diff --git a/.gitignore b/.gitignore index 829a555..0a807f9 100644 --- a/.gitignore +++ b/.gitignore @@ -1,9 +1,12 @@ __pycache__/ +.DS_Store *.pyc *.pyo +*.png *.pyd .Python env/ build/ dist/ infra/.deploy-state +loadtest/results/ diff --git a/loadtest/README.md b/loadtest/README.md new file mode 100644 index 0000000..9e0bf64 --- /dev/null +++ b/loadtest/README.md @@ -0,0 +1,77 @@ +# Load Testing + +Ramps concurrent Nightshift VMs in waves to find the concurrency ceiling of a node. Collects per-run timing metrics, host resource samples, and produces a scaling report with zone classifications. + +## Quick start + +```bash +# Run load test (deploys agent, launches waves, writes results) +uv run python loadtest/run.py --waves 5,10,20,30,50,50,50 --duration 180 + +# Visualize the most recent result +uv run --with matplotlib --with numpy python loadtest/run.py --vis + +# Visualize a specific result +uv run --with matplotlib --with numpy python loadtest/run.py --vis loadtest/results/loadtest-20260226-114607.json +``` + +## How it works + +1. **Deploy** — `run.py` packages `agent.py` into a tarball and deploys it via `POST /api/agents` +2. **Wave launch** — Waves fire concurrently (e.g. 5, then 10, then 20 VMs). Each wave runs in parallel with previous waves still executing, so VMs accumulate +3. **SSE streaming** — Each run connects to the event stream and tracks cold start, heartbeats, and completion +4. **Monitor** (optional) — If `--host` and `--key` are provided, `monitor.py` SSH-es into the host every 5 seconds and samples CPU, memory, disk, Firecracker VM count, TAP devices, file descriptors, and iptables rules +5. **Report** — Results are saved to JSON and a scaling report is printed with GREEN/YELLOW/RED zone classifications + +## Options + +| Flag | Default | Description | +|---|---|---| +| `--api-url` | `https://api.nightshift.sh` | Nightshift API base URL | +| `--api-key` | `12345` | API key | +| `--waves` | `5,10,20,30,50,50,50` | Comma-separated wave sizes | +| `--duration` | `180` | Run duration per agent (seconds) | +| `--wave-interval` | `30` | Seconds between wave launches | +| `--host` | — | SSH host for monitoring | +| `--key` | — | SSH key path for monitoring | +| `--output-dir` | `loadtest/results` | Output directory | +| `--skip-deploy` | `false` | Reuse existing agent (skip deployment) | +| `--fail-threshold` | `50` | Wave failure % that stops the test | +| `--vis` | — | Visualize results instead of running a test | + +## Metrics + +**Per-run timing:** +- `submit_duration_s` — time for POST to return 202 +- `cold_start_s` — time from submission to first SSE event (includes VM boot) +- `total_duration_s` — full run duration + +**Per-wave aggregates:** +- Success/failure rate +- Avg, P95, max cold start + +**Host resources** (from `monitor.json`): +- CPU load average, memory usage, disk usage +- Firecracker process count, TAP device count +- Nightshift file descriptors, iptables rules + +## Zone classification + +Each wave is classified into a zone based on its metrics: + +| Zone | Criteria | Meaning | +|---|---|---| +| **GREEN** | failure < 5%, p95 cold start < 15s, avg < 10s | Safe operating range | +| **YELLOW** | avg cold start > 10s or p95 > 15s | Approaching limits, plan to scale | +| **RED** | failure > 5% or p95 cold start > 30s | Over capacity, errors occurring | + +## Visualization + +`--vis` produces a PNG with four panels: + +1. **P95 Cold Start** — line chart colored by zone with gradient fill, annotated peak/best values +2. **Success Rate** — per-wave bar chart with overall pass rate +3. **Memory Usage** — time series from monitor data with peak/start/end callouts +4. **Active VMs & System Load** — Firecracker count + load average overlay + +Charts use a dark theme with monospace fonts. Monitor panels only appear when `monitor.json` is present alongside the result file. diff --git a/loadtest/agent.py b/loadtest/agent.py new file mode 100644 index 0000000..9553132 --- /dev/null +++ b/loadtest/agent.py @@ -0,0 +1,78 @@ +"""Load-test agent — deployed to Nightshift, runs for a configurable duration. + +The prompt should be a number of seconds to run (e.g. "180"). +The agent does light CPU work (prime sieve) and emits periodic heartbeats +so the load test runner can track liveness. + +Usage (deploy manually): + uv run nightshift deploy loadtest/agent.py + +Or let loadtest/run.py deploy it automatically via the API. +""" + +import os +import time + +from nightshift import AgentConfig, NightshiftApp + +app = NightshiftApp() + + +@app.agent( + AgentConfig( + vcpu_count=2, + mem_size_mib=2048, + timeout_seconds=1800, + max_concurrent_vms=200, + stateful=False, + ) +) +async def loadtest_agent(prompt: str): + """Run for the requested duration with periodic heartbeats.""" + try: + duration = int(prompt.strip()) + except ValueError: + duration = 180 + + start = time.monotonic() + heartbeat_num = 0 + + yield { + "type": "agent.message", + "role": "assistant", + "content": f"loadtest: starting, duration={duration}s, pid={os.getpid()}", + } + + while time.monotonic() - start < duration: + # Light CPU work: count primes up to 5000 via sieve + sieve = [True] * 5000 + sieve[0] = sieve[1] = False + for i in range(2, int(5000**0.5) + 1): + if sieve[i]: + for j in range(i * i, 5000, i): + sieve[j] = False + prime_count = sum(sieve) + + heartbeat_num += 1 + elapsed = time.monotonic() - start + yield { + "type": "agent.message", + "role": "assistant", + "content": ( + f"loadtest: heartbeat {heartbeat_num}, " + f"elapsed={elapsed:.1f}s, primes={prime_count}" + ), + } + + # Sleep between heartbeats (10s intervals) + remaining = duration - (time.monotonic() - start) + if remaining > 0: + import asyncio + await asyncio.sleep(min(10, remaining)) + + total = time.monotonic() - start + yield { + "type": "agent.message", + "role": "assistant", + "content": f"loadtest: completed, total={total:.1f}s, heartbeats={heartbeat_num}", + } diff --git a/loadtest/monitor.py b/loadtest/monitor.py new file mode 100644 index 0000000..d2e82d9 --- /dev/null +++ b/loadtest/monitor.py @@ -0,0 +1,271 @@ +"""Host resource monitor — samples system metrics via SSH during load tests. + +Runs independently alongside the load test, writing timestamped samples to a +JSON file. Each sample captures CPU, memory, disk, process counts, file +descriptors, and network state on the remote host. + +Usage: + uv run python loadtest/monitor.py --host 34.197.220.78 --key ~/.ssh/nightshift.pem + +Or imported by run.py and started programmatically. +""" + +from __future__ import annotations + +import asyncio +import json +import os +import time +from dataclasses import asdict, dataclass, field + + +@dataclass +class HostSample: + timestamp: float = 0.0 + elapsed_s: float = 0.0 + + # CPU (from /proc/stat snapshot via mpstat or top) + cpu_percent: float = 0.0 + load_avg_1m: float = 0.0 + load_avg_5m: float = 0.0 + load_avg_15m: float = 0.0 + + # Memory + mem_total_mb: int = 0 + mem_used_mb: int = 0 + mem_available_mb: int = 0 + mem_percent: float = 0.0 + + # Disk + disk_total_gb: float = 0.0 + disk_used_gb: float = 0.0 + disk_available_gb: float = 0.0 + disk_percent: float = 0.0 + + # Processes + firecracker_count: int = 0 + tap_device_count: int = 0 + nightshift_fd_count: int = 0 + iptables_rule_count: int = 0 + + # Errors during collection + errors: list[str] = field(default_factory=list) + + +SAMPLE_SCRIPT = r""" +import json, os, subprocess + +sample = {} + +# Load average +with open('/proc/loadavg') as f: + parts = f.read().split() + sample['load_avg_1m'] = float(parts[0]) + sample['load_avg_5m'] = float(parts[1]) + sample['load_avg_15m'] = float(parts[2]) + +# CPU usage from /proc/stat (instant snapshot — idle ratio) +with open('/proc/stat') as f: + line = f.readline() # cpu user nice system idle iowait irq softirq steal + parts = line.split()[1:] + vals = [int(x) for x in parts] + total = sum(vals) + idle = vals[3] + vals[4] # idle + iowait + sample['cpu_percent'] = round(100 * (1 - idle / total), 1) if total else 0 + +# Memory from /proc/meminfo +meminfo = {} +with open('/proc/meminfo') as f: + for line in f: + key, val = line.split(':') + meminfo[key.strip()] = int(val.strip().split()[0]) # kB +sample['mem_total_mb'] = meminfo.get('MemTotal', 0) // 1024 +sample['mem_available_mb'] = meminfo.get('MemAvailable', 0) // 1024 +sample['mem_used_mb'] = sample['mem_total_mb'] - sample['mem_available_mb'] +sample['mem_percent'] = round(100 * sample['mem_used_mb'] / sample['mem_total_mb'], 1) if sample['mem_total_mb'] else 0 + +# Disk usage +st = os.statvfs('/') +sample['disk_total_gb'] = round(st.f_blocks * st.f_frsize / 1e9, 1) +sample['disk_available_gb'] = round(st.f_bavail * st.f_frsize / 1e9, 1) +sample['disk_used_gb'] = round(sample['disk_total_gb'] - sample['disk_available_gb'], 1) +sample['disk_percent'] = round(100 * sample['disk_used_gb'] / sample['disk_total_gb'], 1) if