Cloudflare Workers turned eight in 2025 without slowing down: it now ships D1 for databases, R2 for egress-free storage, Durable Objects for distributed state, and Workers AI for running models without managing GPUs. It remains the fastest option for edge logic; for large in-memory processes or strict global consistency, other platforms fit better.
WASI 0.2 reached GA in January 2024, bringing WebAssembly's Component Model into production: typed WIT interfaces that let Rust, Go, and JavaScript code compose without manual glue code. That shift makes edge functions with sub-1 ms cold start, secure plugins, and untrusted-code sandboxing viable today, though it does not replace containers for traditional apps.
SQLite in production is more viable than most teams assume. WAL mode removes read contention, Litestream replicates the WAL to S3 in near-realtime, and LiteFS adds multi-node replication. Without a separate database server, apps like Tailscale and PocketBase already do this in production. This article explains when it makes sense and its real limits.
Deno Deploy is the serverless-edge platform from the team that built Deno: native TypeScript without a transpile step, standard Web APIs, and global deployment to ~35 regions. Cold start runs ~50ms vs Cloudflare Workers (~5ms). Best for lightweight APIs and Fresh/Astro SSR; less ideal when your project needs the full Cloudflare infrastructure stack.
WebAssembly is moving beyond the browser through WASI, the standard system interface, and the component model, which defines declarative WIT interfaces so modules written in different languages can compose with each other. Cold start lands around 1 ms versus roughly 500 ms for a container, a key difference for serverless and edge computing teams.
4 min2384.3
We use first- and third-party cookies to analyze site traffic. You can accept them, reject them, or configure your choice.
Learn more about cookies
Cookie preferences
NecessaryEssential for the site to work. Always on.
AnalyticsHelp us understand how the site is used (Google Analytics).