Merge branch 'fix/docker' into develop

.gitignore

@@ -271,6 +271,8 @@ continue_config.json
 CLAUDE_MONITOR.md
 CLAUDE.md
 
+.claude/
+
 tests/**/test_site
 tests/**/reports
 tests/**/benchmark_reports
@@ -282,3 +284,14 @@ docs/apps/linkdin/debug*/
 docs/apps/linkdin/samples/insights/*
 
 scripts/
+
+
+# Databse files
+*.sqlite3
+*.sqlite3-journal
+*.db-journal
+*.db-wal
+*.db-shm
+*.db
+*.rdb
+*.ldb

deploy/docker/STRESS_TEST_PIPELINE.md

@@ -0,0 +1,241 @@
+# Crawl4AI Docker Memory & Pool Optimization - Implementation Log
+
+## Critical Issues Identified
+
+### Memory Management
+- **Host vs Container**: `psutil.virtual_memory()` reported host memory, not container limits
+- **Browser Pooling**: No pool reuse - every endpoint created new browsers
+- **Warmup Waste**: Permanent browser sat idle with mismatched config signature
+- **Idle Cleanup**: 30min TTL too long, janitor ran every 60s
+- **Endpoint Inconsistency**: 75% of endpoints bypassed pool (`/md`, `/html`, `/screenshot`, `/pdf`, `/execute_js`, `/llm`)
+
+### Pool Design Flaws
+- **Config Mismatch**: Permanent browser used `config.yml` args, endpoints used empty `BrowserConfig()`
+- **Logging Level**: Pool hit markers at DEBUG, invisible with INFO logging
+
+## Implementation Changes
+
+### 1. Container-Aware Memory Detection (`utils.py`)
+```python
+def get_container_memory_percent() -> float:
+    # Try cgroup v2 → v1 → fallback to psutil
+    # Reads /sys/fs/cgroup/memory.{current,max} OR memory/memory.{usage,limit}_in_bytes
+```
+
+### 2. Smart Browser Pool (`crawler_pool.py`)
+**3-Tier System:**
+- **PERMANENT**: Always-ready default browser (never cleaned)
+- **HOT_POOL**: Configs used 3+ times (longer TTL)
+- **COLD_POOL**: New/rare configs (short TTL)
+
+**Key Functions:**
+- `get_crawler(cfg)`: Check permanent → hot → cold → create new
+- `init_permanent(cfg)`: Initialize permanent at startup
+- `janitor()`: Adaptive cleanup (10s/30s/60s intervals based on memory)
+- `_sig(cfg)`: SHA1 hash of config dict for pool keys
+
+**Logging Fix**: Changed `logger.debug()` → `logger.info()` for pool hits
+
+### 3. Endpoint Unification
+**Helper Function** (`server.py`):
+```python
+def get_default_browser_config() -> BrowserConfig:
+    return BrowserConfig(
+        extra_args=config["crawler"]["browser"].get("extra_args", []),
+        **config["crawler"]["browser"].get("kwargs", {}),
+    )
+```
+
+**Migrated Endpoints:**
+- `/html`, `/screenshot`, `/pdf`, `/execute_js` → use `get_default_browser_config()`
+- `handle_llm_qa()`, `handle_markdown_request()` → same
+
+**Result**: All endpoints now hit permanent browser pool
+
+### 4. Config Updates (`config.yml`)
+- `idle_ttl_sec: 1800` → `300` (30min → 5min base TTL)
+- `port: 11234` → `11235` (fixed mismatch with Gunicorn)
+
+### 5. Lifespan Fix (`server.py`)
+```python
+await init_permanent(BrowserConfig(
+    extra_args=config["crawler"]["browser"].get("extra_args", []),
+    **config["crawler"]["browser"].get("kwargs", {}),
+))
+```
+Permanent browser now matches endpoint config signatures
+
+## Test Results
+
+### Test 1: Basic Health
+- 10 requests to `/health`
+- **Result**: 100% success, avg 3ms latency
+- **Baseline**: Container starts in ~5s, 270 MB idle
+
+### Test 2: Memory Monitoring
+- 20 requests with Docker stats tracking
+- **Result**: 100% success, no memory leak (-0.2 MB delta)
+- **Baseline**: 269.7 MB container overhead
+
+### Test 3: Pool Validation
+- 30 requests to `/html` endpoint
+- **Result**: **100% permanent browser hits**, 0 new browsers created
+- **Memory**: 287 MB baseline → 396 MB active (+109 MB)
+- **Latency**: Avg 4s (includes network to httpbin.org)
+
+### Test 4: Concurrent Load
+- Light (10) → Medium (50) → Heavy (100) concurrent
+- **Total**: 320 requests
+- **Result**: 100% success, **320/320 permanent hits**, 0 new browsers
+- **Memory**: 269 MB → peak 1533 MB → final 993 MB
+- **Latency**: P99 at 100 concurrent = 34s (expected with single browser)
+
+### Test 5: Pool Stress (Mixed Configs)
+- 20 requests with 4 different viewport configs
+- **Result**: 4 new browsers, 4 cold hits, **4 promotions to hot**, 8 hot hits
+- **Reuse Rate**: 60% (12 pool hits / 20 requests)
+- **Memory**: 270 MB → 928 MB peak (+658 MB = ~165 MB per browser)
+- **Proves**: Cold → hot promotion at 3 uses working perfectly
+
+### Test 6: Multi-Endpoint
+- 10 requests each: `/html`, `/screenshot`, `/pdf`, `/crawl`
+- **Result**: 100% success across all 4 endpoints
+- **Latency**: 5-8s avg (PDF slowest at 7.2s)
+
+### Test 7: Cleanup Verification
+- 20 requests (load spike) → 90s idle
+- **Memory**: 269 MB → peak 1107 MB → final 780 MB
+- **Recovery**: 327 MB (39%) - partial cleanup
+- **Note**: Hot pool browsers persist (by design), janitor working correctly
+
+## Performance Metrics
+
+| Metric | Before | After | Improvement |
+|--------|--------|-------|-------------|
+| Pool Reuse | 0% | 100% (default config) | ∞ |
+| Memory Leak | Unknown | 0 MB/cycle | Stable |
+| Browser Reuse | No | Yes | ~3-5s saved per request |
+| Idle Memory | 500-700 MB × N | 270-400 MB | 10x reduction |
+| Concurrent Capacity | ~20 | 100+ | 5x |
+
+## Key Learnings
+
+1. **Config Signature Matching**: Permanent browser MUST match endpoint default config exactly (SHA1 hash)
+2. **Logging Levels**: Pool diagnostics need INFO level, not DEBUG
+3. **Memory in Docker**: Must read cgroup files, not host metrics
+4. **Janitor Timing**: 60s interval adequate, but TTLs should be short (5min) for cold pool
+5. **Hot Promotion**: 3-use threshold works well for production patterns
+6. **Memory Per Browser**: ~150-200 MB per Chromium instance with headless + text_mode
+
+## Test Infrastructure
+
+**Location**: `deploy/docker/tests/`
+**Dependencies**: `httpx`, `docker` (Python SDK)
+**Pattern**: Sequential build - each test adds one capability
+
+**Files**:
+- `test_1_basic.py`: Health check + container lifecycle
+- `test_2_memory.py`: + Docker stats monitoring
+- `test_3_pool.py`: + Log analysis for pool markers
+- `test_4_concurrent.py`: + asyncio.Semaphore for concurrency control
+- `test_5_pool_stress.py`: + Config variants (viewports)
+- `test_6_multi_endpoint.py`: + Multiple endpoint testing
+- `test_7_cleanup.py`: + Time-series memory tracking for janitor
+
+**Run Pattern**:
+```bash
+cd deploy/docker/tests
+pip install -r requirements.txt
+# Rebuild after code changes:
+cd /path/to/repo && docker buildx build -t crawl4ai-local:latest --load .
+# Run test:
+python test_N_name.py
+```
+
+## Architecture Decisions
+
+**Why Permanent Browser?**
+- 90% of requests use default config → single browser serves most traffic
+- Eliminates 3-5s startup overhead per request
+
+**Why 3-Tier Pool?**
+- Permanent: Zero cost for common case
+- Hot: Amortized cost for frequent variants
+- Cold: Lazy allocation for rare configs
+
+**Why Adaptive Janitor?**
+- Memory pressure triggers aggressive cleanup
+- Low memory allows longer TTLs for better reuse
+
+**Why Not Close After Each Request?**
+- Browser startup: 3-5s overhead
+- Pool reuse: <100ms overhead
+- Net: 30-50x faster
+
+## Future Optimizations
+
+1. **Request Queuing**: When at capacity, queue instead of reject
+2. **Pre-warming**: Predict common configs, pre-create browsers
+3. **Metrics Export**: Prometheus metrics for pool efficiency
+4. **Config Normalization**: Group similar viewports (e.g., 1920±50 → 1920)
+
+## Critical Code Paths
+
+**Browser Acquisition** (`crawler_pool.py:34-78`):
+```
+get_crawler(cfg) →
+  _sig(cfg) →
+  if sig == DEFAULT_CONFIG_SIG → PERMANENT
+  elif sig in HOT_POOL → HOT_POOL[sig]
+  elif sig in COLD_POOL → promote if count >= 3
+  else → create new in COLD_POOL
+```
+
+**Janitor Loop** (`crawler_pool.py:107-146`):
+```
+while True:
+  mem% = get_container_memory_percent()
+  if mem% > 80: interval=10s, cold_ttl=30s
+  elif mem% > 60: interval=30s, cold_ttl=60s
+  else: interval=60s, cold_ttl=300s
+  sleep(interval)
+  close idle browsers (COLD then HOT)
+```
+
+**Endpoint Pattern** (`server.py` example):
+```python
+@app.post("/html")
+async def generate_html(...):
+    from crawler_pool import get_crawler
+    crawler = await get_crawler(get_default_browser_config())
+    results = await crawler.arun(url=body.url, config=cfg)
+    # No crawler.close() - returned to pool
+```
+
+## Debugging Tips
+
+**Check Pool Activity**:
+```bash
+docker logs crawl4ai-test | grep -E "(🔥|♨️|❄️|🆕|⬆️)"
+```
+
+**Verify Config Signature**:
+```python
+from crawl4ai import BrowserConfig
+import json, hashlib
+cfg = BrowserConfig(...)
+sig = hashlib.sha1(json.dumps(cfg.to_dict(), sort_keys=True).encode()).hexdigest()
+print(sig[:8])  # Compare with logs
+```
+
+**Monitor Memory**:
+```bash
+docker stats crawl4ai-test
+```
+
+## Known Limitations
+
+- **Mac Docker Stats**: CPU metrics unreliable, memory works
+- **PDF Generation**: Slowest endpoint (~7s), no optimization yet
+- **Hot Pool Persistence**: May hold memory longer than needed (trade-off for performance)
+- **Janitor Lag**: Up to 60s before cleanup triggers in low-memory scenarios

deploy/docker/api.py

@@ -67,6 +67,7 @@ async def handle_llm_qa(
     config: dict
 ) -> str:
     """Process QA using LLM with crawled content as context."""
+    from crawler_pool import get_crawler
     try:
         if not url.startswith(('http://', 'https://')) and not url.startswith(("raw:", "raw://")):
             url = 'https://' + url
@@ -75,15 +76,21 @@ async def handle_llm_qa(
         if last_q_index != -1:
             url = url[:last_q_index]
 
-        # Get markdown content
-        async with AsyncWebCrawler() as crawler:
-            result = await crawler.arun(url)
-            if not result.success:
-                raise HTTPException(
-                    status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-                    detail=result.error_message
-                )
-            content = result.markdown.fit_markdown or result.markdown.raw_markdown
+        # Get markdown content (use default config)
+        from utils import load_config
+        cfg = load_config()
+        browser_cfg = BrowserConfig(
+            extra_args=cfg["crawler"]["browser"].get("extra_args", []),
+            **cfg["crawler"]["browser"].get("kwargs", {}),
+        )
+        crawler = await get_crawler(browser_cfg)
+        result = await crawler.arun(url)
+        if not result.success:
+            raise HTTPException(
+                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=result.error_message
+            )
+        content = result.markdown.fit_markdown or result.markdown.raw_markdown
 
         # Create prompt and get LLM response
         prompt = f"""Use the following content as context to answer the question.
@@ -272,25 +279,32 @@ async def handle_markdown_request(
 
         cache_mode = CacheMode.ENABLED if cache == "1" else CacheMode.WRITE_ONLY
 
-        async with AsyncWebCrawler() as crawler:
-            result = await crawler.arun(
-                url=decoded_url,
-                config=CrawlerRunConfig(
-                    markdown_generator=md_generator,
-                    scraping_strategy=LXMLWebScrapingStrategy(),
-                    cache_mode=cache_mode
-                )
+        from crawler_pool import get_crawler
+        from utils import load_config as _load_config
+        _cfg = _load_config()
+        browser_cfg = BrowserConfig(
+            extra_args=_cfg["crawler"]["browser"].get("extra_args", []),
+            **_cfg["crawler"]["browser"].get("kwargs", {}),
+        )
+        crawler = await get_crawler(browser_cfg)
+        result = await crawler.arun(
+            url=decoded_url,
+            config=CrawlerRunConfig(
+                markdown_generator=md_generator,
+                scraping_strategy=LXMLWebScrapingStrategy(),
+                cache_mode=cache_mode
+            )
+        )
+
+        if not result.success:
+            raise HTTPException(
+                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=result.error_message
             )
 
-            if not result.success:
-                raise HTTPException(
-                    status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-                    detail=result.error_message
-                )
-
-            return (result.markdown.raw_markdown 
-                   if filter_type == FilterType.RAW 
-                   else result.markdown.fit_markdown)
+        return (result.markdown.raw_markdown
+               if filter_type == FilterType.RAW
+               else result.markdown.fit_markdown)
 
     except Exception as e:
         logger.error(f"Markdown error: {str(e)}", exc_info=True)
@@ -504,6 +518,16 @@ async def handle_crawl_request(
     hooks_config: Optional[dict] = None
 ) -> dict:
     """Handle non-streaming crawl requests with optional hooks."""
+    # Track request start
+    request_id = f"req_{uuid4().hex[:8]}"
+    try:
+        from monitor import get_monitor
+        await get_monitor().track_request_start(
+            request_id, "/crawl", urls[0] if urls else "batch", browser_config
+        )
+    except:
+        pass  # Monitor not critical
+
     start_mem_mb = _get_memory_mb() # <--- Get memory before
     start_time = time.time()
     mem_delta_mb = None
@@ -615,6 +639,15 @@ async def handle_crawl_request(
             "server_peak_memory_mb": peak_mem_mb
         }
 
+        # Track request completion
+        try:
+            from monitor import get_monitor
+            await get_monitor().track_request_end(
+                request_id, success=True, pool_hit=True, status_code=200
+            )
+        except:
+            pass
+
         # Add hooks information if hooks were used
         if hooks_config and hook_manager:
             from hook_manager import UserHookManager
@@ -643,6 +676,16 @@ async def handle_crawl_request(
 
     except Exception as e:
         logger.error(f"Crawl error: {str(e)}", exc_info=True)
+
+        # Track request error
+        try:
+            from monitor import get_monitor
+            await get_monitor().track_request_end(
+                request_id, success=False, error=str(e), status_code=500
+            )
+        except:
+            pass
+
         if 'crawler' in locals() and crawler.ready: # Check if crawler was initialized and started
             #  try:
             #      await crawler.close()

deploy/docker/config.yml

@@ -3,7 +3,7 @@ app:
   title: "Crawl4AI API"
   version: "1.0.0"
   host: "0.0.0.0"
-  port: 11234
+  port: 11235
   reload: False
   workers: 1
   timeout_keep_alive: 300
@@ -61,7 +61,7 @@ crawler:
     batch_process: 300.0  # Timeout for batch processing
   pool:
     max_pages: 40                          # ← GLOBAL_SEM permits
-    idle_ttl_sec: 1800                     # ← 30 min janitor cutoff
+    idle_ttl_sec: 300                     # ← 30 min janitor cutoff
   browser:
     kwargs:
       headless: true

deploy/docker/crawler_pool.py

@@ -1,60 +1,170 @@
-# crawler_pool.py  (new file)
-import asyncio, json, hashlib, time, psutil
+# crawler_pool.py - Smart browser pool with tiered management
+import asyncio, json, hashlib, time
 from contextlib import suppress
-from typing import Dict
+from typing import Dict, Optional
 from crawl4ai import AsyncWebCrawler, BrowserConfig
-from typing import Dict
-from utils import load_config 
+from utils import load_config, get_container_memory_percent
+import logging
 
+logger = logging.getLogger(__name__)
 CONFIG = load_config()
 
-POOL: Dict[str, AsyncWebCrawler] = {}
+# Pool tiers
+PERMANENT: Optional[AsyncWebCrawler] = None  # Always-ready default browser
+HOT_POOL: Dict[str, AsyncWebCrawler] = {}    # Frequent configs
+COLD_POOL: Dict[str, AsyncWebCrawler] = {}   # Rare configs
 LAST_USED: Dict[str, float] = {}
+USAGE_COUNT: Dict[str, int] = {}
 LOCK = asyncio.Lock()
 
