![]() ![]() On subsequent navigations, the static assets will already be in the cache. One thing to note here is that it helps only on first-time navigations. This is done for CSS and JavaScript assets, where the URLs can be retrieved ahead of time. With predictive prefetch, when a user navigates to the predicted page, the assets are already in the browser cache. So why don't pages in the flow help each other? That is the idea of predictive prefetch, where one page prefetches the static assets required for the next likely page. For example, the flow can be a navigation from the homepage to a search page to an item page. Predictive prefetch of static assets #Ī user session on eBay is not just one page. The "cut" here is the wasted image bytes sent to users. Previously the optimizations were up to the uploader, but now eBay enforces the rules within the tools, so all images uploaded will be optimized appropriately. eBay has a lot of hand-curated images, which are uploaded through various tools. Second, though eBay's listing images are heavily optimized (in both size and format), the same rigor did not apply for curated images (for example, the top module on the homepage). WebP images being served to supported browsers on. The search results page is the most image-heavy page at eBay, and they were already using WebP, but not in a consistent pattern. eBay did two optimizations for images.įirst, eBay standardized on the WebP image format for search results across all platforms, including iOS, Android, and supported browsers. Images are one of the largest contributors to page bloat. The "cut" here is the time spent by services to display relevant content. The outcome: users get to see above-the-fold content quicker. The below-the-fold data is sent in a later chunk or lazy-loaded. Once data is ready, it is instantly flushed. When a request comes to these services, they work on getting the data for above-the-fold content immediately, by calling other upstream services in parallel. eBay then introduced the concept of the critical path for Experience Services. This layer is specifically designed to be view- or device-based, rather than entity-based like item, user, or order. iOS/Android/desktop and web apps are aware of this, but what about services? eBay's service architecture has a layer called Experience Services, which the frontends (platform-specific apps and web servers) talk to. The content above-the-fold is more critical than something below-the-fold. Not every pixel on the screen is equally important. Critical path optimization for above-the-fold content # The "cut" here is the wasted bytes in the response payload. Teams usually procrastinated on this cleanup activity, but you'd be surprised by how much eBay saved. This added up over time and became a performance bottleneck. Previously, with every new feature, eBay kept increasing the payload of their responses, without cleaning up what was unused. eBay reduced their text payloads by trimming all the unused and unnecessary bytes of JavaScript, CSS, HTML, and JSON responses served to users. One way to make sites fast is to simply load less code. Reduce payload across all text resources # This post covers topics that are relevant to the web developer community at large, rather than eBay-specific topics. The improvements eBay made were possible due to the reduction or "cuts" (in the size and time) of various entities that take part in a user's journey. There's still more work ahead but here's eBay's learnings so far. Chrome User Experience Report data for First Contentful Paint and First Input Delay for the origin. …and their Chrome User Experience Report data highlights these improvements, too. Through the adoption of Performance Budgets (derived after doing a competitive study with the Chrome User Experience Report) and a focus on key user-centric performance metrics, eBay was able to make significant improvements to site speed. ![]()
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