Micro-frontend architecture support solutions

The micro-frontend architecture achieves modular development by splitting large frontend applications into independent sub-applications. Vite.js, as a modern build tool, offers multiple micro-frontend implementation solutions. The Module Federation solution supports runtime dynamic loading and dependency sharing. The iframe solution provides stable isolation but requires performance considerations. The Custom Elements solution leverages Web Components to achieve technology stack independence and style isolation. The build-time composition solution determines dependency relationships during compilation. Route-level integration enables on-demand loading of sub-applications. Style isolation can be implemented using CSS Modules or Scoped CSS. State management employs an event bus or shared state libraries. Performance optimizations include dependency pre-building and dynamic imports. Debugging requires configuring Sourcemaps and error boundaries. Deployment supports independent or federated approaches. Testing should consider integration tests and contract tests to ensure system stability.

Server-side rendering (SSR) integration solution

Vite.js, as a modern front-end build tool, natively supports server-side rendering (SSR), enabling the effortless construction of isomorphic applications to enhance first-screen performance and SEO optimization. Its core principle is based on ESM features, encompassing both server-side and client-side builds. Basic integration requires configuring the server entry file and client-side hydration logic. Routing and data prefetching are key aspects of SSR, while state management requires attention to synchronization issues. Build and deployment demand special configurations. Performance optimization can leverage component caching and streaming rendering. Common challenges include cross-request pollution and client-side hydration failures. Advanced integration supports micro-frontends and edge rendering solutions. During debugging, SSR mode can be enabled, and testing strategies should cover both server-side rendering and client-side hydration. In terms of ecosystem tools, it can integrate with solutions like Nuxt.js or vite-plugin-ssr.

Performance monitoring and measurement methods

As a modern front-end build tool, Vite.js may face performance issues as project scale grows, requiring systematic optimization and monitoring. Core optimization strategies include: dependency pre-bundling optimization by precisely controlling included/excluded dependencies to reduce build time; advanced code splitting using dynamic imports and custom chunking strategies to minimize main bundle size; resource handling techniques like modern image format conversion to reduce asset size. The performance monitoring system covers build-time metric collection through visualization tools to analyze module size and compression efficiency, and runtime performance measurement using Navigation Timing API to capture real-user data. Continuous monitoring solutions involve configuring PWA plugins for offline metric collection. Advanced debugging methods include memory analysis and component-level performance tracing. Build environment tuning involves multi-environment differentiated configurations and compiler parameter adjustments, targeting modern browsers to reduce code size and avoid unnecessary polyfill injection.

Configuration tips for modern builds

As a next-generation front-end build tool, ViteJS leverages the browser's native ESM features to deliver a fast development experience. Performance optimization must be considered from both development and production perspectives. During development, it utilizes ESM's on-demand compilation feature, while in production, it relies on Rollup for bundling optimizations. The development environment can be enhanced through dependency pre-bundling and HMR optimizations for efficiency. In production, strategies like code splitting and resource compression are employed. Advanced techniques include on-demand component loading, WASM processing, and cache optimization. Modern build features support top-level `await` and Worker thread integration. Build analysis tools generate visual reports, and environment variable handling enables multi-environment configurations. SSR optimizations involve build configurations and client-side hydration. Image processing covers compression and SVG componentization. Browser compatibility is ensured through configuration and on-demand Polyfill introduction. Build performance monitoring includes time-consuming analysis and memory usage tracking.

Optimization of media resources such as images

Modern web applications heavily utilize media resources such as images and videos, which often account for the bulk of page load time. Unoptimized media resources can lead to slow first-screen loading, wasted bandwidth, and degraded user experience. Vite, as a next-generation front-end build tool, offers a variety of out-of-the-box optimization techniques, including built-in image processing capabilities, automatic conversion of small images to base64, and generating hashed filenames. Vite also supports image format conversion through plugins, such as WebP and AVIF, significantly reducing file sizes. Additionally, it enables responsive image handling by generating multiple-sized versions for dynamic loading based on viewport size. The article details lazy loading implementation methods, including the native `loading` attribute and the Intersection Observer API, as well as sprite sheet optimization to merge small icons and reduce request counts. For video resources, it recommends prioritizing the WebM format and provides preloading strategies to dynamically load content based on network conditions. Furthermore, it covers CDN acceleration, dynamic importing of large-sized resources, and best practices for cache strategies. Finally, it introduces performance monitoring methods to help developers analyze and optimize resource loading performance.