-MEM_LIMIT  = CONFIG.get("crawler", {}).get("memory_threshold_percent", 95.0)   # % RAM – refuse new browsers above this
-IDLE_TTL  = CONFIG.get("crawler", {}).get("pool", {}).get("idle_ttl_sec", 1800)   # close if unused for 30 min
+# Config
+MEM_LIMIT = CONFIG.get("crawler", {}).get("memory_threshold_percent", 95.0)
+BASE_IDLE_TTL = CONFIG.get("crawler", {}).get("pool", {}).get("idle_ttl_sec", 300)
+DEFAULT_CONFIG_SIG = None  # Cached sig for default config
 
 def _sig(cfg: BrowserConfig) -> str:
+    """Generate config signature."""
     payload = json.dumps(cfg.to_dict(), sort_keys=True, separators=(",",":"))
     return hashlib.sha1(payload.encode()).hexdigest()
 
+def _is_default_config(sig: str) -> bool:
+    """Check if config matches default."""
+    return sig == DEFAULT_CONFIG_SIG
+
 async def get_crawler(cfg: BrowserConfig) -> AsyncWebCrawler:
-    try:
-        sig = _sig(cfg)
-        async with LOCK:
-            if sig in POOL:
-                LAST_USED[sig] = time.time();  
-                return POOL[sig]
-            if psutil.virtual_memory().percent >= MEM_LIMIT:
-                raise MemoryError("RAM pressure – new browser denied")
-            crawler = AsyncWebCrawler(config=cfg, thread_safe=False)
-            await crawler.start()
-            POOL[sig] = crawler; LAST_USED[sig] = time.time()
-            return crawler
-    except MemoryError as e:
-        raise MemoryError(f"RAM pressure – new browser denied: {e}")
-    except Exception as e:
-        raise RuntimeError(f"Failed to start browser: {e}")
-    finally:
-        if sig in POOL:
-            LAST_USED[sig] = time.time()
-        else:
-            # If we failed to start the browser, we should remove it from the pool
-            POOL.pop(sig, None)
-            LAST_USED.pop(sig, None)
-        # If we failed to start the browser, we should remove it from the pool
-async def close_all():
+    """Get crawler from pool with tiered strategy."""
+    sig = _sig(cfg)
     async with LOCK:
-        await asyncio.gather(*(c.close() for c in POOL.values()), return_exceptions=True)
-        POOL.clear(); LAST_USED.clear()
+        # Check permanent browser for default config
+        if PERMANENT and _is_default_config(sig):
+            LAST_USED[sig] = time.time()
+            USAGE_COUNT[sig] = USAGE_COUNT.get(sig, 0) + 1
+            logger.info("🔥 Using permanent browser")
+            return PERMANENT
+
+        # Check hot pool
+        if sig in HOT_POOL:
+            LAST_USED[sig] = time.time()
+            USAGE_COUNT[sig] = USAGE_COUNT.get(sig, 0) + 1
+            logger.info(f"♨️  Using hot pool browser (sig={sig[:8]})")
+            return HOT_POOL[sig]
+
+        # Check cold pool (promote to hot if used 3+ times)
+        if sig in COLD_POOL:
+            LAST_USED[sig] = time.time()
+            USAGE_COUNT[sig] = USAGE_COUNT.get(sig, 0) + 1
+
+            if USAGE_COUNT[sig] >= 3:
+                logger.info(f"⬆️  Promoting to hot pool (sig={sig[:8]}, count={USAGE_COUNT[sig]})")
+                HOT_POOL[sig] = COLD_POOL.pop(sig)
+
+                # Track promotion in monitor
+                try:
+                    from monitor import get_monitor
+                    await get_monitor().track_janitor_event("promote", sig, {"count": USAGE_COUNT[sig]})
+                except:
+                    pass
+
+                return HOT_POOL[sig]
+
+            logger.info(f"❄️  Using cold pool browser (sig={sig[:8]})")
+            return COLD_POOL[sig]
+
+        # Memory check before creating new
+        mem_pct = get_container_memory_percent()
+        if mem_pct >= MEM_LIMIT:
+            logger.error(f"💥 Memory pressure: {mem_pct:.1f}% >= {MEM_LIMIT}%")
+            raise MemoryError(f"Memory at {mem_pct:.1f}%, refusing new browser")
+
+        # Create new in cold pool
+        logger.info(f"🆕 Creating new browser in cold pool (sig={sig[:8]}, mem={mem_pct:.1f}%)")
+        crawler = AsyncWebCrawler(config=cfg, thread_safe=False)
+        await crawler.start()
+        COLD_POOL[sig] = crawler
+        LAST_USED[sig] = time.time()
+        USAGE_COUNT[sig] = 1
+        return crawler
+
+async def init_permanent(cfg: BrowserConfig):
+    """Initialize permanent default browser."""
+    global PERMANENT, DEFAULT_CONFIG_SIG
+    async with LOCK:
+        if PERMANENT:
+            return
+        DEFAULT_CONFIG_SIG = _sig(cfg)
+        logger.info("🔥 Creating permanent default browser")
+        PERMANENT = AsyncWebCrawler(config=cfg, thread_safe=False)
+        await PERMANENT.start()
+        LAST_USED[DEFAULT_CONFIG_SIG] = time.time()
+        USAGE_COUNT[DEFAULT_CONFIG_SIG] = 0
+
+async def close_all():
+    """Close all browsers."""
+    async with LOCK:
+        tasks = []
+        if PERMANENT:
+            tasks.append(PERMANENT.close())
+        tasks.extend([c.close() for c in HOT_POOL.values()])
+        tasks.extend([c.close() for c in COLD_POOL.values()])
+        await asyncio.gather(*tasks, return_exceptions=True)
+        HOT_POOL.clear()
+        COLD_POOL.clear()
+        LAST_USED.clear()
+        USAGE_COUNT.clear()
 
 async def janitor():
+    """Adaptive cleanup based on memory pressure."""
     while True:
-        await asyncio.sleep(60)
+        mem_pct = get_container_memory_percent()
+
+        # Adaptive intervals and TTLs
+        if mem_pct > 80:
+            interval, cold_ttl, hot_ttl = 10, 30, 120
+        elif mem_pct > 60:
+            interval, cold_ttl, hot_ttl = 30, 60, 300
+        else:
+            interval, cold_ttl, hot_ttl = 60, BASE_IDLE_TTL, BASE_IDLE_TTL * 2
+
+        await asyncio.sleep(interval)
+
         now = time.time()
         async with LOCK:
-            for sig, crawler in list(POOL.items()):
-                if now - LAST_USED[sig] > IDLE_TTL:
-                    with suppress(Exception): await crawler.close()
-                    POOL.pop(sig, None); LAST_USED.pop(sig, None)
+            # Clean cold pool
+            for sig in list(COLD_POOL.keys()):
+                if now - LAST_USED.get(sig, now) > cold_ttl:
+                    idle_time = now - LAST_USED[sig]
+                    logger.info(f"🧹 Closing cold browser (sig={sig[:8]}, idle={idle_time:.0f}s)")
+                    with suppress(Exception):
+                        await COLD_POOL[sig].close()
+                    COLD_POOL.pop(sig, None)
+                    LAST_USED.pop(sig, None)
+                    USAGE_COUNT.pop(sig, None)
+
+                    # Track in monitor
+                    try:
+                        from monitor import get_monitor
+                        await get_monitor().track_janitor_event("close_cold", sig, {"idle_seconds": int(idle_time), "ttl": cold_ttl})
+                    except:
+                        pass
+
+            # Clean hot pool (more conservative)
+            for sig in list(HOT_POOL.keys()):
+                if now - LAST_USED.get(sig, now) > hot_ttl:
+                    idle_time = now - LAST_USED[sig]
+                    logger.info(f"🧹 Closing hot browser (sig={sig[:8]}, idle={idle_time:.0f}s)")
+                    with suppress(Exception):
+                        await HOT_POOL[sig].close()
+                    HOT_POOL.pop(sig, None)
+                    LAST_USED.pop(sig, None)
+                    USAGE_COUNT.pop(sig, None)
+
+                    # Track in monitor
+                    try:
+                        from monitor import get_monitor
+                        await get_monitor().track_janitor_event("close_hot", sig, {"idle_seconds": int(idle_time), "ttl": hot_ttl})
+                    except:
+                        pass
+
+            # Log pool stats
+            if mem_pct > 60:
+                logger.info(f"📊 Pool: hot={len(HOT_POOL)}, cold={len(COLD_POOL)}, mem={mem_pct:.1f}%")

deploy/docker/monitor.py

@@ -0,0 +1,382 @@
+# monitor.py - Real-time monitoring stats with Redis persistence
+import time
+import json
+import asyncio
+from typing import Dict, List, Optional
+from datetime import datetime, timezone
+from collections import deque
+from redis import asyncio as aioredis
+from utils import get_container_memory_percent
+import psutil
+import logging
+
+logger = logging.getLogger(__name__)
+
+class MonitorStats:
+    """Tracks real-time server stats with Redis persistence."""
+
+    def __init__(self, redis: aioredis.Redis):
+        self.redis = redis
+        self.start_time = time.time()
+
+        # In-memory queues (fast reads, Redis backup)
+        self.active_requests: Dict[str, Dict] = {}  # id -> request info
+        self.completed_requests: deque = deque(maxlen=100)  # Last 100
+        self.janitor_events: deque = deque(maxlen=100)
+        self.errors: deque = deque(maxlen=100)
+
+        # Endpoint stats (persisted in Redis)
+        self.endpoint_stats: Dict[str, Dict] = {}  # endpoint -> {count, total_time, errors, ...}
+
+        # Background persistence queue (max 10 pending persist requests)
+        self._persist_queue: asyncio.Queue = asyncio.Queue(maxsize=10)
+        self._persist_worker_task: Optional[asyncio.Task] = None
+
+        # Timeline data (5min window, 5s resolution = 60 points)
+        self.memory_timeline: deque = deque(maxlen=60)
+        self.requests_timeline: deque = deque(maxlen=60)
+        self.browser_timeline: deque = deque(maxlen=60)
+
+    async def track_request_start(self, request_id: str, endpoint: str, url: str, config: Dict = None):
+        """Track new request start."""
+        req_info = {
+            "id": request_id,
+            "endpoint": endpoint,
+            "url": url[:100],  # Truncate long URLs
+            "start_time": time.time(),
+            "config_sig": config.get("sig", "default") if config else "default",
+            "mem_start": psutil.Process().memory_info().rss / (1024 * 1024)
+        }
+        self.active_requests[request_id] = req_info
+
+        # Increment endpoint counter
+        if endpoint not in self.endpoint_stats:
+            self.endpoint_stats[endpoint] = {
+                "count": 0, "total_time": 0, "errors": 0,
+                "pool_hits": 0, "success": 0
+            }
+        self.endpoint_stats[endpoint]["count"] += 1
+
+        # Queue persistence (handled by background worker)
+        try:
+            self._persist_queue.put_nowait(True)
+        except asyncio.QueueFull:
+            logger.warning("Persistence queue full, skipping")
+
+    async def track_request_end(self, request_id: str, success: bool, error: str = None,
+                               pool_hit: bool = True, status_code: int = 200):
+        """Track request completion."""
+        if request_id not in self.active_requests:
+            return
+
+        req_info = self.active_requests.pop(request_id)
+        end_time = time.time()
+        elapsed = end_time - req_info["start_time"]
+        mem_end = psutil.Process().memory_info().rss / (1024 * 1024)
+        mem_delta = mem_end - req_info["mem_start"]
+
+        # Update stats
+        endpoint = req_info["endpoint"]
+        if endpoint in self.endpoint_stats:
+            self.endpoint_stats[endpoint]["total_time"] += elapsed
+            if success:
+                self.endpoint_stats[endpoint]["success"] += 1
+            else:
+                self.endpoint_stats[endpoint]["errors"] += 1
+            if pool_hit:
+                self.endpoint_stats[endpoint]["pool_hits"] += 1
+
+        # Add to completed queue
+        completed = {
+            **req_info,
+            "end_time": end_time,
+            "elapsed": round(elapsed, 2),
+            "mem_delta": round(mem_delta, 1),
+            "success": success,
+            "error": error,
+            "status_code": status_code,
+            "pool_hit": pool_hit
+        }
+        self.completed_requests.append(completed)
+
+        # Track errors
+        if not success and error:
+            self.errors.append({
+                "timestamp": end_time,
+                "endpoint": endpoint,
+                "url": req_info["url"],
+                "error": error,
+                "request_id": request_id
+            })
+
+        await self._persist_endpoint_stats()
+
+    async def track_janitor_event(self, event_type: str, sig: str, details: Dict):
+        """Track janitor cleanup events."""
+        self.janitor_events.append({
+            "timestamp": time.time(),
+            "type": event_type,  # "close_cold", "close_hot", "promote"
+            "sig": sig[:8],
+            "details": details
+        })
+
+    def _cleanup_old_entries(self, max_age_seconds: int = 300):
+        """Remove entries older than max_age_seconds (default 5min)."""
+        now = time.time()
+        cutoff = now - max_age_seconds
+
+        # Clean completed requests
+        while self.completed_requests and self.completed_requests[0].get("end_time", 0) < cutoff:
+            self.completed_requests.popleft()
+
+        # Clean janitor events
+        while self.janitor_events and self.janitor_events[0].get("timestamp", 0) < cutoff:
+            self.janitor_events.popleft()
+
+        # Clean errors
+        while self.errors and self.errors[0].get("timestamp", 0) < cutoff:
+            self.errors.popleft()
+
+    async def update_timeline(self):
+        """Update timeline data points (called every 5s)."""
+        now = time.time()
+        mem_pct = get_container_memory_percent()
+
+        # Clean old entries (keep last 5 minutes)
+        self._cleanup_old_entries(max_age_seconds=300)
+
+        # Count requests in last 5s
+        recent_reqs = sum(1 for req in self.completed_requests
+                         if now - req.get("end_time", 0) < 5)
+
+        # Browser counts (acquire lock to prevent race conditions)
+        from crawler_pool import PERMANENT, HOT_POOL, COLD_POOL, LOCK
+        async with LOCK:
+            browser_count = {
+                "permanent": 1 if PERMANENT else 0,
+                "hot": len(HOT_POOL),
+                "cold": len(COLD_POOL)
+            }
+
+        self.memory_timeline.append({"time": now, "value": mem_pct})
+        self.requests_timeline.append({"time": now, "value": recent_reqs})
+        self.browser_timeline.append({"time": now, "browsers": browser_count})
+
+    async def _persist_endpoint_stats(self):
+        """Persist endpoint stats to Redis."""
+        try:
+            await self.redis.set(
+                "monitor:endpoint_stats",
+                json.dumps(self.endpoint_stats),
+                ex=86400  # 24h TTL
+            )
+        except Exception as e:
+            logger.warning(f"Failed to persist endpoint stats: {e}")
+
+    async def _persistence_worker(self):
+        """Background worker to persist stats to Redis."""
+        while True:
+            try:
+                await self._persist_queue.get()
+                await self._persist_endpoint_stats()
+                self._persist_queue.task_done()
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"Persistence worker error: {e}")
+
+    def start_persistence_worker(self):
+        """Start the background persistence worker."""
+        if not self._persist_worker_task:
+            self._persist_worker_task = asyncio.create_task(self._persistence_worker())
+            logger.info("Started persistence worker")
+
+    async def stop_persistence_worker(self):
+        """Stop the background persistence worker."""
+        if self._persist_worker_task:
+            self._persist_worker_task.cancel()
+            try:
+                await self._persist_worker_task
+            except asyncio.CancelledError:
+                pass
+            self._persist_worker_task = None
+            logger.info("Stopped persistence worker")
+
+    async def cleanup(self):
+        """Cleanup on shutdown - persist final stats and stop workers."""
+        logger.info("Monitor cleanup starting...")
+        try:
+            # Persist final stats before shutdown
+            await self._persist_endpoint_stats()
+            # Stop background worker
+            await self.stop_persistence_worker()
+            logger.info("Monitor cleanup completed")
+        except Exception as e:
+            logger.error(f"Monitor cleanup error: {e}")
+
+    async def load_from_redis(self):
+        """Load persisted stats from Redis."""
+        try:
+            data = await self.redis.get("monitor:endpoint_stats")
+            if data:
+                self.endpoint_stats = json.loads(data)
+                logger.info("Loaded endpoint stats from Redis")
+        except Exception as e:
+            logger.warning(f"Failed to load from Redis: {e}")
+
+    async def get_health_summary(self) -> Dict:
+        """Get current system health snapshot."""
+        mem_pct = get_container_memory_percent()
+        cpu_pct = psutil.cpu_percent(interval=0.1)
+
+        # Network I/O (delta since last call)
+        net = psutil.net_io_counters()
+
+        # Pool status (acquire lock to prevent race conditions)
+        from crawler_pool import PERMANENT, HOT_POOL, COLD_POOL, LOCK
+        async with LOCK:
+            # TODO: Track actual browser process memory instead of estimates
+            # These are conservative estimates based on typical Chromium usage
+            permanent_mem = 270 if PERMANENT else 0  # Estimate: ~270MB for permanent browser
+            hot_mem = len(HOT_POOL) * 180  # Estimate: ~180MB per hot pool browser
+            cold_mem = len(COLD_POOL) * 180  # Estimate: ~180MB per cold pool browser
+            permanent_active = PERMANENT is not None
+            hot_count = len(HOT_POOL)
+            cold_count = len(COLD_POOL)
+
+        return {
+            "container": {
+                "memory_percent": round(mem_pct, 1),
+                "cpu_percent": round(cpu_pct, 1),
+                "network_sent_mb": round(net.bytes_sent / (1024**2), 2),
+                "network_recv_mb": round(net.bytes_recv / (1024**2), 2),
+                "uptime_seconds": int(time.time() - self.start_time)
+            },
+            "pool": {
+                "permanent": {"active": permanent_active, "memory_mb": permanent_mem},
+                "hot": {"count": hot_count, "memory_mb": hot_mem},
+                "cold": {"count": cold_count, "memory_mb": cold_mem},
+                "total_memory_mb": permanent_mem + hot_mem + cold_mem
+            },
+            "janitor": {
+                "next_cleanup_estimate": "adaptive",  # Would need janitor state
+                "memory_pressure": "LOW" if mem_pct < 60 else "MEDIUM" if mem_pct < 80 else "HIGH"
+            }
+        }
+
+    def get_active_requests(self) -> List[Dict]:
+        """Get list of currently active requests."""
+        now = time.time()
+        return [
+            {
+                **req,
+                "elapsed": round(now - req["start_time"], 1),
+                "status": "running"
+            }
+            for req in self.active_requests.values()
+        ]
+
+    def get_completed_requests(self, limit: int = 50, filter_status: str = "all") -> List[Dict]:
+        """Get recent completed requests."""
+        requests = list(self.completed_requests)[-limit:]
+        if filter_status == "success":
+            requests = [r for r in requests if r.get("success")]
+        elif filter_status == "error":
+            requests = [r for r in requests if not r.get("success")]
+        return requests
+
+    async def get_browser_list(self) -> List[Dict]:
+        """Get detailed browser pool information."""
+        from crawler_pool import PERMANENT, HOT_POOL, COLD_POOL, LAST_USED, USAGE_COUNT, DEFAULT_CONFIG_SIG, LOCK
+
+        browsers = []
+        now = time.time()
+
+        # Acquire lock to prevent race conditions during iteration
+        async with LOCK:
+            if PERMANENT:
+                browsers.append({
+                    "type": "permanent",
+                    "sig": DEFAULT_CONFIG_SIG[:8] if DEFAULT_CONFIG_SIG else "unknown",
+                    "age_seconds": int(now - self.start_time),
+                    "last_used_seconds": int(now - LAST_USED.get(DEFAULT_CONFIG_SIG, now)),
+                    "memory_mb": 270,
+                    "hits": USAGE_COUNT.get(DEFAULT_CONFIG_SIG, 0),
+                    "killable": False
+                })
+
+            for sig, crawler in HOT_POOL.items():
+                browsers.append({
+                    "type": "hot",
+                    "sig": sig[:8],
+                    "age_seconds": int(now - self.start_time),  # Approximation
+                    "last_used_seconds": int(now - LAST_USED.get(sig, now)),
+                    "memory_mb": 180,  # Estimate
+                    "hits": USAGE_COUNT.get(sig, 0),
+                    "killable": True
+                })
+
+            for sig, crawler in COLD_POOL.items():
+                browsers.append({
+                    "type": "cold",
+                    "sig": sig[:8],
+                    "age_seconds": int(now - self.start_time),
+                    "last_used_seconds": int(now - LAST_USED.get(sig, now)),
+                    "memory_mb": 180,
+                    "hits": USAGE_COUNT.get(sig, 0),
+                    "killable": True
+                })
+
+        return browsers
+
+    def get_endpoint_stats_summary(self) -> Dict[str, Dict]:
+        """Get aggregated endpoint statistics."""
+        summary = {}
+        for endpoint, stats in self.endpoint_stats.items():
+            count = stats["count"]
+            avg_time = (stats["total_time"] / count) if count > 0 else 0
+            success_rate = (stats["success"] / count * 100) if count > 0 else 0
+            pool_hit_rate = (stats["pool_hits"] / count * 100) if count > 0 else 0
+
+            summary[endpoint] = {
+                "count": count,
+                "avg_latency_ms": round(avg_time * 1000, 1),
+                "success_rate_percent": round(success_rate, 1),
+                "pool_hit_rate_percent": round(pool_hit_rate, 1),
+                "errors": stats["errors"]
+            }
+        return summary
+
+    def get_timeline_data(self, metric: str, window: str = "5m") -> Dict:
+        """Get timeline data for charts."""
+        # For now, only 5m window supported
+        if metric == "memory":
+            data = list(self.memory_timeline)
+        elif metric == "requests":
+            data = list(self.requests_timeline)
+        elif metric == "browsers":
+            data = list(self.browser_timeline)
+        else:
+            return {"timestamps": [], "values": []}
+
+        return {
+            "timestamps": [int(d["time"]) for d in data],
+            "values": [d.get("value", d.get("browsers")) for d in data]
+        }
+
+    def get_janitor_log(self, limit: int = 100) -> List[Dict]:
+        """Get recent janitor events."""
+        return list(self.janitor_events)[-limit:]
+
+    def get_errors_log(self, limit: int = 100) -> List[Dict]:
+        """Get recent errors."""
+        return list(self.errors)[-limit:]
+
+# Global instance (initialized in server.py)
+monitor_stats: Optional[MonitorStats] = None
+
+def get_monitor() -> MonitorStats:
+    """Get global monitor instance."""
+    if monitor_stats is None:
+        raise RuntimeError("Monitor not initialized")
+    return monitor_stats

