence scrapers, building data pipelines for ML training sets, or maintaining automated web testing infrastructure, Neotask removes the manual handoff between your GitLab workflows and your Apify actors. Every crawl is traceable, every deployment is automated, and every dataset output is versioned.
Stop treating web scraping as a side process. With Neotask connecting Apify and GitLab, it becomes a full participant in your development lifecycle.
Yes. Neotask integrates with both Apify and GitLab so that a GitLab pipeline job can trigger an Apify actor run, wait for it to complete, and pass or fail the stage based on the actor's exit status. This lets you enforce data quality gates directly in your CI/CD workflow without writing custom webhook or polling scripts.
After an Apify actor run completes, Neotask can retrieve the resulting dataset and commit it to a specified GitLab repository and branch as a versioned artifact. This gives you a full audit trail of crawl outputs tied to specific pipeline runs, which is especially useful for automated web testing pipelines that rely on scraped reference data.
Yes. Neotask can watch a GitLab repository for pushes to a configured branch and automatically redeploy the corresponding Apify actor when actor source code changes are detected. This removes the manual upload step and keeps your production crawlers in sync with the latest code in your repository.
Connect Apify and GitLab in Neotask and turn every GitLab push into a fully automated scraping deployment — no scripts, no manual triggers.
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