Avoiding Memory Leaks in Node Renderer SSR

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Why Memory Leaks Happen in the Node Renderer

The Node Renderer reuses V8 VM contexts across requests for performance. Your server bundle is loaded once into a VM context and reused for every SSR request until the worker restarts.

This means module-level state persists across all requests for the lifetime of the worker process. Code that works fine in the browser — where each page navigation creates a fresh JavaScript context — can silently leak memory on the server.

Browser:  page load → JS context created → user navigates → context destroyed ✓
Node SSR: worker starts → JS context created → request 1, 2, 3, ... 10,000 → same context ✗

Migrating from ExecJS? ExecJS creates a fresh JavaScript context per render, so module-level state is automatically cleared. When you switch to the Node Renderer, code that "worked fine" before may start leaking because the same context is now reused across requests.

Common Leak Patterns

1. Module-level caches without eviction

Any module-level Map, Set, plain object, or array used as a cache will grow unboundedly because the module is loaded once and reused across all requests.

Leaks:

// cache lives forever — entries are never removed
const cache = new Map();

export function buildSignedUrl(imageUrl, width, height) {
  const key = `${imageUrl}-${width}-${height}`;
  if (cache.has(key)) return cache.get(key);

  const result = computeHmacSignature(imageUrl, width, height);
  cache.set(key, result); // grows with every unique input across all requests
  return result;
}

Fix: Add a max size with LRU eviction, clear the cache periodically, or remove it if the computation is cheap:

import { LRUCache } from 'lru-cache';

const cache = new LRUCache({ max: 1000 }); // bounded — evicts oldest entries

2. Lodash _.memoize and similar unbounded memoization

Lodash's _.memoize uses an unbounded Map internally. At module scope, it accumulates entries across all SSR requests forever.

Leaks:

import _ from 'lodash';

// Each unique argument adds a permanent entry
export const formatLocation = _.memoize((city, state) => {
  return `${city}, ${state}`.toLowerCase().replace(/\s+/g, '-');
});

Fix: Use a bounded LRU cache, or avoid memoization at module scope for functions called with diverse inputs during SSR.

3. Module-level Sets or arrays that accumulate

Leaks:

const SENT_EVENTS = new Set(); // grows with every unique event

export function trackEvent(event) {
  if (SENT_EVENTS.has(event.key)) return;
  SENT_EVENTS.add(event.key); // never removed
  sendToAnalytics(event);
}

Fix: Don't track client-side-only state (like analytics) during SSR. Guard with a server-side check:

export function trackEvent(event, railsContext) {
  if (railsContext.serverSide) return; // skip during SSR
  // ... client-only tracking
}

4. Third-party libraries with internal caches

Some libraries maintain internal caches or singletons that grow in SSR:

• Styled-components / Emotion: CSS-in-JS libraries can accumulate style sheets. Use ServerStyleSheet (styled-components) or extractCritical (Emotion) and reset between renders
• Apollo Client: GraphQL cache grows if not reset between renders
• MobX: Observer components can leak if useStaticRendering is not enabled (mobx-react < v7)
• Amplitude / analytics SDKs: Event queues accumulate if initialized during SSR
• i18n libraries: Message catalogs may cache translations

Fix: Check if your libraries have SSR-specific configuration. Many provide a resetServerContext() or similar function. Initialize analytics and tracking libraries only on the client side.