deploy/docker/monitor_routes.py

@@ -0,0 +1,405 @@
+# monitor_routes.py - Monitor API endpoints
+from fastapi import APIRouter, HTTPException, WebSocket, WebSocketDisconnect
+from pydantic import BaseModel
+from typing import Optional
+from monitor import get_monitor
+import logging
+import asyncio
+import json
+
+logger = logging.getLogger(__name__)
+router = APIRouter(prefix="/monitor", tags=["monitor"])
+
+
+@router.get("/health")
+async def get_health():
+    """Get current system health snapshot."""
+    try:
+        monitor = get_monitor()
+        return await monitor.get_health_summary()
+    except Exception as e:
+        logger.error(f"Error getting health: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/requests")
+async def get_requests(status: str = "all", limit: int = 50):
+    """Get active and completed requests.
+
+    Args:
+        status: Filter by 'active', 'completed', 'success', 'error', or 'all'
+        limit: Max number of completed requests to return (default 50)
+    """
+    # Input validation
+    if status not in ["all", "active", "completed", "success", "error"]:
+        raise HTTPException(400, f"Invalid status: {status}. Must be one of: all, active, completed, success, error")
+    if limit < 1 or limit > 1000:
+        raise HTTPException(400, f"Invalid limit: {limit}. Must be between 1 and 1000")
+
+    try:
+        monitor = get_monitor()
+
+        if status == "active":
+            return {"active": monitor.get_active_requests(), "completed": []}
+        elif status == "completed":
+            return {"active": [], "completed": monitor.get_completed_requests(limit)}
+        elif status in ["success", "error"]:
+            return {"active": [], "completed": monitor.get_completed_requests(limit, status)}
+        else:  # "all"
+            return {
+                "active": monitor.get_active_requests(),
+                "completed": monitor.get_completed_requests(limit)
+            }
+    except Exception as e:
+        logger.error(f"Error getting requests: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/browsers")
+async def get_browsers():
+    """Get detailed browser pool information."""
+    try:
+        monitor = get_monitor()
+        browsers = await monitor.get_browser_list()
+
+        # Calculate summary stats
+        total_browsers = len(browsers)
+        total_memory = sum(b["memory_mb"] for b in browsers)
+
+        # Calculate reuse rate from recent requests
+        recent = monitor.get_completed_requests(100)
+        pool_hits = sum(1 for r in recent if r.get("pool_hit", False))
+        reuse_rate = (pool_hits / len(recent) * 100) if recent else 0
+
+        return {
+            "browsers": browsers,
+            "summary": {
+                "total_count": total_browsers,
+                "total_memory_mb": total_memory,
+                "reuse_rate_percent": round(reuse_rate, 1)
+            }
+        }
+    except Exception as e:
+        logger.error(f"Error getting browsers: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/endpoints/stats")
+async def get_endpoint_stats():
+    """Get aggregated endpoint statistics."""
+    try:
+        monitor = get_monitor()
+        return monitor.get_endpoint_stats_summary()
+    except Exception as e:
+        logger.error(f"Error getting endpoint stats: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/timeline")
+async def get_timeline(metric: str = "memory", window: str = "5m"):
+    """Get timeline data for charts.
+
+    Args:
+        metric: 'memory', 'requests', or 'browsers'
+        window: Time window (only '5m' supported for now)
+    """
+    # Input validation
+    if metric not in ["memory", "requests", "browsers"]:
+        raise HTTPException(400, f"Invalid metric: {metric}. Must be one of: memory, requests, browsers")
+    if window != "5m":
+        raise HTTPException(400, f"Invalid window: {window}. Only '5m' is currently supported")
+
+    try:
+        monitor = get_monitor()
+        return monitor.get_timeline_data(metric, window)
+    except Exception as e:
+        logger.error(f"Error getting timeline: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/logs/janitor")
+async def get_janitor_log(limit: int = 100):
+    """Get recent janitor cleanup events."""
+    # Input validation
+    if limit < 1 or limit > 1000:
+        raise HTTPException(400, f"Invalid limit: {limit}. Must be between 1 and 1000")
+
+    try:
+        monitor = get_monitor()
+        return {"events": monitor.get_janitor_log(limit)}
+    except Exception as e:
+        logger.error(f"Error getting janitor log: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.get("/logs/errors")
+async def get_errors_log(limit: int = 100):
+    """Get recent errors."""
+    # Input validation
+    if limit < 1 or limit > 1000:
+        raise HTTPException(400, f"Invalid limit: {limit}. Must be between 1 and 1000")
+
+    try:
+        monitor = get_monitor()
+        return {"errors": monitor.get_errors_log(limit)}
+    except Exception as e:
+        logger.error(f"Error getting errors log: {e}")
+        raise HTTPException(500, str(e))
+
+
+# ========== Control Actions ==========
+
+class KillBrowserRequest(BaseModel):
+    sig: str
+
+
+@router.post("/actions/cleanup")
+async def force_cleanup():
+    """Force immediate janitor cleanup (kills idle cold pool browsers)."""
+    try:
+        from crawler_pool import COLD_POOL, LAST_USED, USAGE_COUNT, LOCK
+        import time
+        from contextlib import suppress
+
+        killed_count = 0
+        now = time.time()
+
+        async with LOCK:
+            for sig in list(COLD_POOL.keys()):
+                # Kill all cold pool browsers immediately
+                logger.info(f"🧹 Force cleanup: closing cold browser (sig={sig[:8]})")
+                with suppress(Exception):
+                    await COLD_POOL[sig].close()
+                COLD_POOL.pop(sig, None)
+                LAST_USED.pop(sig, None)
+                USAGE_COUNT.pop(sig, None)
+                killed_count += 1
+
+        monitor = get_monitor()
+        await monitor.track_janitor_event("force_cleanup", "manual", {"killed": killed_count})
+
+        return {"success": True, "killed_browsers": killed_count}
+    except Exception as e:
+        logger.error(f"Error during force cleanup: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.post("/actions/kill_browser")
+async def kill_browser(req: KillBrowserRequest):
+    """Kill a specific browser by signature (hot or cold only).
+
+    Args:
+        sig: Browser config signature (first 8 chars)
+    """
+    try:
+        from crawler_pool import HOT_POOL, COLD_POOL, LAST_USED, USAGE_COUNT, LOCK, DEFAULT_CONFIG_SIG
+        from contextlib import suppress
+
+        # Find full signature matching prefix
+        target_sig = None
+        pool_type = None
+
+        async with LOCK:
+            # Check hot pool
+            for sig in HOT_POOL.keys():
+                if sig.startswith(req.sig):
+                    target_sig = sig
+                    pool_type = "hot"
+                    break
+
+            # Check cold pool
+            if not target_sig:
+                for sig in COLD_POOL.keys():
+                    if sig.startswith(req.sig):
+                        target_sig = sig
+                        pool_type = "cold"
+                        break
+
+            # Check if trying to kill permanent
+            if DEFAULT_CONFIG_SIG and DEFAULT_CONFIG_SIG.startswith(req.sig):
+                raise HTTPException(403, "Cannot kill permanent browser. Use restart instead.")
+
+            if not target_sig:
+                raise HTTPException(404, f"Browser with sig={req.sig} not found")
+
+            # Warn if there are active requests (browser might be in use)
+            monitor = get_monitor()
+            active_count = len(monitor.get_active_requests())
+            if active_count > 0:
+                logger.warning(f"Killing browser {target_sig[:8]} while {active_count} requests are active - may cause failures")
+
+            # Kill the browser
+            if pool_type == "hot":
+                browser = HOT_POOL.pop(target_sig)
+            else:
+                browser = COLD_POOL.pop(target_sig)
+
+            with suppress(Exception):
+                await browser.close()
+
+            LAST_USED.pop(target_sig, None)
+            USAGE_COUNT.pop(target_sig, None)
+
+        logger.info(f"🔪 Killed {pool_type} browser (sig={target_sig[:8]})")
+
+        monitor = get_monitor()
+        await monitor.track_janitor_event("kill_browser", target_sig, {"pool": pool_type, "manual": True})
+
+        return {"success": True, "killed_sig": target_sig[:8], "pool_type": pool_type}
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error killing browser: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.post("/actions/restart_browser")
+async def restart_browser(req: KillBrowserRequest):
+    """Restart a browser (kill + recreate). Works for permanent too.
+
+    Args:
+        sig: Browser config signature (first 8 chars), or "permanent"
+    """
+    try:
+        from crawler_pool import (PERMANENT, HOT_POOL, COLD_POOL, LAST_USED,
+                                  USAGE_COUNT, LOCK, DEFAULT_CONFIG_SIG, init_permanent)
+        from crawl4ai import AsyncWebCrawler, BrowserConfig
+        from contextlib import suppress
+        import time
+
+        # Handle permanent browser restart
+        if req.sig == "permanent" or (DEFAULT_CONFIG_SIG and DEFAULT_CONFIG_SIG.startswith(req.sig)):
+            async with LOCK:
+                if PERMANENT:
+                    with suppress(Exception):
+                        await PERMANENT.close()
+
+                # Reinitialize permanent
+                from utils import load_config
+                config = load_config()
+                await init_permanent(BrowserConfig(
+                    extra_args=config["crawler"]["browser"].get("extra_args", []),
+                    **config["crawler"]["browser"].get("kwargs", {}),
+                ))
+
+            logger.info("🔄 Restarted permanent browser")
+            return {"success": True, "restarted": "permanent"}
+
+        # Handle hot/cold browser restart
+        target_sig = None
+        pool_type = None
+        browser_config = None
+
+        async with LOCK:
+            # Find browser
+            for sig in HOT_POOL.keys():
+                if sig.startswith(req.sig):
+                    target_sig = sig
+                    pool_type = "hot"
+                    # Would need to reconstruct config (not stored currently)
+                    break
+
+            if not target_sig:
+                for sig in COLD_POOL.keys():
+                    if sig.startswith(req.sig):
+                        target_sig = sig
+                        pool_type = "cold"
+                        break
+
+            if not target_sig:
+                raise HTTPException(404, f"Browser with sig={req.sig} not found")
+
+            # Kill existing
+            if pool_type == "hot":
+                browser = HOT_POOL.pop(target_sig)
+            else:
+                browser = COLD_POOL.pop(target_sig)
+
+            with suppress(Exception):
+                await browser.close()
+
+            # Note: We can't easily recreate with same config without storing it
+            # For now, just kill and let new requests create fresh ones
+            LAST_USED.pop(target_sig, None)
+            USAGE_COUNT.pop(target_sig, None)
+
+        logger.info(f"🔄 Restarted {pool_type} browser (sig={target_sig[:8]})")
+
+        monitor = get_monitor()
+        await monitor.track_janitor_event("restart_browser", target_sig, {"pool": pool_type})
+
+        return {"success": True, "restarted_sig": target_sig[:8], "note": "Browser will be recreated on next request"}
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error restarting browser: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.post("/stats/reset")
+async def reset_stats():
+    """Reset today's endpoint counters."""
+    try:
+        monitor = get_monitor()
+        monitor.endpoint_stats.clear()
+        await monitor._persist_endpoint_stats()
+
+        return {"success": True, "message": "Endpoint stats reset"}
+    except Exception as e:
+        logger.error(f"Error resetting stats: {e}")
+        raise HTTPException(500, str(e))
+
+
+@router.websocket("/ws")
+async def websocket_endpoint(websocket: WebSocket):
+    """WebSocket endpoint for real-time monitoring updates.
+
+    Sends updates every 2 seconds with:
+    - Health stats
+    - Active/completed requests
+    - Browser pool status
+    - Timeline data
+    """
+    await websocket.accept()
+    logger.info("WebSocket client connected")
+
+    try:
+        while True:
+            try:
+                # Gather all monitoring data
+                monitor = get_monitor()
+
+                data = {
+                    "timestamp": asyncio.get_event_loop().time(),
+                    "health": await monitor.get_health_summary(),
+                    "requests": {
+                        "active": monitor.get_active_requests(),
+                        "completed": monitor.get_completed_requests(limit=10)
+                    },
+                    "browsers": await monitor.get_browser_list(),
+                    "timeline": {
+                        "memory": monitor.get_timeline_data("memory", "5m"),
+                        "requests": monitor.get_timeline_data("requests", "5m"),
+                        "browsers": monitor.get_timeline_data("browsers", "5m")
+                    },
+                    "janitor": monitor.get_janitor_log(limit=10),
+                    "errors": monitor.get_errors_log(limit=10)
+                }
+
+                # Send update to client
+                await websocket.send_json(data)
+
+                # Wait 2 seconds before next update
+                await asyncio.sleep(2)
+
+            except WebSocketDisconnect:
+                logger.info("WebSocket client disconnected")
+                break
+            except Exception as e:
+                logger.error(f"WebSocket error: {e}", exc_info=True)
+                await asyncio.sleep(2)  # Continue trying
+
+    except Exception as e:
+        logger.error(f"WebSocket connection error: {e}", exc_info=True)
+    finally:
+        logger.info("WebSocket connection closed")

deploy/docker/server.py

@@ -16,6 +16,7 @@ from fastapi import Request, Depends
 from fastapi.responses import FileResponse
 import base64
 import re
+import logging
 from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
 from api import (
     handle_markdown_request, handle_llm_qa,
@@ -78,6 +79,14 @@ __version__ = "0.5.1-d1"
 MAX_PAGES = config["crawler"]["pool"].get("max_pages", 30)
 GLOBAL_SEM = asyncio.Semaphore(MAX_PAGES)
 
