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Automating Dynamic Prerendering at Halodoc: A Data-Driven Approach to SEO and Faster Page Discovery

Halodoc replaced a manually maintained list of prerendered Angular routes with an automated pipeline driven by the Google Search Console API. A weekly Jenkins cron job queries GSC for the top-clicked pages over the last 7 days, filters them through a 'Smart Threshold' (top 10 per route category), and writes the results into a decoupled TypeScript constants file. Jenkins then opens an automated Merge Request for a quick engineer review before deployment. This approach reduced the lag between emerging search trends and site configuration from months to 7 days, cut manual engineering effort to under 5 minutes per cycle, and kept production builds completing in 70–90 seconds. The team also packaged the pipeline logic as a shareable Claude Code AI skill available in their open-source repository.

    #cicd#angular#seo
Jun 26•14m read time•From blogs.halodoc.io
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Table of contents
The Problem: Hardcoded Routes and the "Static" TrapThe Solution: A Data-Driven PipelineThe Challenge of ScaleThe Workflow ArchitectureThe Impact in NumbersBuilding Your Own: The Halodoc AI SkillConclusionReferenceJoin usAbout Halodoc
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Halodoc

HaloDoc is a healthcare technology platform that offers telemedicine services, online pharmacy, and ...

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