Bun as a JavaScript Runtime: Six Months Running It Alongside Node in Production
I moved our internal tooling to Bun cautiously, deliberately keeping Node.js running our actual production services, and let the two coexist long enough over six months to see where Bun genuinely earns its speed reputation and where Node's longer maturity still wins out for the things that matter most in production.
Package Installation Speed, the Most Immediate, Obvious Win
Running bun install on our monorepo, dependency installation completed dramatically faster than the equivalent npm or even pnpm install, a difference significant enough that it changed how willing developers were to do a clean install rather than working around a suspicious node_modules folder.
bun install
bun add zod
bun remove lodash
The All-in-One Toolkit Approach
Bun bundles a runtime, package manager, test runner, and bundler into a single binary, and for our internal tooling scripts specifically, this meant genuinely fewer separate dependencies and configuration files to maintain compared to assembling the equivalent Node-based toolchain from npm, Jest, and a separate bundler.
bun test
bun build ./src/index.ts --outdir ./dist
bun run ./scripts/deploy.ts
Native TypeScript Execution
Running TypeScript files directly without a separate compilation step or ts-node genuinely simplified our internal scripting workflow, removing a category of configuration friction, tsconfig quirks specifically for script execution, that had accumulated in our Node-based tooling over time.
Node.js Compatibility, Genuinely High But Not Complete
The overwhelming majority of our npm dependencies worked without modification under Bun, a genuinely impressive compatibility achievement given how much of the npm ecosystem assumes Node-specific behavior. We did hit a small number of packages relying on Node-specific native modules or less common APIs that either failed outright or behaved subtly differently, requiring either a patch or an alternative package.
Why We Haven't Moved Production Services Yet
Node's operational maturity, well-understood memory behavior under sustained load, extensive production monitoring tooling built specifically around it, and a much longer track record at genuine scale, still matters more for our production services than Bun's speed advantage, and we've deliberately treated production migration as a separate, more cautious decision from adopting Bun for tooling.
Test Runner Performance
Bun's built-in test runner, a genuine alternative to Jest, ran our existing test suite noticeably faster once migrated, and its Jest-compatible API meant the migration itself required minimal changes to existing test files, mostly just changing the import source and a handful of Jest-specific matcher edge cases.
import { test, expect } from "bun:test";
test("adds two numbers", () => {
expect(1 + 1).toBe(2);
});
Memory Usage Under Sustained Load
Running a genuinely long-lived internal service under Bun for an extended stress test, memory usage patterns looked reasonable but hadn't accumulated the years of real-world production hardening and known-issue documentation that Node's memory behavior under sustained, high-traffic load has, which is exactly the caution keeping us from a full production migration yet.
Ecosystem Maturity Around Deployment and Monitoring
Our existing production observability tooling, APM integrations, error tracking, log aggregation, is built with deep, well-tested Node.js support, and equivalent tooling for Bun, while improving, is genuinely newer and less battle-tested, a real practical consideration beyond the runtime's own capabilities.
My Actual Take After Six Months
For internal tooling, scripts, and development environments, Bun has been a genuine, measurable improvement we've fully adopted without reservation. For production services specifically, I'm watching the ecosystem mature rather than migrating yet, and I'd recommend the same cautious, staged approach to any team seriously considering it, rather than a full, immediate production cutover based purely on benchmark numbers.