+# ── default browser config helper ─────────────────────────────
+def get_default_browser_config() -> BrowserConfig:
+    """Get default BrowserConfig from config.yml."""
+    return BrowserConfig(
+        extra_args=config["crawler"]["browser"].get("extra_args", []),
+        **config["crawler"]["browser"].get("kwargs", {}),
+    )
+
 # import logging
 # page_log = logging.getLogger("page_cap")
 # orig_arun = AsyncWebCrawler.arun
@@ -103,15 +112,52 @@ AsyncWebCrawler.arun = capped_arun
 
 @asynccontextmanager
 async def lifespan(_: FastAPI):
-    await get_crawler(BrowserConfig(
+    from crawler_pool import init_permanent
+    from monitor import MonitorStats
+    import monitor as monitor_module
+
+    # Initialize monitor
+    monitor_module.monitor_stats = MonitorStats(redis)
+    await monitor_module.monitor_stats.load_from_redis()
+    monitor_module.monitor_stats.start_persistence_worker()
+
+    # Initialize browser pool
+    await init_permanent(BrowserConfig(
         extra_args=config["crawler"]["browser"].get("extra_args", []),
         **config["crawler"]["browser"].get("kwargs", {}),
-    ))           # warm‑up
-    app.state.janitor = asyncio.create_task(janitor())        # idle GC
+    ))
+
+    # Start background tasks
+    app.state.janitor = asyncio.create_task(janitor())
+    app.state.timeline_updater = asyncio.create_task(_timeline_updater())
+
     yield
+
+    # Cleanup
     app.state.janitor.cancel()
+    app.state.timeline_updater.cancel()
+
+    # Monitor cleanup (persist stats and stop workers)
+    from monitor import get_monitor
+    try:
+        await get_monitor().cleanup()
+    except Exception as e:
+        logger.error(f"Monitor cleanup failed: {e}")
+
     await close_all()
 
+async def _timeline_updater():
+    """Update timeline data every 5 seconds."""
+    from monitor import get_monitor
+    while True:
+        await asyncio.sleep(5)
+        try:
+            await asyncio.wait_for(get_monitor().update_timeline(), timeout=4.0)
+        except asyncio.TimeoutError:
+            logger.warning("Timeline update timeout after 4s")
+        except Exception as e:
+            logger.warning(f"Timeline update error: {e}")
+
 # ───────────────────── FastAPI instance ──────────────────────
 app = FastAPI(
     title=config["app"]["title"],
@@ -129,6 +175,25 @@ app.mount(
     name="play",
 )
 
+# ── static monitor dashboard ────────────────────────────────
+MONITOR_DIR = pathlib.Path(__file__).parent / "static" / "monitor"
+if not MONITOR_DIR.exists():
+    raise RuntimeError(f"Monitor assets not found at {MONITOR_DIR}")
+app.mount(
+    "/dashboard",
+    StaticFiles(directory=MONITOR_DIR, html=True),
+    name="monitor_ui",
+)
+
+# ── static assets (logo, etc) ────────────────────────────────
+ASSETS_DIR = pathlib.Path(__file__).parent / "static" / "assets"
+if ASSETS_DIR.exists():
+    app.mount(
+        "/static/assets",
+        StaticFiles(directory=ASSETS_DIR),
+        name="assets",
+    )
+
 
 @app.get("/")
 async def root():
@@ -212,6 +277,12 @@ def _safe_eval_config(expr: str) -> dict:
 # ── job router ──────────────────────────────────────────────
 app.include_router(init_job_router(redis, config, token_dep))
 
+# ── monitor router ──────────────────────────────────────────
+from monitor_routes import router as monitor_router
+app.include_router(monitor_router)
+
+logger = logging.getLogger(__name__)
+
 # ──────────────────────── Endpoints ──────────────────────────
 @app.post("/token")
 async def get_token(req: TokenRequest):
@@ -266,27 +337,20 @@ async def generate_html(
     Crawls the URL, preprocesses the raw HTML for schema extraction, and returns the processed HTML.
     Use when you need sanitized HTML structures for building schemas or further processing.
     """
+    from crawler_pool import get_crawler
     cfg = CrawlerRunConfig()
     try:
-        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-            results = await crawler.arun(url=body.url, config=cfg)
-        # Check if the crawl was successful
+        crawler = await get_crawler(get_default_browser_config())
+        results = await crawler.arun(url=body.url, config=cfg)
         if not results[0].success:
-            raise HTTPException(
-                status_code=500,
-                detail=results[0].error_message or "Crawl failed"
-            )
+            raise HTTPException(500, detail=results[0].error_message or "Crawl failed")
 
         raw_html = results[0].html
         from crawl4ai.utils import preprocess_html_for_schema
         processed_html = preprocess_html_for_schema(raw_html)
         return JSONResponse({"html": processed_html, "url": body.url, "success": True})
     except Exception as e:
-        # Log and raise as HTTP 500 for other exceptions
-        raise HTTPException(
-            status_code=500,
-            detail=str(e)
-        )
+        raise HTTPException(500, detail=str(e))
 
 # Screenshot endpoint
 
@@ -304,16 +368,13 @@ async def generate_screenshot(
     Use when you need an image snapshot of the rendered page. Its recommened to provide an output path to save the screenshot.
     Then in result instead of the screenshot you will get a path to the saved file.
     """
+    from crawler_pool import get_crawler
     try:
-        cfg = CrawlerRunConfig(
-            screenshot=True, screenshot_wait_for=body.screenshot_wait_for)
-        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-            results = await crawler.arun(url=body.url, config=cfg)
+        cfg = CrawlerRunConfig(screenshot=True, screenshot_wait_for=body.screenshot_wait_for)
+        crawler = await get_crawler(get_default_browser_config())
+        results = await crawler.arun(url=body.url, config=cfg)
         if not results[0].success:
-            raise HTTPException(
-                status_code=500,
-                detail=results[0].error_message or "Crawl failed"
-            )
+            raise HTTPException(500, detail=results[0].error_message or "Crawl failed")
         screenshot_data = results[0].screenshot
         if body.output_path:
             abs_path = os.path.abspath(body.output_path)
@@ -323,10 +384,7 @@ async def generate_screenshot(
             return {"success": True, "path": abs_path}
         return {"success": True, "screenshot": screenshot_data}
     except Exception as e:
-        raise HTTPException(
-            status_code=500,
-            detail=str(e)
-        )
+        raise HTTPException(500, detail=str(e))
 
 # PDF endpoint
 
@@ -344,15 +402,13 @@ async def generate_pdf(
     Use when you need a printable or archivable snapshot of the page. It is recommended to provide an output path to save the PDF.
     Then in result instead of the PDF you will get a path to the saved file.
     """
+    from crawler_pool import get_crawler
     try:
         cfg = CrawlerRunConfig(pdf=True)
-        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-            results = await crawler.arun(url=body.url, config=cfg)
+        crawler = await get_crawler(get_default_browser_config())
+        results = await crawler.arun(url=body.url, config=cfg)
         if not results[0].success:
-            raise HTTPException(
-                status_code=500,
-                detail=results[0].error_message or "Crawl failed"
-            )
+            raise HTTPException(500, detail=results[0].error_message or "Crawl failed")
         pdf_data = results[0].pdf
         if body.output_path:
             abs_path = os.path.abspath(body.output_path)
@@ -362,10 +418,7 @@ async def generate_pdf(
             return {"success": True, "path": abs_path}
         return {"success": True, "pdf": base64.b64encode(pdf_data).decode()}
     except Exception as e:
-        raise HTTPException(
-            status_code=500,
-            detail=str(e)
-        )
+        raise HTTPException(500, detail=str(e))
 
 
 @app.post("/execute_js")
@@ -421,23 +474,17 @@ async def execute_js(
         ```
 
     """
+    from crawler_pool import get_crawler
     try:
         cfg = CrawlerRunConfig(js_code=body.scripts)
-        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-            results = await crawler.arun(url=body.url, config=cfg)
+        crawler = await get_crawler(get_default_browser_config())
+        results = await crawler.arun(url=body.url, config=cfg)
         if not results[0].success:
-            raise HTTPException(
-                status_code=500,
-                detail=results[0].error_message or "Crawl failed"
-            )
-        # Return JSON-serializable dict of the first CrawlResult
+            raise HTTPException(500, detail=results[0].error_message or "Crawl failed")
         data = results[0].model_dump()
         return JSONResponse(data)
     except Exception as e:
-        raise HTTPException(
-            status_code=500,
-            detail=str(e)
-        )
+        raise HTTPException(500, detail=str(e))
 
 
 @app.get("/llm/{url:path}")

deploy/docker/static/playground/index.html

@@ -167,11 +167,14 @@
             </a>
         </h1>
 
-        <div class="ml-auto flex space-x-2">
-            <button id="play-tab"
-                class="px-3 py-1 rounded-t bg-surface border border-b-0 border-border text-primary">Playground</button>
-            <button id="stress-tab" class="px-3 py-1 rounded-t border border-border hover:bg-surface">Stress
-                Test</button>
+        <div class="ml-auto flex items-center space-x-4">
+            <a href="/dashboard" class="text-xs text-secondary hover:text-primary underline">Monitor</a>
+            <div class="flex space-x-2">
+                <button id="play-tab"
+                    class="px-3 py-1 rounded-t bg-surface border border-b-0 border-border text-primary">Playground</button>
+                <button id="stress-tab" class="px-3 py-1 rounded-t border border-border hover:bg-surface">Stress
+                    Test</button>
+            </div>
         </div>
     </header>
 

deploy/docker/test-websocket.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python3
+"""
+Quick WebSocket test - Connect to monitor WebSocket and print updates
+"""
+import asyncio
+import websockets
+import json
+
+async def test_websocket():
+    uri = "ws://localhost:11235/monitor/ws"
+    print(f"Connecting to {uri}...")
+
+    try:
+        async with websockets.connect(uri) as websocket:
+            print("✅ Connected!")
+
+            # Receive and print 5 updates
+            for i in range(5):
+                message = await websocket.recv()
+                data = json.loads(message)
+                print(f"\n📊 Update #{i+1}:")
+                print(f"  - Health: CPU {data['health']['container']['cpu_percent']}%, Memory {data['health']['container']['memory_percent']}%")
+                print(f"  - Active Requests: {len(data['requests']['active'])}")
+                print(f"  - Browsers: {len(data['browsers'])}")
+
+    except Exception as e:
+        print(f"❌ Error: {e}")
+        return 1
+
+    print("\n✅ WebSocket test passed!")
+    return 0
+
+if __name__ == "__main__":
+    exit(asyncio.run(test_websocket()))

deploy/docker/tests/demo_monitor_dashboard.py

@@ -0,0 +1,164 @@
+#!/usr/bin/env python3
+"""
+Monitor Dashboard Demo Script
+Generates varied activity to showcase all monitoring features for video recording.
+"""
+import httpx
+import asyncio
+import time
+from datetime import datetime
+
+BASE_URL = "http://localhost:11235"
+
+async def demo_dashboard():
+    print("🎬 Monitor Dashboard Demo - Starting...\n")
+    print(f"📊 Dashboard: {BASE_URL}/dashboard")
+    print("=" * 60)
+
+    async with httpx.AsyncClient(timeout=60.0) as client:
+
+        # Phase 1: Simple requests (permanent browser)
+        print("\n🔷 Phase 1: Testing permanent browser pool")
+        print("-" * 60)
+        for i in range(5):
+            print(f"  {i+1}/5 Request to /crawl (default config)...")
+            try:
+                r = await client.post(
+                    f"{BASE_URL}/crawl",
+                    json={"urls": [f"https://httpbin.org/html?req={i}"], "crawler_config": {}}
+                )
+                print(f"     ✅ Status: {r.status_code}, Time: {r.elapsed.total_seconds():.2f}s")
+            except Exception as e:
+                print(f"     ❌ Error: {e}")
+            await asyncio.sleep(1)  # Small delay between requests
+
+        # Phase 2: Create variant browsers (different configs)
+        print("\n🔶 Phase 2: Testing cold→hot pool promotion")
+        print("-" * 60)
+        viewports = [
+            {"width": 1920, "height": 1080},
+            {"width": 1280, "height": 720},
+            {"width": 800, "height": 600}
+        ]
+
+        for idx, viewport in enumerate(viewports):
+            print(f"  Viewport {viewport['width']}x{viewport['height']}:")
+            for i in range(4):  # 4 requests each to trigger promotion at 3
+                try:
+                    r = await client.post(
+                        f"{BASE_URL}/crawl",
+                        json={
+                            "urls": [f"https://httpbin.org/json?v={idx}&r={i}"],
+                            "browser_config": {"viewport": viewport},
+                            "crawler_config": {}
+                        }
+                    )
+                    print(f"    {i+1}/4 ✅ {r.status_code} - Should see cold→hot after 3 uses")
+                except Exception as e:
+                    print(f"    {i+1}/4 ❌ {e}")
+                await asyncio.sleep(0.5)
+
+        # Phase 3: Concurrent burst (stress pool)
+        print("\n🔷 Phase 3: Concurrent burst (10 parallel)")
+        print("-" * 60)
+        tasks = []
+        for i in range(10):
+            tasks.append(
+                client.post(
+                    f"{BASE_URL}/crawl",
+                    json={"urls": [f"https://httpbin.org/delay/2?burst={i}"], "crawler_config": {}}
+                )
+            )
+
+        print("  Sending 10 concurrent requests...")
+        start = time.time()
+        results = await asyncio.gather(*tasks, return_exceptions=True)
+        elapsed = time.time() - start
+
+        successes = sum(1 for r in results if not isinstance(r, Exception) and r.status_code == 200)
+        print(f"  ✅ {successes}/10 succeeded in {elapsed:.2f}s")
+
+        # Phase 4: Multi-endpoint coverage
+        print("\n🔶 Phase 4: Testing multiple endpoints")
+        print("-" * 60)
+        endpoints = [
+            ("/md", {"url": "https://httpbin.org/html", "f": "fit", "c": "0"}),
+            ("/screenshot", {"url": "https://httpbin.org/html"}),
+            ("/pdf", {"url": "https://httpbin.org/html"}),
+        ]
+
+        for endpoint, payload in endpoints:
+            print(f"  Testing {endpoint}...")
+            try:
+                if endpoint == "/md":
+                    r = await client.post(f"{BASE_URL}{endpoint}", json=payload)
+                else:
+                    r = await client.post(f"{BASE_URL}{endpoint}", json=payload)
+                print(f"    ✅ {r.status_code}")
+            except Exception as e:
+                print(f"    ❌ {e}")
+            await asyncio.sleep(1)
+
+        # Phase 5: Intentional error (to populate errors tab)
+        print("\n🔷 Phase 5: Generating error examples")
+        print("-" * 60)
+        print("  Triggering invalid URL error...")
+        try:
+            r = await client.post(
+                f"{BASE_URL}/crawl",
+                json={"urls": ["invalid://bad-url"], "crawler_config": {}}
+            )
+            print(f"    Response: {r.status_code}")
+        except Exception as e:
+            print(f"    ✅ Error captured: {type(e).__name__}")
+
+        # Phase 6: Wait for janitor activity
+        print("\n🔶 Phase 6: Waiting for janitor cleanup...")
+        print("-" * 60)
+        print("  Idle for 40s to allow janitor to clean cold pool browsers...")
+        for i in range(40, 0, -10):
+            print(f"    {i}s remaining... (Check dashboard for cleanup events)")
+            await asyncio.sleep(10)
+
+        # Phase 7: Final stats check
+        print("\n🔷 Phase 7: Final dashboard state")
+        print("-" * 60)
+
+        r = await client.get(f"{BASE_URL}/monitor/health")
+        health = r.json()
+        print(f"  Memory: {health['container']['memory_percent']:.1f}%")
+        print(f"  Browsers: Perm={health['pool']['permanent']['active']}, "
+              f"Hot={health['pool']['hot']['count']}, Cold={health['pool']['cold']['count']}")
+
+        r = await client.get(f"{BASE_URL}/monitor/endpoints/stats")
+        stats = r.json()
+        print(f"\n  Endpoint Stats:")
+        for endpoint, data in stats.items():
+            print(f"    {endpoint}: {data['count']} req, "
+                  f"{data['avg_latency_ms']:.0f}ms avg, "
+                  f"{data['success_rate_percent']:.1f}% success")
+
+        r = await client.get(f"{BASE_URL}/monitor/browsers")
+        browsers = r.json()
+        print(f"\n  Pool Efficiency:")
+        print(f"    Total browsers: {browsers['summary']['total_count']}")
+        print(f"    Memory usage: {browsers['summary']['total_memory_mb']} MB")
+        print(f"    Reuse rate: {browsers['summary']['reuse_rate_percent']:.1f}%")
+
+    print("\n" + "=" * 60)
+    print("✅ Demo complete! Dashboard is now populated with rich data.")
+    print(f"\n📹 Recording tip: Refresh {BASE_URL}/dashboard")
+    print("   You should see:")
+    print("   • Active & completed requests")
+    print("   • Browser pool (permanent + hot/cold)")
+    print("   • Janitor cleanup events")
+    print("   • Endpoint analytics")
+    print("   • Memory timeline")
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(demo_dashboard())
+    except KeyboardInterrupt:
+        print("\n\n⚠️  Demo interrupted by user")
+    except Exception as e:
+        print(f"\n\n❌ Demo failed: {e}")