5. Event listeners at module scope

If code registers event listeners at module scope during SSR, they accumulate across requests:

Leaks:

// Every SSR render adds another listener — they're never removed
process.on('unhandledRejection', (err) => {
  reportError(err);
});

Fix: Register listeners once (outside the render path), or guard with a flag:

let listenerRegistered = false;
if (!listenerRegistered) {
  process.on('unhandledRejection', (err) => reportError(err));
  listenerRegistered = true;
}

Diagnosing Memory Leaks

1. Monitor worker RSS over time

Watch the worker process memory. If RSS grows monotonically without plateauing, you have a leak:

# Check worker memory every 10 seconds
while true; do
  ps -o rss= -p <worker-pid> | awk '{printf "%.1f MB\n", $1/1024}'
  sleep 10
done

2. Take V8 heap snapshots

Use v8.writeHeapSnapshot() to capture heap state before and after load, then compare in Chrome DevTools:

// In your renderer config, add a way to trigger snapshots:
const v8 = require('v8');

process.on('SIGUSR2', () => {
  if (global.gc) global.gc(); // force GC first
  const filename = v8.writeHeapSnapshot();
  console.log(`Heap snapshot written to ${filename}`);
});

Then send kill -USR2 <worker-pid> at different times and compare the snapshots in Chrome DevTools (Memory tab → Load).

3. Use --inspect for live profiling

Start the renderer with the --inspect flag to connect Chrome DevTools:

node --inspect node-renderer.js

Open chrome://inspect in Chrome, take heap snapshots, and use the "Comparison" view to see what objects accumulated between snapshots.

Mitigations

Set --max-old-space-size

Without this flag, V8 reads the container's memory limit and sets a very large heap ceiling. This causes V8 to defer garbage collection, amplifying any existing leaks.

Always set this for production:

NODE_OPTIONS=--max-old-space-size=1536 node node-renderer.js

Size it based on your container memory and worker count. For example, with 4GB container memory and 3 workers: 4096 / 3 ≈ 1365, round to 1400.

Enable worker rolling restarts

Rolling restarts are the primary safety net against memory leaks. They periodically kill and restart workers, reclaiming all accumulated memory:

const config = {
  // Restart all workers every 45 minutes
  allWorkersRestartInterval: 45,
  // Stagger individual restarts by 6 minutes to avoid downtime
  delayBetweenIndividualWorkerRestarts: 6,
  // Force-kill workers that don't restart within 30 seconds
  gracefulWorkerRestartTimeout: 30,
};

Important: Both allWorkersRestartInterval and delayBetweenIndividualWorkerRestarts must be set for restarts to be enabled. See JS Configuration for details.

Size restart intervals for your traffic

The restart interval should be short enough that leaked memory doesn't fill the container:

• Low traffic / small bundles: 60–120 minutes may be fine
• High traffic / large bundles: 15–30 minutes
• If you're seeing OOMs: reduce the interval until stable, then investigate the root cause

The Browser vs. Server Mental Model

When writing code that runs during SSR, always ask: "If this module-level variable is never reset, will it grow with each request?"

Pattern	Browser	Node Renderer
const cache = {} at module scope	Cleared on navigation	Persists forever
new Set() at module scope	Cleared on navigation	Persists forever
_.memoize(fn) at module scope	Cleared on navigation	Persists forever
React component state (useState)	Per-component lifecycle	Created and collected per render (OK)
useEffect callbacks	Runs on client	Skipped during SSR (OK)
useMemo inside components	Per-component lifecycle	Runs during SSR but result is per-render (OK)

The rule of thumb: module-level mutable state is the danger zone. React component-level state and hooks are fine because React creates and discards them per render.

Audit Checklist

Use this to scan your server bundle code for potential leaks:

• Search for module-level new Map(), new Set(), const cache = {}, [] — are any of these unbounded?
• Search for _.memoize or memoize( at module scope — are they called with diverse SSR inputs?
• Search for setInterval without corresponding clearInterval — timers leak if not cleaned up (only relevant when stubTimers: false)
• Search for process.on( or .addEventListener( at module scope — listeners accumulate if added per render
• Check third-party libraries for SSR cleanup functions (resetServerContext, useStaticRendering, etc.)
• Verify NODE_OPTIONS=--max-old-space-size=<MB> is set in production
• Verify allWorkersRestartInterval and delayBetweenIndividualWorkerRestarts are both configured