LCP 최적화 완벽 가이드: 2026년 로딩 성능 개선의 모든 것
LCP(Largest Contentful Paint) 최적화의 모든 것. TTFB부터 fetchpriority, AVIF 이미지, Speculation Rules API까지 2026년 최신 기법으로 로딩 성능을 극적으로 개선하는 실전 가이드입니다.
Daniel started in performance work on the SRE side. He spent six years at Spotify on the Web Player team, where he owned the TTI regression budget for the desktop web app and built the internal dashboard that flagged perf regressions per PR before merge. He left in 2023 to join a small consultancy doing performance audits for fintech and travel companies, mostly in the UK and Nigeria. His subspecialty is server-side rendering tradeoffs: when streaming SSR actually helps, when it makes things worse on flaky 4G, and the real numbers behind React Server Components for content-heavy sites. He's a heavy Playwright user for perf testing, mistrusts most npm dependencies on principle, and is currently writing a small Rust tool to diff WebPageTest waterfalls across deploys. Outside of work he coaches a junior dev meetup in Manchester.
LCP(Largest Contentful Paint) 최적화의 모든 것. TTFB부터 fetchpriority, AVIF 이미지, Speculation Rules API까지 2026년 최신 기법으로 로딩 성능을 극적으로 개선하는 실전 가이드입니다.