detect-ssr-leak

Testing & Quality

Detect server-side memory leaks in Node.js SSR services. Use when user asks to "check for memory leak", "detect leak", "SSR memory leak", "内存泄漏", or wants to diagnose growing memory usage on a Node.js server. TRIGGER when user mentions memory leak detection, especially for SSR/Vue/React server-side rendering.

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Detect SSR Memory Leak

Detect server-side Node.js memory leaks for SSR rendering services using a three-phase approach: external RSS monitoring, inline heap instrumentation, and CDP heap snapshot comparison.

Prerequisites

A running Node.js SSR server (Koa, Express, etc.)
The target URL (e.g., http://localhost:7102/login)
If using Phase 2, a controller module where the diagnostic endpoint can be added

Phase 1: External RSS Monitoring (Quick Screening)

Zero code changes. Detects whether a leak exists by monitoring process RSS from outside.

Steps

Find worker PIDs:

ps -eo pid,ppid,command | grep "node.*bootstrap" | grep -v grep

Identify the master PID (ppid of others) and worker PIDs.

Create and run the external monitoring script. Use the template at ${CLAUDE_SKILL_DIR}/scripts/external-monitor.mjs:

# Copy and edit the script, set WORKER_PIDS and TARGET_URL
cp ${CLAUDE_SKILL_DIR}/scripts/external-monitor.mjs /tmp/ssr-leak-external.mjs
# Edit WORKER_PIDS and TARGET_URL in the script, then run:
node /tmp/ssr-leak-external.mjs

Interpret results:

RSS slope < 1 KB/request → Normal (cache warmup)
1-5 KB/request → Suspicious, proceed to Phase 2
> 5 KB/request → Strong leak signal, proceed to Phase 2

Phase 2: Inline Heap Instrumentation (Precise Measurement)

Add a temporary diagnostic controller to read process.memoryUsage() and v8.getHeapStatistics() from within the Node.js process.

Steps

Add the ControllerMemoryDiag controller to an existing module. Use the template at ${CLAUDE_SKILL_DIR}/templates/memoryDiag.ts. Key endpoints:

GET /stats — Returns process.memoryUsage() + v8.getHeapStatistics() + pid
POST /gc — Forces GC via node:inspector Session, returns post-GC stats
GET /heapSnapshot — Writes .heapsnapshot file via v8.writeHeapSnapshot()

Mark all methods as public/no-auth so they can be called without authentication.
Verify the endpoint works:

curl -s http://localhost:<PORT>/api/<module>/memoryDiag/stats | python3 -m json.tool

Run the inline heap measurement script. Use the template at ${CLAUDE_SKILL_DIR}/scripts/inline-heap.mjs:

cp ${CLAUDE_SKILL_DIR}/scripts/inline-heap.mjs /tmp/ssr-leak-inline.mjs
# Edit STATS_URL, GC_URL, LOGIN_URL, then run:
node /tmp/ssr-leak-inline.mjs

Key metrics to watch:

Metric	Normal	Suspicious	Confirmed Leak
`heapUsed` after GC	Stable	1-5 KB/req	>5 KB/req, never converges
`number_of_native_contexts`	1-3	Slowly growing	Monotonically increasing
`number_of_detached_contexts`	0 or constant	Growing	V8 contexts not collected

Phase 3: CDP Heap Snapshot Comparison (Root Cause Identification)

If Phase 2 confirms a leak, use Chrome DevTools Protocol to take and compare heap snapshots, identifying the exact leaking object types.

Steps

Enable inspector on the target worker:

# Find worker PID, then send SIGUSR1
kill -USR1 <WORKER_PID>

Verify inspector is available:

curl -s http://127.0.0.1:9229/json

Run the CDP streaming heap analysis script. Use the template at ${CLAUDE_SKILL_DIR}/scripts/cdp-heap-analyze.mjs:

cp ${CLAUDE_SKILL_DIR}/scripts/cdp-heap-analyze.mjs /tmp/ssr-leak-cdp.mjs
# Install ws if needed: cd /tmp && npm install ws
# Edit TARGET_URL, then run:
node /tmp/ssr-leak-cdp.mjs

The script will:

Connect to the worker via CDP WebSocket
Take a baseline heap snapshot after GC
Send load requests to the target URL
Take a post-load heap snapshot after GC
Stream-parse both snapshots and compare object counts/sizes by type

Interpret the V8 node type mapping:

type_0 = hidden        type_5 = closure           type_10 = concatenated string
type_1 = object        type_6 = regexp            type_11 = sliced string
type_2 = array         type_7 = number            type_12 = symbol
type_3 = string        type_8 = native            type_13 = bigint
type_4 = code          type_9 = synthetic         type_14 = object shape

Common SSR leak patterns by type:

object (type_1) growth → Vue/React app instances not unmounted, component trees retained
closure (type_5) growth → Reactive effects (watch/computed/effect), event handlers, _createPerformAction closures capturing this
string (type_3) growth → Template compile results, property names, module source text retained by object references
array (type_2) growth → Reactive dependency tracking arrays, listener lists

Cluster Mode Handling

If the server runs in cluster mode (multiple workers), requests distribute across workers. Two strategies:

Single worker mode (recommended): Restart with META_MODE=production SERVER_WORKERS=1 (or equivalent env vars) for clean measurements
Per-PID tracking: The diagnostic endpoint returns pid, group measurements by PID in the analysis script

Known SSR Leak Suspects

When analyzing, check these common root causes:

Vue app instance not unmounted: createSSRApp() creates app instances that must be unmounted after renderToString(). Missing app.unmount() leaks the entire component tree.
Dynamic import() with cache-busting nonce: Each unique URL creates a new V8 module record. Old modules may never be GC'd.
Closures capturing request context: _createPerformAction or similar closures that capture this (bean/service instances) prevent the entire request context from being GC'd.
Unbounded caches: Caches keyed by variable data (host, locale) that grow without TTL or size limits.
Event listener accumulation: Listeners added per-request on global objects that are never removed.

Cleanup

After analysis, remember to:

Remove the ControllerMemoryDiag from the codebase (it's a diagnostic tool, not production code)
Delete temporary heap snapshot files from /tmp/
If inspector was enabled via SIGUSR1, restart the server to disable it

Arguments

If the user provides arguments, parse them as:

$1 or $ARGUMENTS — Target URL (default: ask the user)
If no URL provided, ask: "What is the target URL to test for memory leaks?"

Report Format

After completing the analysis, present results in this format:

## Memory Leak Detection Results

### Phase X: [method name]

**Verdict:** PASS / SUSPICIOUS / LEAK DETECTED

| Metric | Before | After | Delta |
|--------|--------|-------|-------|
| heapUsed | X MB | Y MB | +Z KB/request |
| ... | ... | ... | ... |

### Top Leaking Types (if Phase 3)
[table of object/closure/string growth]

### Root Cause Analysis
[analysis of why the leak is happening, referencing specific code paths]

### Recommendations
[specific code changes to fix the leak]