Before optimizing, you need to identify what's slowing down your Jekyll builds. The build process involves multiple stages: reading files, processing Liquid templates, converting Markdown, executing plugins, and writing the final HTML output. Each stage can become a bottleneck depending on your site's structure and complexity.
Use Jekyll's built-in profiling to identify slow components. Run `jekyll build --profile` to see a detailed breakdown of build times by file and process. Look for patterns: are particular collections taking disproportionate time? Are specific includes or layouts causing delays? Large sites with hundreds of posts might slow down during pagination or archive generation, while image-heavy sites might struggle with asset processing. Understanding these patterns helps you prioritize optimization efforts where they'll have the most impact.
Monitor your build times consistently by adding automated timing to your GitHub Actions workflows. This helps you track how changes affect build performance over time and catch regressions before they become critical. Also pay attention to memory usage, as GitHub Pages has limited memory allocation. Memory-intensive operations like processing large images or complex data transformations can cause builds to fail even within the time limit.
Liquid template processing is often the primary bottleneck in Jekyll builds. Complex logic, nested includes, and inefficient loops can dramatically increase build times. Optimizing your Liquid templates requires both strategic changes and attention to detail.
Reduce or eliminate expensive Liquid operations like `where` filters on large collections, multiple nested loops, and complex conditional logic. Instead of filtering large collections multiple times in different templates, precompute the filtered data in your configuration or use includes with parameters to reuse processed data. For example, instead of having each page calculate related posts independently, generate a related posts mapping during build and reference it where needed.
Optimize your include usage by minimizing nested includes and passing parameters efficiently. Each `include` statement adds processing overhead, especially when nested or used within loops. Consider merging frequently used include combinations into single files, or using Liquid `capture` blocks to store reusable HTML fragments. For content that changes rarely but appears on multiple pages, like navigation or footer content, consider generating it once and including it statically rather than processing it repeatedly for every page.
Jekyll's asset handling can significantly impact both build times and site performance. Unoptimized images, redundant CSS/JS processing, and inefficient asset organization all contribute to slower builds and poorer user experience.
Implement an intelligent image strategy that processes images before they enter your Jekyll build pipeline. Use external image optimization tools or services to resize, compress, and convert images to modern formats like WebP before committing them to your repository. For images that need dynamic resizing, consider using Cloudflare Images or another CDN-based image processing service rather than handling it within Jekyll. This reduces build-time processing and ensures optimal delivery to users.
Simplify your CSS and JavaScript pipeline by minimizing the use of build-time processing for assets that don't change frequently. While SASS compilation is convenient, precompiling your main CSS files and only using Jekyll processing for small, frequently changed components can speed up builds. For complex JavaScript bundling, consider using a separate build process that outputs final files to your Jekyll site, rather than relying on Jekyll plugins that execute during each build.
Incremental building only processes files that have changed since the last build, dramatically reducing build times for small updates. While GitHub Pages doesn't support Jekyll's native incremental build feature, you can implement similar strategies in your development workflow and through smart content organization.
Use Jekyll's incremental build (`--incremental`) during local development to test changes quickly. This is particularly valuable when working on style changes or content updates where you need to see results immediately. For production builds, structure your content so that frequently updated sections are isolated from large, static sections. This mental model of incremental building helps you understand which changes will trigger extensive rebuilds versus limited processing.
Implement a smart deployment strategy that separates content updates from structural changes. When publishing new blog posts or page updates, the build only needs to process the new content and any pages that include dynamic elements like recent post lists. Major structural changes that affect many pages should be done separately from content updates to keep individual build times manageable. This approach helps you work within GitHub Pages' build constraints while maintaining an efficient publishing workflow.
Plugins extend Jekyll's functionality but can significantly impact build performance. Each plugin adds processing overhead, and poorly optimized plugins can become major bottlenecks. Smart plugin management balances functionality with performance considerations.
Audit your plugin usage regularly and remove unused or redundant plugins. Some common plugins have lighter-weight alternatives, or their functionality might be achievable with simple Liquid filters or includes. For essential plugins, check if they offer performance configurations or if they're executing expensive operations on every build when less frequent processing would suffice.
Consider replacing heavy plugins with custom solutions for your specific needs. A general-purpose plugin might include features you don't need but still pay the performance cost for. A custom Liquid filter or generator tailored to your exact requirements can often be more efficient. For example, instead of using a full-featured search index plugin, you might implement a simpler solution that only indexes the fields you actually search, or move search functionality entirely to the client side with pre-built indexes.
Optimizing your GitHub Pages deployment workflow ensures reliable builds and fast updates. This involves both Jekyll configuration and GitHub-specific optimizations that work within the platform's constraints.
Configure your `_config.yml` for optimal GitHub Pages performance. Set `future: false` to avoid building posts dated in the future unless you need that functionality. Use `limit_posts: 10` during development to work with a subset of your content. Enable `incremental: false` explicitly since GitHub Pages doesn't support it. These small configuration changes can shave seconds off each build, which adds up significantly over multiple deployments.
Implement a branch-based development strategy that separates work-in-progress from production-ready content. Use your main branch for production builds and feature branches for development. This prevents partial updates from triggering production builds and allows you to use GitHub Pages' built-in preview functionality for testing. Combine this with GitHub Actions for additional optimization: set up actions that only build changed sections, run performance tests, and validate content before merging to main, ensuring that your production builds are fast and reliable.
By systematically optimizing your Jekyll setup, you transform a potentially slow and frustrating build process into a smooth, efficient workflow. Fast builds mean faster content iteration and more reliable deployments, while optimized output ensures your visitors get the best possible experience. The time invested in Jekyll optimization pays dividends every time you publish content and every time a visitor accesses your site.
Fast builds are useless if your content isn't engaging. Next, we'll explore how to leverage Jekyll's data capabilities to create dynamic, data-driven content experiences.