deploy/docker/tests/requirements.txt

@@ -0,0 +1,2 @@
+httpx>=0.25.0
+docker>=7.0.0

deploy/docker/tests/test_1_basic.py

@@ -0,0 +1,138 @@
+#!/usr/bin/env python3
+"""
+Test 1: Basic Container Health + Single Endpoint
+- Starts container
+- Hits /health endpoint 10 times
+- Reports success rate and basic latency
+"""
+import asyncio
+import time
+import docker
+import httpx
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+REQUESTS = 10
+
+async def test_endpoint(url: str, count: int):
+    """Hit endpoint multiple times, return stats."""
+    results = []
+    async with httpx.AsyncClient(timeout=30.0) as client:
+        for i in range(count):
+            start = time.time()
+            try:
+                resp = await client.get(url)
+                elapsed = (time.time() - start) * 1000  # ms
+                results.append({
+                    "success": resp.status_code == 200,
+                    "latency_ms": elapsed,
+                    "status": resp.status_code
+                })
+                print(f"  [{i+1}/{count}] ✓ {resp.status_code} - {elapsed:.0f}ms")
+            except Exception as e:
+                results.append({
+                    "success": False,
+                    "latency_ms": None,
+                    "error": str(e)
+                })
+                print(f"  [{i+1}/{count}] ✗ Error: {e}")
+    return results
+
+def start_container(client, image: str, name: str, port: int):
+    """Start container, return container object."""
+    # Clean up existing
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container '{name}'...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container '{name}' from image '{image}'...")
+    container = client.containers.run(
+        image,
+        name=name,
+        ports={f"{port}/tcp": port},
+        detach=True,
+        shm_size="1g",
+        environment={"PYTHON_ENV": "production"}
+    )
+
+    # Wait for health
+    print(f"⏳ Waiting for container to be healthy...")
+    for _ in range(30):  # 30s timeout
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                # Quick health check
+                import requests
+                resp = requests.get(f"http://localhost:{port}/health", timeout=2)
+                if resp.status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+def stop_container(container):
+    """Stop and remove container."""
+    print(f"🛑 Stopping container...")
+    container.stop()
+    container.remove()
+    print(f"✅ Container removed")
+
+async def main():
+    print("="*60)
+    print("TEST 1: Basic Container Health + Single Endpoint")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+
+    try:
+        # Start container
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        # Test /health endpoint
+        print(f"\n📊 Testing /health endpoint ({REQUESTS} requests)...")
+        url = f"http://localhost:{PORT}/health"
+        results = await test_endpoint(url, REQUESTS)
+
+        # Calculate stats
+        successes = sum(1 for r in results if r["success"])
+        success_rate = (successes / len(results)) * 100
+        latencies = [r["latency_ms"] for r in results if r["latency_ms"] is not None]
+        avg_latency = sum(latencies) / len(latencies) if latencies else 0
+
+        # Print results
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"  Success Rate: {success_rate:.1f}% ({successes}/{len(results)})")
+        print(f"  Avg Latency:  {avg_latency:.0f}ms")
+        if latencies:
+            print(f"  Min Latency:  {min(latencies):.0f}ms")
+            print(f"  Max Latency:  {max(latencies):.0f}ms")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        if success_rate >= 100:
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            print(f"❌ TEST FAILED (expected 100% success rate)")
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        return 1
+    finally:
+        if container:
+            stop_container(container)
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_2_memory.py

@@ -0,0 +1,205 @@
+#!/usr/bin/env python3
+"""
+Test 2: Docker Stats Monitoring
+- Extends Test 1 with real-time container stats
+- Monitors memory % and CPU during requests
+- Reports baseline, peak, and final memory
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+REQUESTS = 20  # More requests to see memory usage
+
+# Stats tracking
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background thread to collect container stats."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+
+        try:
+            # Extract memory stats
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)  # MB
+            mem_limit = stat['memory_stats'].get('limit', 1) / (1024 * 1024)
+            mem_percent = (mem_usage / mem_limit * 100) if mem_limit > 0 else 0
+
+            # Extract CPU stats (handle missing fields on Mac)
+            cpu_percent = 0
+            try:
+                cpu_delta = stat['cpu_stats']['cpu_usage']['total_usage'] - \
+                           stat['precpu_stats']['cpu_usage']['total_usage']
+                system_delta = stat['cpu_stats'].get('system_cpu_usage', 0) - \
+                              stat['precpu_stats'].get('system_cpu_usage', 0)
+                if system_delta > 0:
+                    num_cpus = stat['cpu_stats'].get('online_cpus', 1)
+                    cpu_percent = (cpu_delta / system_delta * num_cpus * 100.0)
+            except (KeyError, ZeroDivisionError):
+                pass
+
+            stats_history.append({
+                'timestamp': time.time(),
+                'memory_mb': mem_usage,
+                'memory_percent': mem_percent,
+                'cpu_percent': cpu_percent
+            })
+        except Exception as e:
+            # Skip malformed stats
+            pass
+
+        time.sleep(0.5)  # Sample every 500ms
+
+async def test_endpoint(url: str, count: int):
+    """Hit endpoint, return stats."""
+    results = []
+    async with httpx.AsyncClient(timeout=30.0) as client:
+        for i in range(count):
+            start = time.time()
+            try:
+                resp = await client.get(url)
+                elapsed = (time.time() - start) * 1000
+                results.append({
+                    "success": resp.status_code == 200,
+                    "latency_ms": elapsed,
+                })
+                if (i + 1) % 5 == 0:  # Print every 5 requests
+                    print(f"  [{i+1}/{count}] ✓ {resp.status_code} - {elapsed:.0f}ms")
+            except Exception as e:
+                results.append({"success": False, "error": str(e)})
+                print(f"  [{i+1}/{count}] ✗ Error: {e}")
+    return results
+
+def start_container(client, image: str, name: str, port: int):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container '{name}'...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container '{name}'...")
+    container = client.containers.run(
+        image,
+        name=name,
+        ports={f"{port}/tcp": port},
+        detach=True,
+        shm_size="1g",
+        mem_limit="4g",  # Set explicit memory limit
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                resp = requests.get(f"http://localhost:{port}/health", timeout=2)
+                if resp.status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+def stop_container(container):
+    """Stop container."""
+    print(f"🛑 Stopping container...")
+    container.stop()
+    container.remove()
+
+async def main():
+    print("="*60)
+    print("TEST 2: Docker Stats Monitoring")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        # Start container
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        # Start stats monitoring in background
+        print(f"\n📊 Starting stats monitor...")
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        # Wait a bit for baseline
+        await asyncio.sleep(2)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline memory: {baseline_mem:.1f} MB")
+
+        # Test /health endpoint
+        print(f"\n🔄 Running {REQUESTS} requests to /health...")
+        url = f"http://localhost:{PORT}/health"
+        results = await test_endpoint(url, REQUESTS)
+
+        # Wait a bit to capture peak
+        await asyncio.sleep(1)
+
+        # Stop monitoring
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Calculate stats
+        successes = sum(1 for r in results if r.get("success"))
+        success_rate = (successes / len(results)) * 100
+        latencies = [r["latency_ms"] for r in results if "latency_ms" in r]
+        avg_latency = sum(latencies) / len(latencies) if latencies else 0
+
+        # Memory stats
+        memory_samples = [s['memory_mb'] for s in stats_history]
+        peak_mem = max(memory_samples) if memory_samples else 0
+        final_mem = memory_samples[-1] if memory_samples else 0
+        mem_delta = final_mem - baseline_mem
+
+        # Print results
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"  Success Rate: {success_rate:.1f}% ({successes}/{len(results)})")
+        print(f"  Avg Latency:  {avg_latency:.0f}ms")
+        print(f"\n  Memory Stats:")
+        print(f"    Baseline: {baseline_mem:.1f} MB")
+        print(f"    Peak:     {peak_mem:.1f} MB")
+        print(f"    Final:    {final_mem:.1f} MB")
+        print(f"    Delta:    {mem_delta:+.1f} MB")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        if success_rate >= 100 and mem_delta < 100:  # No significant memory growth
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            if success_rate < 100:
+                print(f"❌ TEST FAILED (success rate < 100%)")
+            if mem_delta >= 100:
+                print(f"⚠️  WARNING: Memory grew by {mem_delta:.1f} MB")
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            stop_container(container)
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_3_pool.py

@@ -0,0 +1,229 @@
+#!/usr/bin/env python3
+"""
+Test 3: Pool Validation - Permanent Browser Reuse
+- Tests /html endpoint (should use permanent browser)
+- Monitors container logs for pool hit markers
+- Validates browser reuse rate
+- Checks memory after browser creation
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+REQUESTS = 30
+
+# Stats tracking
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background stats collector."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+        try:
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
+            stats_history.append({
+                'timestamp': time.time(),
+                'memory_mb': mem_usage,
+            })
+        except:
+            pass
+        time.sleep(0.5)
+
+def count_log_markers(container):
+    """Extract pool usage markers from logs."""
+    logs = container.logs().decode('utf-8')
+
+    permanent_hits = logs.count("🔥 Using permanent browser")
+    hot_hits = logs.count("♨️  Using hot pool browser")
+    cold_hits = logs.count("❄️  Using cold pool browser")
+    new_created = logs.count("🆕 Creating new browser")
+
+    return {
+        'permanent_hits': permanent_hits,
+        'hot_hits': hot_hits,
+        'cold_hits': cold_hits,
+        'new_created': new_created,
+        'total_hits': permanent_hits + hot_hits + cold_hits
+    }
+
+async def test_endpoint(url: str, count: int):
+    """Hit endpoint multiple times."""
+    results = []
+    async with httpx.AsyncClient(timeout=60.0) as client:
+        for i in range(count):
+            start = time.time()
+            try:
+                resp = await client.post(url, json={"url": "https://httpbin.org/html"})
+                elapsed = (time.time() - start) * 1000
+                results.append({
+                    "success": resp.status_code == 200,
+                    "latency_ms": elapsed,
+                })
+                if (i + 1) % 10 == 0:
+                    print(f"  [{i+1}/{count}] ✓ {resp.status_code} - {elapsed:.0f}ms")
+            except Exception as e:
+                results.append({"success": False, "error": str(e)})
+                print(f"  [{i+1}/{count}] ✗ Error: {e}")
+    return results
+
+def start_container(client, image: str, name: str, port: int):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container...")
+    container = client.containers.run(
+        image,
+        name=name,
+        ports={f"{port}/tcp": port},
+        detach=True,
+        shm_size="1g",
+        mem_limit="4g",
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                resp = requests.get(f"http://localhost:{port}/health", timeout=2)
+                if resp.status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+def stop_container(container):
+    """Stop container."""
+    print(f"🛑 Stopping container...")
+    container.stop()
+    container.remove()
+
+async def main():
+    print("="*60)
+    print("TEST 3: Pool Validation - Permanent Browser Reuse")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        # Start container
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        # Wait for permanent browser initialization
+        print(f"\n⏳ Waiting for permanent browser init (3s)...")
+        await asyncio.sleep(3)
+
+        # Start stats monitoring
+        print(f"📊 Starting stats monitor...")
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        await asyncio.sleep(1)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline (with permanent browser): {baseline_mem:.1f} MB")
+
+        # Test /html endpoint (uses permanent browser for default config)
+        print(f"\n🔄 Running {REQUESTS} requests to /html...")
+        url = f"http://localhost:{PORT}/html"
+        results = await test_endpoint(url, REQUESTS)
+
+        # Wait a bit
+        await asyncio.sleep(1)
+
+        # Stop monitoring
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Analyze logs for pool markers
+        print(f"\n📋 Analyzing pool usage...")
+        pool_stats = count_log_markers(container)
+
+        # Calculate request stats
+        successes = sum(1 for r in results if r.get("success"))
+        success_rate = (successes / len(results)) * 100
+        latencies = [r["latency_ms"] for r in results if "latency_ms" in r]
+        avg_latency = sum(latencies) / len(latencies) if latencies else 0
+
+        # Memory stats
+        memory_samples = [s['memory_mb'] for s in stats_history]
+        peak_mem = max(memory_samples) if memory_samples else 0
+        final_mem = memory_samples[-1] if memory_samples else 0
+        mem_delta = final_mem - baseline_mem
+
+        # Calculate reuse rate
+        total_requests = len(results)
+        total_pool_hits = pool_stats['total_hits']
+        reuse_rate = (total_pool_hits / total_requests * 100) if total_requests > 0 else 0
+
+        # Print results
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"  Success Rate: {success_rate:.1f}% ({successes}/{len(results)})")
+        print(f"  Avg Latency:  {avg_latency:.0f}ms")
+        print(f"\n  Pool Stats:")
+        print(f"    🔥 Permanent Hits: {pool_stats['permanent_hits']}")
+        print(f"    ♨️  Hot Pool Hits:   {pool_stats['hot_hits']}")
+        print(f"    ❄️  Cold Pool Hits:  {pool_stats['cold_hits']}")
+        print(f"    🆕 New Created:    {pool_stats['new_created']}")
+        print(f"    📊 Reuse Rate:     {reuse_rate:.1f}%")
+        print(f"\n  Memory Stats:")
+        print(f"    Baseline: {baseline_mem:.1f} MB")
+        print(f"    Peak:     {peak_mem:.1f} MB")
+        print(f"    Final:    {final_mem:.1f} MB")
+        print(f"    Delta:    {mem_delta:+.1f} MB")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        passed = True
+        if success_rate < 100:
+            print(f"❌ FAIL: Success rate {success_rate:.1f}% < 100%")
+            passed = False
+        if reuse_rate < 80:
+            print(f"❌ FAIL: Reuse rate {reuse_rate:.1f}% < 80% (expected high permanent browser usage)")
+            passed = False
+        if pool_stats['permanent_hits'] < (total_requests * 0.8):
+            print(f"⚠️  WARNING: Only {pool_stats['permanent_hits']} permanent hits out of {total_requests} requests")
+        if mem_delta > 200:
+            print(f"⚠️  WARNING: Memory grew by {mem_delta:.1f} MB (possible browser leak)")
+
+        if passed:
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            stop_container(container)
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_4_concurrent.py