Optimized import methods for third-party libraries

Vite.js, as a modern front-end build tool, leverages native ESM features to provide various optimization methods for introducing third-party libraries. On-demand loading of component libraries (e.g., Ant Design Vue with the unplugin-vue-components plugin) enables automatic tree-shaking to reduce bundle size. Dynamic imports for non-critical libraries, combined with code splitting, improve first-screen performance. Using CDN external links for large libraries sets them as external dependencies. Opting for lightweight alternatives (e.g., date-fns instead of Moment.js, lodash-es instead of full lodash) further reduces size. Pre-bundling optimizations via the `optimizeDeps` configuration ensure efficiency. Tree-shaking-friendly imports prioritize ESM format. Version locking and dependency analysis are facilitated by vite-plugin-visualizer. Browser caching strategies utilize hashed filenames. Server-side rendering distinguishes between client and server imports. For CSS-in-JS libraries, critical CSS extraction is enabled. Atomic CSS frameworks like UnoCSS are recommended.

Monitoring and analyzing build performance

Webpack build performance is crucial for development efficiency and deployment speed. The build process can slow down due to misconfiguration, excessive dependencies, or inefficient plugins. Monitoring and analysis tools can help identify bottlenecks and optimize performance. Use `speed-measure-webpack-plugin` to measure the duration of each phase, and `webpack-bundle-analyzer` to generate a dependency treemap, focusing on oversized files, duplicate dependencies, and unnecessary polyfills. Leverage Node.js performance hooks to record detailed timestamps. Key optimization metrics include initial compilation time, incremental compilation time, output size, and module count. Implementing caching strategies can significantly improve secondary build speeds. For large projects, use `thread-loader` for parallel processing and dynamic imports to split code, reducing the main bundle size. Integrate CI systems to automate metric collection and monitor long-term build trends. Adjust resolution strategies to reduce search scope, analyze memory usage to detect leaks and frequent GC, and review plugin performance to address synchronous operations and unnecessary traversals. Separate development and production environment configurations, and handle build warnings such as module merge failures and oversized bundles. Use `statoscope` to analyze third-party dependencies, checking for multiple versions and unused files. Extend `stats` data to collect custom metrics and use hooks to gather additional build information.

Key points for server-side rendering optimization

Key optimization points for server-side rendering (SSR) include code splitting and lazy loading through Webpack's import syntax and loadable components to achieve component-level splitting and reduce initial load. Memory caching strategies employ LRU to cache frequently accessed pages and avoid duplicate rendering. Build configurations must distinguish between client and server sides, using webpack-node-externals to exclude Node modules. Streaming rendering reduces TTFB time. Performance monitoring collects key metric data. Data prefetching prevents client-side duplicate requests, while window.INITIAL_STATE synchronizes state. Static resource optimizations like CSS inlining reduce request counts. Error handling implements SSR error boundaries and fallback solutions. Compile-time optimizations remove PropTypes and server-specific configurations. Adjust Node parameters and enable Gzip. Continuous integration optimizations generate analysis reports and Docker layer caching.

Long cache optimization solution

Long-term caching optimization is a key strategy in Webpack builds to enhance application loading performance. By properly configuring filename hashing, code splitting, and module identifiers, it ensures that user browsers cache as many static resources as possible, reducing redundant downloads. Webpack provides three hash generation methods, with `contenthash` being the recommended choice—it only changes when file content is modified. Module identifier stabilization is achieved using `HashedModuleIdsPlugin`. Runtime code is split into separate files, while third-party libraries employ dedicated chunks for caching. Dynamic import optimization involves using magic comments to name dynamically imported modules. Manifest file handling ensures correct generation and referencing. Content Security Policy (CSP) integration requires proper `Cache-Control` headers and server-side caching strategies. Version file automation creates version marker files to help clients detect updates. Preloading critical resources with `preload` and `prefetch` optimizes resource loading. Module dependency analysis leverages `webpack-bundle-analyzer` to identify optimization opportunities. Persistent cache configuration enables filesystem caching to improve build performance. Hash length optimization balances hash length and collision probability. Server-side rendering (SSR) compatibility addresses resource references in SSR environments. Resource preloading strategies are based on usage analysis. Multi-environment configurations distinguish caching strategies between development and production. Resource fingerprint verification ensures integrity. Build information injection embeds build details for debugging. Resource loading monitoring implements performance tracking for loaded resources.

On-demand loading and lazy loading of routes

On-demand loading is an optimization technique that loads specific resources only when needed. Route lazy loading is a concrete implementation of this, where route components are split into independent code chunks and loaded only when the corresponding route is accessed. Webpack supports code splitting, including three methods: entry points, preventing duplication, and dynamic imports, with dynamic imports being the most commonly used. Frameworks like React, Vue, and Angular all support route lazy loading. Webpack configuration optimizations include setting output filenames, code splitting rules, etc. Preloading and prefetching can further enhance performance. In practice, issues like third-party library separation, route-based grouping, critical CSS extraction, etc., need to be addressed. Common challenges include loading state management, chunk naming, and duplicate dependencies. Advanced applications involve user behavior prediction, server-side rendering, and WebWorker performance monitoring. Analysis tools, browser caching strategies, and leveraging long-term caching are essential. Modern improvements include using ES modules.