@@ -0,0 +1,236 @@
+#!/usr/bin/env python3
+"""
+Test 4: Concurrent Load Testing
+- Tests pool under concurrent load
+- Escalates: 10 → 50 → 100 concurrent requests
+- Validates latency distribution (P50, P95, P99)
+- Monitors memory stability
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+from collections import defaultdict
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+LOAD_LEVELS = [
+    {"name": "Light", "concurrent": 10, "requests": 20},
+    {"name": "Medium", "concurrent": 50, "requests": 100},
+    {"name": "Heavy", "concurrent": 100, "requests": 200},
+]
+
+# Stats
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background stats collector."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+        try:
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
+            stats_history.append({'timestamp': time.time(), 'memory_mb': mem_usage})
+        except:
+            pass
+        time.sleep(0.5)
+
+def count_log_markers(container):
+    """Extract pool markers."""
+    logs = container.logs().decode('utf-8')
+    return {
+        'permanent': logs.count("🔥 Using permanent browser"),
+        'hot': logs.count("♨️  Using hot pool browser"),
+        'cold': logs.count("❄️  Using cold pool browser"),
+        'new': logs.count("🆕 Creating new browser"),
+    }
+
+async def hit_endpoint(client, url, payload, semaphore):
+    """Single request with concurrency control."""
+    async with semaphore:
+        start = time.time()
+        try:
+            resp = await client.post(url, json=payload, timeout=60.0)
+            elapsed = (time.time() - start) * 1000
+            return {"success": resp.status_code == 200, "latency_ms": elapsed}
+        except Exception as e:
+            return {"success": False, "error": str(e)}
+
+async def run_concurrent_test(url, payload, concurrent, total_requests):
+    """Run concurrent requests."""
+    semaphore = asyncio.Semaphore(concurrent)
+    async with httpx.AsyncClient() as client:
+        tasks = [hit_endpoint(client, url, payload, semaphore) for _ in range(total_requests)]
+        results = await asyncio.gather(*tasks)
+    return results
+
+def calculate_percentiles(latencies):
+    """Calculate P50, P95, P99."""
+    if not latencies:
+        return 0, 0, 0
+    sorted_lat = sorted(latencies)
+    n = len(sorted_lat)
+    return (
+        sorted_lat[int(n * 0.50)],
+        sorted_lat[int(n * 0.95)],
+        sorted_lat[int(n * 0.99)],
+    )
+
+def start_container(client, image, name, port):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container...")
+    container = client.containers.run(
+        image, name=name, ports={f"{port}/tcp": port},
+        detach=True, shm_size="1g", mem_limit="4g",
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                if requests.get(f"http://localhost:{port}/health", timeout=2).status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+async def main():
+    print("="*60)
+    print("TEST 4: Concurrent Load Testing")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        print(f"\n⏳ Waiting for permanent browser init (3s)...")
+        await asyncio.sleep(3)
+
+        # Start monitoring
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        await asyncio.sleep(1)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline: {baseline_mem:.1f} MB\n")
+
+        url = f"http://localhost:{PORT}/html"
+        payload = {"url": "https://httpbin.org/html"}
+
+        all_results = []
+        level_stats = []
+
+        # Run load levels
+        for level in LOAD_LEVELS:
+            print(f"{'='*60}")
+            print(f"🔄 {level['name']} Load: {level['concurrent']} concurrent, {level['requests']} total")
+            print(f"{'='*60}")
+
+            start_time = time.time()
+            results = await run_concurrent_test(url, payload, level['concurrent'], level['requests'])
+            duration = time.time() - start_time
+
+            successes = sum(1 for r in results if r.get("success"))
+            success_rate = (successes / len(results)) * 100
+            latencies = [r["latency_ms"] for r in results if "latency_ms" in r]
+            p50, p95, p99 = calculate_percentiles(latencies)
+            avg_lat = sum(latencies) / len(latencies) if latencies else 0
+
+            print(f"  Duration:     {duration:.1f}s")
+            print(f"  Success:      {success_rate:.1f}% ({successes}/{len(results)})")
+            print(f"  Avg Latency:  {avg_lat:.0f}ms")
+            print(f"  P50/P95/P99:  {p50:.0f}ms / {p95:.0f}ms / {p99:.0f}ms")
+
+            level_stats.append({
+                'name': level['name'],
+                'concurrent': level['concurrent'],
+                'success_rate': success_rate,
+                'avg_latency': avg_lat,
+                'p50': p50, 'p95': p95, 'p99': p99,
+            })
+            all_results.extend(results)
+
+            await asyncio.sleep(2)  # Cool down between levels
+
+        # Stop monitoring
+        await asyncio.sleep(1)
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Final stats
+        pool_stats = count_log_markers(container)
+        memory_samples = [s['memory_mb'] for s in stats_history]
+        peak_mem = max(memory_samples) if memory_samples else 0
+        final_mem = memory_samples[-1] if memory_samples else 0
+
+        print(f"\n{'='*60}")
+        print(f"FINAL RESULTS:")
+        print(f"{'='*60}")
+        print(f"  Total Requests: {len(all_results)}")
+        print(f"\n  Pool Utilization:")
+        print(f"    🔥 Permanent: {pool_stats['permanent']}")
+        print(f"    ♨️  Hot:       {pool_stats['hot']}")
+        print(f"    ❄️  Cold:      {pool_stats['cold']}")
+        print(f"    🆕 New:       {pool_stats['new']}")
+        print(f"\n  Memory:")
+        print(f"    Baseline: {baseline_mem:.1f} MB")
+        print(f"    Peak:     {peak_mem:.1f} MB")
+        print(f"    Final:    {final_mem:.1f} MB")
+        print(f"    Delta:    {final_mem - baseline_mem:+.1f} MB")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        passed = True
+        for ls in level_stats:
+            if ls['success_rate'] < 99:
+                print(f"❌ FAIL: {ls['name']} success rate {ls['success_rate']:.1f}% < 99%")
+                passed = False
+            if ls['p99'] > 10000:  # 10s threshold
+                print(f"⚠️  WARNING: {ls['name']} P99 latency {ls['p99']:.0f}ms very high")
+
+        if final_mem - baseline_mem > 300:
+            print(f"⚠️  WARNING: Memory grew {final_mem - baseline_mem:.1f} MB")
+
+        if passed:
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            print(f"🛑 Stopping container...")
+            container.stop()
+            container.remove()
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_5_pool_stress.py

@@ -0,0 +1,267 @@
+#!/usr/bin/env python3
+"""
+Test 5: Pool Stress - Mixed Configs
+- Tests hot/cold pool with different browser configs
+- Uses different viewports to create config variants
+- Validates cold → hot promotion after 3 uses
+- Monitors pool tier distribution
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+import random
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+REQUESTS_PER_CONFIG = 5  # 5 requests per config variant
+
+# Different viewport configs to test pool tiers
+VIEWPORT_CONFIGS = [
+    None,  # Default (permanent browser)
+    {"width": 1920, "height": 1080},  # Desktop
+    {"width": 1024, "height": 768},   # Tablet
+    {"width": 375, "height": 667},    # Mobile
+]
+
+# Stats
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background stats collector."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+        try:
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
+            stats_history.append({'timestamp': time.time(), 'memory_mb': mem_usage})
+        except:
+            pass
+        time.sleep(0.5)
+
+def analyze_pool_logs(container):
+    """Extract detailed pool stats from logs."""
+    logs = container.logs().decode('utf-8')
+
+    permanent = logs.count("🔥 Using permanent browser")
+    hot = logs.count("♨️  Using hot pool browser")
+    cold = logs.count("❄️  Using cold pool browser")
+    new = logs.count("🆕 Creating new browser")
+    promotions = logs.count("⬆️  Promoting to hot pool")
+
+    return {
+        'permanent': permanent,
+        'hot': hot,
+        'cold': cold,
+        'new': new,
+        'promotions': promotions,
+        'total': permanent + hot + cold
+    }
+
+async def crawl_with_viewport(client, url, viewport):
+    """Single request with specific viewport."""
+    payload = {
+        "urls": ["https://httpbin.org/html"],
+        "browser_config": {},
+        "crawler_config": {}
+    }
+
+    # Add viewport if specified
+    if viewport:
+        payload["browser_config"] = {
+            "type": "BrowserConfig",
+            "params": {
+                "viewport": {"type": "dict", "value": viewport},
+                "headless": True,
+                "text_mode": True,
+                "extra_args": [
+                    "--no-sandbox",
+                    "--disable-dev-shm-usage",
+                    "--disable-gpu",
+                    "--disable-software-rasterizer",
+                    "--disable-web-security",
+                    "--allow-insecure-localhost",
+                    "--ignore-certificate-errors"
+                ]
+            }
+        }
+
+    start = time.time()
+    try:
+        resp = await client.post(url, json=payload, timeout=60.0)
+        elapsed = (time.time() - start) * 1000
+        return {"success": resp.status_code == 200, "latency_ms": elapsed, "viewport": viewport}
+    except Exception as e:
+        return {"success": False, "error": str(e), "viewport": viewport}
+
+def start_container(client, image, name, port):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container...")
+    container = client.containers.run(
+        image, name=name, ports={f"{port}/tcp": port},
+        detach=True, shm_size="1g", mem_limit="4g",
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                if requests.get(f"http://localhost:{port}/health", timeout=2).status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+async def main():
+    print("="*60)
+    print("TEST 5: Pool Stress - Mixed Configs")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        print(f"\n⏳ Waiting for permanent browser init (3s)...")
+        await asyncio.sleep(3)
+
+        # Start monitoring
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        await asyncio.sleep(1)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline: {baseline_mem:.1f} MB\n")
+
+        url = f"http://localhost:{PORT}/crawl"
+
+        print(f"Testing {len(VIEWPORT_CONFIGS)} different configs:")
+        for i, vp in enumerate(VIEWPORT_CONFIGS):
+            vp_str = "Default" if vp is None else f"{vp['width']}x{vp['height']}"
+            print(f"  {i+1}. {vp_str}")
+        print()
+
+        # Run requests: repeat each config REQUESTS_PER_CONFIG times
+        all_results = []
+        config_sequence = []
+
+        for _ in range(REQUESTS_PER_CONFIG):
+            for viewport in VIEWPORT_CONFIGS:
+                config_sequence.append(viewport)
+
+        # Shuffle to mix configs
+        random.shuffle(config_sequence)
+
+        print(f"🔄 Running {len(config_sequence)} requests with mixed configs...")
+
+        async with httpx.AsyncClient() as http_client:
+            for i, viewport in enumerate(config_sequence):
+                result = await crawl_with_viewport(http_client, url, viewport)
+                all_results.append(result)
+
+                if (i + 1) % 5 == 0:
+                    vp_str = "default" if result['viewport'] is None else f"{result['viewport']['width']}x{result['viewport']['height']}"
+                    status = "✓" if result.get('success') else "✗"
+                    lat = f"{result.get('latency_ms', 0):.0f}ms" if 'latency_ms' in result else "error"
+                    print(f"  [{i+1}/{len(config_sequence)}] {status} {vp_str} - {lat}")
+
+        # Stop monitoring
+        await asyncio.sleep(2)
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Analyze results
+        pool_stats = analyze_pool_logs(container)
+
+        successes = sum(1 for r in all_results if r.get("success"))
+        success_rate = (successes / len(all_results)) * 100
+        latencies = [r["latency_ms"] for r in all_results if "latency_ms" in r]
+        avg_lat = sum(latencies) / len(latencies) if latencies else 0
+
+        memory_samples = [s['memory_mb'] for s in stats_history]
+        peak_mem = max(memory_samples) if memory_samples else 0
+        final_mem = memory_samples[-1] if memory_samples else 0
+
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"{'='*60}")
+        print(f"  Requests:     {len(all_results)}")
+        print(f"  Success Rate: {success_rate:.1f}% ({successes}/{len(all_results)})")
+        print(f"  Avg Latency:  {avg_lat:.0f}ms")
+        print(f"\n  Pool Statistics:")
+        print(f"    🔥 Permanent: {pool_stats['permanent']}")
+        print(f"    ♨️  Hot:       {pool_stats['hot']}")
+        print(f"    ❄️  Cold:      {pool_stats['cold']}")
+        print(f"    🆕 New:       {pool_stats['new']}")
+        print(f"    ⬆️  Promotions: {pool_stats['promotions']}")
+        print(f"    📊 Reuse:     {(pool_stats['total'] / len(all_results) * 100):.1f}%")
+        print(f"\n  Memory:")
+        print(f"    Baseline: {baseline_mem:.1f} MB")
+        print(f"    Peak:     {peak_mem:.1f} MB")
+        print(f"    Final:    {final_mem:.1f} MB")
+        print(f"    Delta:    {final_mem - baseline_mem:+.1f} MB")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        passed = True
+
+        if success_rate < 99:
+            print(f"❌ FAIL: Success rate {success_rate:.1f}% < 99%")
+            passed = False
+
+        # Should see promotions since we repeat each config 5 times
+        if pool_stats['promotions'] < (len(VIEWPORT_CONFIGS) - 1):  # -1 for default
+            print(f"⚠️  WARNING: Only {pool_stats['promotions']} promotions (expected ~{len(VIEWPORT_CONFIGS)-1})")
+
+        # Should have created some browsers for different configs
+        if pool_stats['new'] == 0:
+            print(f"⚠️  NOTE: No new browsers created (all used default?)")
+
+        if pool_stats['permanent'] == len(all_results):
+            print(f"⚠️  NOTE: All requests used permanent browser (configs not varying enough?)")
+
+        if final_mem - baseline_mem > 500:
+            print(f"⚠️  WARNING: Memory grew {final_mem - baseline_mem:.1f} MB")
+
+        if passed:
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            print(f"🛑 Stopping container...")
+            container.stop()
+            container.remove()
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_6_multi_endpoint.py

@@ -0,0 +1,234 @@
+#!/usr/bin/env python3
+"""
+Test 6: Multi-Endpoint Testing
+- Tests multiple endpoints together: /html, /screenshot, /pdf, /crawl
+- Validates each endpoint works correctly
+- Monitors success rates per endpoint
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+REQUESTS_PER_ENDPOINT = 10
+
+# Stats
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background stats collector."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+        try:
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
+            stats_history.append({'timestamp': time.time(), 'memory_mb': mem_usage})
+        except:
+            pass
+        time.sleep(0.5)
+
+async def test_html(client, base_url, count):
+    """Test /html endpoint."""
+    url = f"{base_url}/html"
+    results = []
+    for _ in range(count):
+        start = time.time()
+        try:
+            resp = await client.post(url, json={"url": "https://httpbin.org/html"}, timeout=30.0)
+            elapsed = (time.time() - start) * 1000
+            results.append({"success": resp.status_code == 200, "latency_ms": elapsed})
+        except Exception as e:
+            results.append({"success": False, "error": str(e)})
+    return results
+
+async def test_screenshot(client, base_url, count):
+    """Test /screenshot endpoint."""
+    url = f"{base_url}/screenshot"
+    results = []
+    for _ in range(count):
+        start = time.time()
+        try:
+            resp = await client.post(url, json={"url": "https://httpbin.org/html"}, timeout=30.0)
+            elapsed = (time.time() - start) * 1000
+            results.append({"success": resp.status_code == 200, "latency_ms": elapsed})
+        except Exception as e:
+            results.append({"success": False, "error": str(e)})
+    return results
+
+async def test_pdf(client, base_url, count):
+    """Test /pdf endpoint."""
+    url = f"{base_url}/pdf"
+    results = []
+    for _ in range(count):
+        start = time.time()
+        try:
+            resp = await client.post(url, json={"url": "https://httpbin.org/html"}, timeout=30.0)
+            elapsed = (time.time() - start) * 1000
+            results.append({"success": resp.status_code == 200, "latency_ms": elapsed})
+        except Exception as e:
+            results.append({"success": False, "error": str(e)})
+    return results
+
+async def test_crawl(client, base_url, count):
+    """Test /crawl endpoint."""
+    url = f"{base_url}/crawl"
+    results = []
+    payload = {
+        "urls": ["https://httpbin.org/html"],
+        "browser_config": {},
+        "crawler_config": {}
+    }
+    for _ in range(count):
+        start = time.time()
+        try:
+            resp = await client.post(url, json=payload, timeout=30.0)
+            elapsed = (time.time() - start) * 1000
+            results.append({"success": resp.status_code == 200, "latency_ms": elapsed})
+        except Exception as e:
+            results.append({"success": False, "error": str(e)})
+    return results
+
+def start_container(client, image, name, port):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container...")
+    container = client.containers.run(
+        image, name=name, ports={f"{port}/tcp": port},
+        detach=True, shm_size="1g", mem_limit="4g",
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                if requests.get(f"http://localhost:{port}/health", timeout=2).status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+async def main():
+    print("="*60)
+    print("TEST 6: Multi-Endpoint Testing")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        print(f"\n⏳ Waiting for permanent browser init (3s)...")
+        await asyncio.sleep(3)
+
+        # Start monitoring
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        await asyncio.sleep(1)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline: {baseline_mem:.1f} MB\n")
+
+        base_url = f"http://localhost:{PORT}"
+
+        # Test each endpoint
+        endpoints = {
+            "/html": test_html,
+            "/screenshot": test_screenshot,
+            "/pdf": test_pdf,
+            "/crawl": test_crawl,
+        }
+
+        all_endpoint_stats = {}
+
+        async with httpx.AsyncClient() as http_client:
+            for endpoint_name, test_func in endpoints.items():
+                print(f"🔄 Testing {endpoint_name} ({REQUESTS_PER_ENDPOINT} requests)...")
+                results = await test_func(http_client, base_url, REQUESTS_PER_ENDPOINT)
+
+                successes = sum(1 for r in results if r.get("success"))
+                success_rate = (successes / len(results)) * 100
+                latencies = [r["latency_ms"] for r in results if "latency_ms" in r]
+                avg_lat = sum(latencies) / len(latencies) if latencies else 0
+
+                all_endpoint_stats[endpoint_name] = {
+                    'success_rate': success_rate,
+                    'avg_latency': avg_lat,
+                    'total': len(results),
+                    'successes': successes
+                }
+
+                print(f"  ✓ Success: {success_rate:.1f}% ({successes}/{len(results)}), Avg: {avg_lat:.0f}ms")
+
+        # Stop monitoring
+        await asyncio.sleep(1)
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Final stats
+        memory_samples = [s['memory_mb'] for s in stats_history]
+        peak_mem = max(memory_samples) if memory_samples else 0
+        final_mem = memory_samples[-1] if memory_samples else 0
+
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"{'='*60}")
+        for endpoint, stats in all_endpoint_stats.items():
+            print(f"  {endpoint:12} Success: {stats['success_rate']:5.1f}%  Avg: {stats['avg_latency']:6.0f}ms")
+
+        print(f"\n  Memory:")
+        print(f"    Baseline: {baseline_mem:.1f} MB")
+        print(f"    Peak:     {peak_mem:.1f} MB")
+        print(f"    Final:    {final_mem:.1f} MB")
+        print(f"    Delta:    {final_mem - baseline_mem:+.1f} MB")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        passed = True
+        for endpoint, stats in all_endpoint_stats.items():
+            if stats['success_rate'] < 100:
+                print(f"❌ FAIL: {endpoint} success rate {stats['success_rate']:.1f}% < 100%")
+                passed = False
+
+        if passed:
+            print(f"✅ TEST PASSED")
+            return 0
+        else:
+            return 1
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            print(f"🛑 Stopping container...")
+            container.stop()
+            container.remove()
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_7_cleanup.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python3
+"""
+Test 7: Cleanup Verification (Janitor)
+- Creates load spike then goes idle
+- Verifies memory returns to near baseline
+- Tests janitor cleanup of idle browsers
+- Monitors memory recovery time
+"""
+import asyncio
+import time
+import docker
+import httpx
+from threading import Thread, Event
+
+# Config
+IMAGE = "crawl4ai-local:latest"
+CONTAINER_NAME = "crawl4ai-test"
+PORT = 11235
+SPIKE_REQUESTS = 20  # Create some browsers
+IDLE_TIME = 90  # Wait 90s for janitor (runs every 60s)
+
+# Stats
+stats_history = []
+stop_monitoring = Event()
+
+def monitor_stats(container):
+    """Background stats collector."""
+    for stat in container.stats(decode=True, stream=True):
+        if stop_monitoring.is_set():
+            break
+        try:
+            mem_usage = stat['memory_stats'].get('usage', 0) / (1024 * 1024)
+            stats_history.append({'timestamp': time.time(), 'memory_mb': mem_usage})
+        except:
+            pass
+        time.sleep(1)  # Sample every 1s for this test
+
+def start_container(client, image, name, port):
+    """Start container."""
+    try:
+        old = client.containers.get(name)
+        print(f"🧹 Stopping existing container...")
+        old.stop()
+        old.remove()
+    except docker.errors.NotFound:
+        pass
+
+    print(f"🚀 Starting container...")
+    container = client.containers.run(
+        image, name=name, ports={f"{port}/tcp": port},
+        detach=True, shm_size="1g", mem_limit="4g",
+    )
+
+    print(f"⏳ Waiting for health...")
+    for _ in range(30):
+        time.sleep(1)
+        container.reload()
+        if container.status == "running":
+            try:
+                import requests
+                if requests.get(f"http://localhost:{port}/health", timeout=2).status_code == 200:
+                    print(f"✅ Container healthy!")
+                    return container
+            except:
+                pass
+    raise TimeoutError("Container failed to start")
+
+async def main():
+    print("="*60)
+    print("TEST 7: Cleanup Verification (Janitor)")
+    print("="*60)
+
+    client = docker.from_env()
+    container = None
+    monitor_thread = None
+
+    try:
+        container = start_container(client, IMAGE, CONTAINER_NAME, PORT)
+
+        print(f"\n⏳ Waiting for permanent browser init (3s)...")
+        await asyncio.sleep(3)
+
+        # Start monitoring
+        stop_monitoring.clear()
+        stats_history.clear()
+        monitor_thread = Thread(target=monitor_stats, args=(container,), daemon=True)
+        monitor_thread.start()
+
+        await asyncio.sleep(2)
+        baseline_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        print(f"📏 Baseline: {baseline_mem:.1f} MB\n")
+
+        # Create load spike with different configs to populate pool
+        print(f"🔥 Creating load spike ({SPIKE_REQUESTS} requests with varied configs)...")
+        url = f"http://localhost:{PORT}/crawl"
+
+        viewports = [
+            {"width": 1920, "height": 1080},
+            {"width": 1024, "height": 768},
+            {"width": 375, "height": 667},
+        ]
+
+        async with httpx.AsyncClient(timeout=60.0) as http_client:
+            tasks = []
+            for i in range(SPIKE_REQUESTS):
+                vp = viewports[i % len(viewports)]
+                payload = {
+                    "urls": ["https://httpbin.org/html"],
+                    "browser_config": {
+                        "type": "BrowserConfig",
+                        "params": {
+                            "viewport": {"type": "dict", "value": vp},
+                            "headless": True,
+                            "text_mode": True,
+                            "extra_args": [
+                                "--no-sandbox", "--disable-dev-shm-usage",
+                                "--disable-gpu", "--disable-software-rasterizer",
+                                "--disable-web-security", "--allow-insecure-localhost",
+                                "--ignore-certificate-errors"
+                            ]
+                        }
+                    },
+                    "crawler_config": {}
+                }
+                tasks.append(http_client.post(url, json=payload))
+
+            results = await asyncio.gather(*tasks, return_exceptions=True)
+            successes = sum(1 for r in results if hasattr(r, 'status_code') and r.status_code == 200)
+            print(f"  ✓ Spike completed: {successes}/{len(results)} successful")
+
+        # Measure peak
+        await asyncio.sleep(2)
+        peak_mem = max([s['memory_mb'] for s in stats_history]) if stats_history else baseline_mem
+        print(f"  📊 Peak memory: {peak_mem:.1f} MB (+{peak_mem - baseline_mem:.1f} MB)")
+
+        # Now go idle and wait for janitor
+        print(f"\n⏸️  Going idle for {IDLE_TIME}s (janitor cleanup)...")
+        print(f"  (Janitor runs every 60s, checking for idle browsers)")
+
+        for elapsed in range(0, IDLE_TIME, 10):
+            await asyncio.sleep(10)
+            current_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+            print(f"  [{elapsed+10:3d}s] Memory: {current_mem:.1f} MB")
+
+        # Stop monitoring
+        stop_monitoring.set()
+        if monitor_thread:
+            monitor_thread.join(timeout=2)
+
+        # Analyze memory recovery
+        final_mem = stats_history[-1]['memory_mb'] if stats_history else 0
+        recovery_mb = peak_mem - final_mem
+        recovery_pct = (recovery_mb / (peak_mem - baseline_mem) * 100) if (peak_mem - baseline_mem) > 0 else 0
+
+        print(f"\n{'='*60}")
+        print(f"RESULTS:")
+        print(f"{'='*60}")
+        print(f"  Memory Journey:")
+        print(f"    Baseline:  {baseline_mem:.1f} MB")
+        print(f"    Peak:      {peak_mem:.1f} MB  (+{peak_mem - baseline_mem:.1f} MB)")
+        print(f"    Final:     {final_mem:.1f} MB  (+{final_mem - baseline_mem:.1f} MB)")
+        print(f"    Recovered: {recovery_mb:.1f} MB  ({recovery_pct:.1f}%)")
+        print(f"{'='*60}")
+
+        # Pass/Fail
+        passed = True
+
+        # Should have created some memory pressure
+        if peak_mem - baseline_mem < 100:
+            print(f"⚠️  WARNING: Peak increase only {peak_mem - baseline_mem:.1f} MB (expected more browsers)")
+
+        # Should recover most memory (within 100MB of baseline)
+        if final_mem - baseline_mem > 100:
+            print(f"⚠️  WARNING: Memory didn't recover well (still +{final_mem - baseline_mem:.1f} MB above baseline)")
+        else:
+            print(f"✅ Good memory recovery!")
+
+        # Baseline + 50MB tolerance
+        if final_mem - baseline_mem < 50:
+            print(f"✅ Excellent cleanup (within 50MB of baseline)")
+
+        print(f"✅ TEST PASSED")
+        return 0
+
+    except Exception as e:
+        print(f"\n❌ TEST ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return 1
+    finally:
+        stop_monitoring.set()
+        if container:
+            print(f"🛑 Stopping container...")
+            container.stop()
+            container.remove()
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    exit(exit_code)

deploy/docker/tests/test_monitor_demo.py

@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+"""Quick test to generate monitor dashboard activity"""
+import httpx
+import asyncio
+
+async def test_dashboard():
+    async with httpx.AsyncClient(timeout=30.0) as client:
+        print("📊 Generating dashboard activity...")
+
+        # Test 1: Simple crawl
+        print("\n1️⃣ Running simple crawl...")
+        r1 = await client.post(
+            "http://localhost:11235/crawl",
+            json={"urls": ["https://httpbin.org/html"], "crawler_config": {}}
+        )
+        print(f"   Status: {r1.status_code}")
+
+        # Test 2: Multiple URLs
+        print("\n2️⃣ Running multi-URL crawl...")
+        r2 = await client.post(
+            "http://localhost:11235/crawl",
+            json={
+                "urls": [
+                    "https://httpbin.org/html",
+                    "https://httpbin.org/json"
+                ],
+                "crawler_config": {}
+            }
+        )
+        print(f"   Status: {r2.status_code}")
+
+        # Test 3: Check monitor health
+        print("\n3️⃣ Checking monitor health...")
+        r3 = await client.get("http://localhost:11235/monitor/health")
+        health = r3.json()
+        print(f"   Memory: {health['container']['memory_percent']}%")
+        print(f"   Browsers: {health['pool']['permanent']['active']}")
+
+        # Test 4: Check requests
+        print("\n4️⃣ Checking request log...")
+        r4 = await client.get("http://localhost:11235/monitor/requests")
+        reqs = r4.json()
+        print(f"   Active: {len(reqs['active'])}")
+        print(f"   Completed: {len(reqs['completed'])}")
+
+        # Test 5: Check endpoint stats
+        print("\n5️⃣ Checking endpoint stats...")
+        r5 = await client.get("http://localhost:11235/monitor/endpoints/stats")
+        stats = r5.json()
+        for endpoint, data in stats.items():
+            print(f"   {endpoint}: {data['count']} requests, {data['avg_latency_ms']}ms avg")
+
+        print("\n✅ Dashboard should now show activity!")
+        print(f"\n🌐 Open: http://localhost:11235/dashboard")
+
+if __name__ == "__main__":
+    asyncio.run(test_dashboard())

deploy/docker/utils.py

@@ -179,3 +179,28 @@ def verify_email_domain(email: str) -> bool:
         return True if records else False
     except Exception as e:
         return False
+
+def get_container_memory_percent() -> float:
+    """Get actual container memory usage vs limit (cgroup v1/v2 aware)."""
+    try:
+        # Try cgroup v2 first
+        usage_path = Path("/sys/fs/cgroup/memory.current")
+        limit_path = Path("/sys/fs/cgroup/memory.max")
+        if not usage_path.exists():
+            # Fall back to cgroup v1
+            usage_path = Path("/sys/fs/cgroup/memory/memory.usage_in_bytes")
+            limit_path = Path("/sys/fs/cgroup/memory/memory.limit_in_bytes")
+
+        usage = int(usage_path.read_text())
+        limit = int(limit_path.read_text())
+
+        # Handle unlimited (v2: "max", v1: > 1e18)
+        if limit > 1e18:
+            import psutil
+            limit = psutil.virtual_memory().total
+
+        return (usage / limit) * 100
+    except:
+        # Non-container or unsupported: fallback to host
+        import psutil
+        return psutil.virtual_memory().percent

docs/md_v2/core/self-hosting.md

@@ -1,4 +1,20 @@
-# Crawl4AI Docker Guide 🐳
+# Self-Hosting Crawl4AI 🚀
+
+**Take Control of Your Web Crawling Infrastructure**
+
+Self-hosting Crawl4AI gives you complete control over your web crawling and data extraction pipeline. Unlike cloud-based solutions, you own your data, infrastructure, and destiny.
+
+## Why Self-Host?
+
+- **🔒 Data Privacy**: Your crawled data never leaves your infrastructure
+- **💰 Cost Control**: No per-request pricing - scale within your own resources
+- **🎯 Customization**: Full control over browser configurations, extraction strategies, and performance tuning
+- **📊 Transparency**: Real-time monitoring dashboard shows exactly what's happening
+- **⚡ Performance**: Direct access without API rate limits or geographic restrictions
+- **🛡️ Security**: Keep sensitive data extraction workflows behind your firewall
+- **🔧 Flexibility**: Customize, extend, and integrate with your existing infrastructure
+
+When you self-host, you can scale from a single container to a full browser infrastructure, all while maintaining complete control and visibility.
 
 ## Table of Contents
 - [Prerequisites](#prerequisites)
@@ -13,36 +29,14 @@
   - [Available MCP Tools](#available-mcp-tools)
   - [Testing MCP Connections](#testing-mcp-connections)
   - [MCP Schemas](#mcp-schemas)
-- [Additional API Endpoints](#additional-api-endpoints)
-  - [HTML Extraction Endpoint](#html-extraction-endpoint)
-  - [Screenshot Endpoint](#screenshot-endpoint)
-  - [PDF Export Endpoint](#pdf-export-endpoint)
-  - [JavaScript Execution Endpoint](#javascript-execution-endpoint)
-- [User-Provided Hooks API](#user-provided-hooks-api)
-  - [Hook Information Endpoint](#hook-information-endpoint)
-  - [Available Hook Points](#available-hook-points)
-  - [Using Hooks in Requests](#using-hooks-in-requests)
-  - [Hook Examples with Real URLs](#hook-examples-with-real-urls)
-  - [Security Best Practices](#security-best-practices)
-  - [Hook Response Information](#hook-response-information)
-  - [Error Handling](#error-handling)
-  - [Hooks Utility: Function-Based Approach (Python)](#hooks-utility-function-based-approach-python)
-- [Job Queue & Webhook API](#job-queue-webhook-api)
-  - [Why Use the Job Queue API?](#why-use-the-job-queue-api)
-  - [Available Endpoints](#available-endpoints)
-  - [Webhook Configuration](#webhook-configuration)
-  - [Usage Examples](#usage-examples)
-  - [Webhook Best Practices](#webhook-best-practices)
-  - [Use Cases](#use-cases)
-  - [Troubleshooting](#troubleshooting)
-- [Dockerfile Parameters](#dockerfile-parameters)
-- [Using the API](#using-the-api)
-  - [Playground Interface](#playground-interface)
-  - [Python SDK](#python-sdk)
-  - [Understanding Request Schema](#understanding-request-schema)
-  - [REST API Examples](#rest-api-examples)
-  - [LLM Configuration Examples](#llm-configuration-examples)
-- [Metrics & Monitoring](#metrics--monitoring)
+- [Real-time Monitoring & Operations](#real-time-monitoring--operations)
+  - [Monitoring Dashboard](#monitoring-dashboard)
+  - [Monitor API Endpoints](#monitor-api-endpoints)
+  - [WebSocket Streaming](#websocket-streaming)
+  - [Control Actions](#control-actions)
+  - [Production Integration](#production-integration)
+- [Deployment Scenarios](#deployment-scenarios)
+- [Complete Examples](#complete-examples)
 - [Server Configuration](#server-configuration)
   - [Understanding config.yml](#understanding-configyml)
   - [JWT Authentication](#jwt-authentication)
@@ -1957,22 +1951,469 @@ async def test_stream_crawl(token: str = None): # Made token optional
 
 ---
 
-## Metrics & Monitoring
+## Real-time Monitoring & Operations
 
-Keep an eye on your crawler with these endpoints:
+One of the key advantages of self-hosting is complete visibility into your infrastructure. Crawl4AI includes a comprehensive real-time monitoring system that gives you full transparency and control.
 
-- `/health` - Quick health check
-- `/metrics` - Detailed Prometheus metrics
-- `/schema` - Full API schema
+### Monitoring Dashboard
 
-Example health check:
+Access the **built-in real-time monitoring dashboard** for complete operational visibility:
+
+```
+http://localhost:11235/monitor
+```
+
+![Monitoring Dashboard](https://via.placeholder.com/800x400?text=Crawl4AI+Monitoring+Dashboard)
+
+**Dashboard Features:**
+
+#### 1. System Health Overview
+- **CPU & Memory**: Live usage with progress bars and percentage indicators
+- **Network I/O**: Total bytes sent/received since startup
+- **Server Uptime**: How long your server has been running
+- **Browser Pool Status**:
+  - 🔥 Permanent browser (always-on default config, ~270MB)
+  - ♨️ Hot pool (frequently used configs, ~180MB each)
+  - ❄️ Cold pool (idle browsers awaiting cleanup, ~180MB each)
+- **Memory Pressure**: LOW/MEDIUM/HIGH indicator for janitor behavior
+
+#### 2. Live Request Tracking
+- **Active Requests**: Currently running crawls with:
+  - Request ID for tracking
+  - Target URL (truncated for display)
+  - Endpoint being used
+  - Elapsed time (updates in real-time)
+  - Memory usage from start
+- **Completed Requests**: Last 10 finished requests showing:
+  - Success/failure status (color-coded)
+  - Total execution time
+  - Memory delta (how much memory changed)
+  - Pool hit (was browser reused?)
+  - HTTP status code
+- **Filtering**: View all, success only, or errors only
+
+#### 3. Browser Pool Management
+Interactive table showing all active browsers:
+
+| Type | Signature | Age | Last Used | Hits | Actions |
+|------|-----------|-----|-----------|------|---------|
+| permanent | abc12345 | 2h | 5s ago | 1,247 | Restart |
+| hot | def67890 | 45m | 2m ago | 89 | Kill / Restart |
+| cold | ghi11213 | 30m | 15m ago | 3 | Kill / Restart |
+
+- **Reuse Rate**: Percentage of requests that reused existing browsers
+- **Memory Estimates**: Total memory used by browser pool
+- **Manual Control**: Kill or restart individual browsers
+
+#### 4. Janitor Events Log
+Real-time log of browser pool cleanup events:
+- When cold browsers are closed due to memory pressure
+- When browsers are promoted from cold to hot pool
+- Forced cleanups triggered manually
+- Detailed cleanup reasons and browser signatures
+
+#### 5. Error Monitoring
+Recent errors with full context:
+- Timestamp
+- Endpoint where error occurred
+- Target URL
+- Error message
+- Request ID for correlation
+
+**Live Updates:**
+The dashboard connects via WebSocket and refreshes every **2 seconds** with the latest data. Connection status indicator shows when you're connected/disconnected.
+
+---
+
+### Monitor API Endpoints
+
+For programmatic monitoring, automation, and integration with your existing infrastructure:
+
+#### Health & Statistics
+
+**Get System Health**
 ```bash
-curl http://localhost:11235/health
+GET /monitor/health
+```
+
+Returns current system snapshot:
+```json
+{
+  "container": {
+    "memory_percent": 45.2,
+    "cpu_percent": 23.1,
+    "network_sent_mb": 1250.45,
+    "network_recv_mb": 3421.12,
+    "uptime_seconds": 7234
+  },
+  "pool": {
+    "permanent": {"active": true, "memory_mb": 270},
+    "hot": {"count": 3, "memory_mb": 540},
+    "cold": {"count": 1, "memory_mb": 180},
+    "total_memory_mb": 990
+  },
+  "janitor": {
+    "next_cleanup_estimate": "adaptive",
+    "memory_pressure": "MEDIUM"
+  }
+}
+```
+
+**Get Request Statistics**
+```bash
+GET /monitor/requests?status=all&limit=50
+```
+
+Query parameters:
+- `status`: Filter by `all`, `active`, `completed`, `success`, or `error`
+- `limit`: Number of completed requests to return (1-1000)
+
+**Get Browser Pool Details**
+```bash
+GET /monitor/browsers
+```
+
+Returns detailed information about all active browsers:
+```json
+{
+  "browsers": [
+    {
+      "type": "permanent",
+      "sig": "abc12345",
+      "age_seconds": 7234,
+      "last_used_seconds": 5,
+      "memory_mb": 270,
+      "hits": 1247,
+      "killable": false
+    },
+    {
+      "type": "hot",
+      "sig": "def67890",
+      "age_seconds": 2701,
+      "last_used_seconds": 120,
+      "memory_mb": 180,
+      "hits": 89,
+      "killable": true
+    }
+  ],
+  "summary": {
+    "total_count": 5,
+    "total_memory_mb": 990,
+    "reuse_rate_percent": 87.3
+  }
+}
+```
+
+**Get Endpoint Performance Statistics**
+```bash
+GET /monitor/endpoints/stats
+```
+
+Returns aggregated metrics per endpoint:
+```json
+{
+  "/crawl": {
+    "count": 1523,
+    "avg_latency_ms": 2341.5,
+    "success_rate_percent": 98.2,
+    "pool_hit_rate_percent": 89.1,
+    "errors": 27
+  },
+  "/md": {
+    "count": 891,
+    "avg_latency_ms": 1823.7,
+    "success_rate_percent": 99.4,
+    "pool_hit_rate_percent": 92.3,
+    "errors": 5
+  }
+}
+```
+
+**Get Timeline Data**
+```bash
+GET /monitor/timeline?metric=memory&window=5m
+```
+
+Parameters:
+- `metric`: `memory`, `requests`, or `browsers`
+- `window`: Currently only `5m` (5-minute window, 5-second resolution)
+
+Returns time-series data for charts:
+```json
+{
+  "timestamps": [1699564800, 1699564805, 1699564810, ...],
+  "values": [42.1, 43.5, 41.8, ...]
+}
+```
+
+#### Logs
+
+**Get Janitor Events**
+```bash
+GET /monitor/logs/janitor?limit=100
+```
+
+**Get Error Log**
+```bash
+GET /monitor/logs/errors?limit=100
 ```
 
 ---
 
-*(Deployment Scenarios and Complete Examples sections remain the same, maybe update links if examples moved)*
+### WebSocket Streaming
+
+For real-time monitoring in your own dashboards or applications:
+
+```bash
+WS /monitor/ws
+```
+
+**Connection Example (Python):**
+```python
+import asyncio
+import websockets
+import json
+
+async def monitor_server():
+    uri = "ws://localhost:11235/monitor/ws"
+
+    async with websockets.connect(uri) as websocket:
+        print("Connected to Crawl4AI monitor")
+
+        while True:
+            # Receive update every 2 seconds
+            data = await websocket.recv()
+            update = json.loads(data)
+
+            # Extract key metrics
+            health = update['health']
+            active_requests = len(update['requests']['active'])
+            browsers = len(update['browsers'])
+
+            print(f"Memory: {health['container']['memory_percent']:.1f}% | "
+                  f"Active: {active_requests} | "
+                  f"Browsers: {browsers}")
+
+            # Check for high memory pressure
+            if health['janitor']['memory_pressure'] == 'HIGH':
+                print("⚠️  HIGH MEMORY PRESSURE - Consider cleanup")
+
+asyncio.run(monitor_server())
+```
+
+**Update Payload Structure:**
+```json
+{
+  "timestamp": 1699564823.456,
+  "health": { /* System health snapshot */ },
+  "requests": {
+    "active": [ /* Currently running */ ],
+    "completed": [ /* Last 10 completed */ ]
+  },
+  "browsers": [ /* All active browsers */ ],
+  "timeline": {
+    "memory": { /* Last 5 minutes */ },
+    "requests": { /* Request rate */ },
+    "browsers": { /* Pool composition */ }
+  },
+  "janitor": [ /* Last 10 cleanup events */ ],
+  "errors": [ /* Last 10 errors */ ]
+}
+```
+
+---
+
+### Control Actions
+
+Take manual control when needed:
+
+**Force Immediate Cleanup**
+```bash
+POST /monitor/actions/cleanup
+```
+
+Kills all cold pool browsers immediately (useful when memory is tight):
+```json
+{
+  "success": true,
+  "killed_browsers": 3
+}
+```
+
+**Kill Specific Browser**
+```bash
+POST /monitor/actions/kill_browser
+Content-Type: application/json
+
+{
+  "sig": "abc12345"  // First 8 chars of browser signature
+}
+```
+
+Response:
+```json
+{
+  "success": true,
+  "killed_sig": "abc12345",
+  "pool_type": "hot"
+}
+```
+
+**Restart Browser**
+```bash
+POST /monitor/actions/restart_browser
+Content-Type: application/json
+
+{
+  "sig": "permanent"  // Or first 8 chars of signature
+}
+```
+
+For permanent browser, this will close and reinitialize it. For hot/cold browsers, it kills them and lets new requests create fresh ones.
+
+**Reset Statistics**
+```bash
+POST /monitor/stats/reset
+```
+
+Clears endpoint counters (useful for starting fresh after testing).
+
+---
+
+### Production Integration
+
+#### Integration with Existing Monitoring Systems
+
+**Prometheus Integration:**
+```bash
+# Scrape metrics endpoint
+curl http://localhost:11235/metrics
+```
+
+**Custom Dashboard Integration:**
+```python
+# Example: Push metrics to your monitoring system
+import asyncio
+import websockets
+import json
+from your_monitoring import push_metric
+
+async def integrate_monitoring():
+    async with websockets.connect("ws://localhost:11235/monitor/ws") as ws:
+        while True:
+            data = json.loads(await ws.recv())
+
+            # Push to your monitoring system
+            push_metric("crawl4ai.memory.percent",
+                       data['health']['container']['memory_percent'])
+            push_metric("crawl4ai.active_requests",
+                       len(data['requests']['active']))
+            push_metric("crawl4ai.browser_count",
+                       len(data['browsers']))
+```
+
+**Alerting Example:**
+```python
+import requests
+import time
+
+def check_health():
+    """Poll health endpoint and alert on issues"""
+    response = requests.get("http://localhost:11235/monitor/health")
+    health = response.json()
+
+    # Alert on high memory
+    if health['container']['memory_percent'] > 85:
+        send_alert(f"High memory: {health['container']['memory_percent']}%")
+
+    # Alert on high error rate
+    stats = requests.get("http://localhost:11235/monitor/endpoints/stats").json()
+    for endpoint, metrics in stats.items():
+        if metrics['success_rate_percent'] < 95:
+            send_alert(f"{endpoint} success rate: {metrics['success_rate_percent']}%")
+
+# Run every minute
+while True:
+    check_health()
+    time.sleep(60)
+```
+
+**Log Aggregation:**
+```python
+import requests
+from datetime import datetime
+
+def aggregate_errors():
+    """Fetch and aggregate errors for logging system"""
+    response = requests.get("http://localhost:11235/monitor/logs/errors?limit=100")
+    errors = response.json()['errors']
+
+    for error in errors:
+        log_to_system({
+            'timestamp': datetime.fromtimestamp(error['timestamp']),
+            'service': 'crawl4ai',
+            'endpoint': error['endpoint'],
+            'url': error['url'],
+            'message': error['error'],
+            'request_id': error['request_id']
+        })
+```
+
+#### Key Metrics to Track
+
+For production self-hosted deployments, monitor these metrics:
+
+1. **Memory Usage Trends**
+   - Track `container.memory_percent` over time
+   - Alert when consistently above 80%
+   - Prevents OOM kills
+
+2. **Request Success Rates**
+   - Monitor per-endpoint success rates
+   - Alert when below 95%
+   - Indicates crawling issues
+
+3. **Average Latency**
+   - Track `avg_latency_ms` per endpoint
+   - Detect performance degradation
+   - Optimize slow endpoints
+
+4. **Browser Pool Efficiency**
+   - Monitor `reuse_rate_percent`
+   - Should be >80% for good efficiency
+   - Low rates indicate pool churn
+
+5. **Error Frequency**
+   - Count errors per time window
+   - Alert on sudden spikes
+   - Track error patterns
+
+6. **Janitor Activity**
+   - Monitor cleanup frequency
+   - Excessive cleanup indicates memory pressure
+   - Adjust pool settings if needed
+
+---
+
+### Quick Health Check
+
+For simple uptime monitoring:
+
+```bash
+curl http://localhost:11235/health
+```
+
+Returns:
+```json
+{
+  "status": "healthy",
+  "version": "0.7.4"
+}
+```
+
+Other useful endpoints:
+- `/metrics` - Prometheus metrics
+- `/schema` - Full API schema
 
 ---
 
@@ -2132,43 +2573,46 @@ We're here to help you succeed with Crawl4AI! Here's how to get support:
 
 ## Summary
 
-In this guide, we've covered everything you need to get started with Crawl4AI's Docker deployment:
-- Building and running the Docker container
-- Configuring the environment
-- Using the interactive playground for testing
-- Making API requests with proper typing
-- Using the Python SDK with **automatic hook conversion**
-- **Working with hooks** - both string-based (REST API) and function-based (Python SDK)
-- Leveraging specialized endpoints for screenshots, PDFs, and JavaScript execution
-- Connecting via the Model Context Protocol (MCP)
-- Monitoring your deployment
+Congratulations! You now have everything you need to self-host your own Crawl4AI infrastructure with complete control and visibility.
 
-### Key Features
+**What You've Learned:**
+- ✅ Multiple deployment options (Docker Hub, Docker Compose, manual builds)
+- ✅ Environment configuration and LLM integration
+- ✅ Using the interactive playground for testing
+- ✅ Making API requests with proper typing (SDK and REST)
+- ✅ Specialized endpoints (screenshots, PDFs, JavaScript execution)
+- ✅ MCP integration for AI-assisted development
+- ✅ **Real-time monitoring dashboard** for operational transparency
+- ✅ **Monitor API** for programmatic control and integration
+- ✅ Production deployment best practices
 
-**Hooks Support**: Crawl4AI offers two approaches for working with hooks:
-- **String-based** (REST API): Works with any language, requires manual string formatting
-- **Function-based** (Python SDK): Write hooks as regular Python functions with full IDE support and automatic conversion
+**Why This Matters:**
 
-**Playground Interface**: The built-in playground at `http://localhost:11235/playground` makes it easy to test configurations and generate corresponding JSON for API requests.
+By self-hosting Crawl4AI, you:
+- 🔒 **Own Your Data**: Everything stays in your infrastructure
+- 📊 **See Everything**: Real-time dashboard shows exactly what's happening
+- 💰 **Control Costs**: Scale within your resources, no per-request fees
+- ⚡ **Maximize Performance**: Direct access with smart browser pooling (10x memory efficiency)
+- 🛡️ **Stay Secure**: Keep sensitive workflows behind your firewall
+- 🔧 **Customize Freely**: Full control over configs, strategies, and optimizations
 
-**MCP Integration**: For AI application developers, the MCP integration allows tools like Claude Code to directly access Crawl4AI's capabilities without complex API handling.
+**Next Steps:**
 
-### Next Steps
+1. **Start Simple**: Deploy with Docker Hub image and test with the playground
+2. **Monitor Everything**: Open `http://localhost:11235/monitor` to watch your server
+3. **Integrate**: Connect your applications using the Python SDK or REST API
+4. **Scale Smart**: Use the monitoring data to optimize your deployment
+5. **Go Production**: Set up alerting, log aggregation, and automated cleanup
 
-1. **Explore Examples**: Check out the comprehensive examples in:
-   - `/docs/examples/hooks_docker_client_example.py` - Python function-based hooks
-   - `/docs/examples/hooks_rest_api_example.py` - REST API string-based hooks
-   - `/docs/examples/README_HOOKS.md` - Comparison and guide
+**Key Resources:**
+- 🎮 **Playground**: `http://localhost:11235/playground` - Interactive testing
+- 📊 **Monitor Dashboard**: `http://localhost:11235/monitor` - Real-time visibility
+- 📖 **Architecture Docs**: `deploy/docker/ARCHITECTURE.md` - Deep technical dive
+- 💬 **Discord Community**: Get help and share experiences
+- ⭐ **GitHub**: Report issues, contribute, show support
 
-2. **Read Documentation**:
-   - `/docs/hooks-utility-guide.md` - Complete hooks utility guide
-   - API documentation for detailed configuration options
+Remember: The monitoring dashboard is your window into your infrastructure. Use it to understand performance, troubleshoot issues, and optimize your deployment. The examples in the `examples` folder show real-world usage patterns you can adapt.
 
-3. **Join the Community**:
-   - GitHub: Report issues and contribute
-   - Discord: Get help and share your experiences
-   - Documentation: Comprehensive guides and tutorials
-
-Keep exploring, and don't hesitate to reach out if you need help! We're building something amazing together. 🚀
+**You're now in control of your web crawling destiny!** 🚀
 
 Happy crawling! 🕷️

mkdocs.yml

@@ -19,7 +19,7 @@ nav:
     - "Marketplace Admin": "marketplace/admin/index.html"
   - Setup & Installation:
     - "Installation": "core/installation.md"
-    - "Docker Deployment": "core/docker-deployment.md"
+    - "Self-Hosting Guide": "core/self-hosting.md"
   - "Blog & Changelog":
     - "Blog Home": "blog/index.md"
     - "Changelog": "https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md"