sample['disk_total_gb'] else 0 + +# Firecracker process count +try: + out = subprocess.check_output(['pgrep', '-c', 'firecracker'], text=True).strip() + sample['firecracker_count'] = int(out) +except (subprocess.CalledProcessError, ValueError): + sample['firecracker_count'] = 0 + +# TAP device count +try: + out = subprocess.check_output(['bash', '-c', 'ip link show | grep -c "tap"'], text=True).strip() + sample['tap_device_count'] = int(out) +except (subprocess.CalledProcessError, ValueError): + sample['tap_device_count'] = 0 + +# Nightshift process file descriptor count +try: + pid = subprocess.check_output(['pgrep', '-f', 'nightshift serve'], text=True).strip().split()[0] + out = subprocess.check_output(['bash', '-c', f'ls /proc/{pid}/fd 2>/dev/null | wc -l'], text=True).strip() + sample['nightshift_fd_count'] = int(out) +except (subprocess.CalledProcessError, ValueError, IndexError): + sample['nightshift_fd_count'] = -1 + +# iptables rule count +try: + out = subprocess.check_output(['sudo', 'iptables', '-L', '-n', '--line-numbers'], text=True) + sample['iptables_rule_count'] = len([l for l in out.splitlines() if l and l[0].isdigit()]) +except (subprocess.CalledProcessError, ValueError): + sample['iptables_rule_count'] = -1 + +print(json.dumps(sample)) +""" + + +class HostMonitor: + """Collects host metrics via SSH at a configurable interval.""" + + def __init__( + self, + host: str, + key_path: str, + user: str = "ubuntu", + interval: float = 5.0, + output_path: str = "loadtest/results/monitor.json", + ): + self.host = host + self.key_path = key_path + self.user = user + self.interval = interval + self.output_path = output_path + self.samples: list[dict] = [] + self._start_time: float = 0 + self._task: asyncio.Task | None = None + + async def _run_ssh(self, cmd: str) -> tuple[str, str]: + """Run a command on the remote host via SSH.""" + proc = await asyncio.create_subprocess_exec( + "ssh", + "-i", self.key_path, + "-o", "StrictHostKeyChecking=no", + "-o", "ConnectTimeout=5", + f"{self.user}@{self.host}", + cmd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + stdout, stderr = await proc.communicate() + return stdout.decode().strip(), stderr.decode().strip() + + async def _collect_sample(self) -> HostSample: + """Collect a single sample from the remote host.""" + sample = HostSample( + timestamp=time.time(), + elapsed_s=round(time.time() - self._start_time, 1), + ) + + try: + # Run the collection script remotely via python3 + stdout, stderr = await self._run_ssh(f"python3 -c {_shell_quote(SAMPLE_SCRIPT)}") + if stdout: + data = json.loads(stdout) + for key, val in data.items(): + if hasattr(sample, key): + setattr(sample, key, val) + if stderr: + sample.errors.append(f"stderr: {stderr[:200]}") + except Exception as e: + sample.errors.append(str(e)) + + return sample + + async def _loop(self) -> None: + """Main sampling loop.""" + self._start_time = time.time() + while True: + try: + sample = await self._collect_sample() + sample_dict = asdict(sample) + self.samples.append(sample_dict) + self._write_samples() + + # Print summary line + print( + f"[monitor] t={sample.elapsed_s:.0f}s " + f"cpu={sample.cpu_percent:.0f}% " + f"mem={sample.mem_used_mb}/{sample.mem_total_mb}MB ({sample.mem_percent:.0f}%) " + f"disk={sample.disk_used_gb}/{sample.disk_total_gb}GB " + f"fc={sample.firecracker_count} tap={sample.tap_device_count} " + f"fd={sample.nightshift_fd_count}" + ) + except asyncio.CancelledError: + raise + except Exception as e: + print(f"[monitor] error: {e}") + + await asyncio.sleep(self.interval) + + def _write_samples(self) -> None: + """Write accumulated samples to disk.""" + os.makedirs(os.path.dirname(self.output_path), exist_ok=True) + with open(self.output_path, "w") as f: + json.dump(self.samples, f, indent=2) + + def start(self) -> asyncio.Task: + """Start the monitoring loop as a background task.""" + self._task = asyncio.create_task(self._loop()) + return self._task + + async def stop(self) -> None: + """Stop the monitoring loop and write final samples.""" + if self._task: + self._task.cancel() + try: + await self._task + except asyncio.CancelledError: + pass + self._write_samples() + print(f"[monitor] stopped, {len(self.samples)} samples written to {self.output_path}") + + +def _shell_quote(s: str) -> str: + """Quote a string for use in a shell command.""" + return "'" + s.replace("'", "'\"'\"'") + "'" + + +async def main(): + import argparse + + parser = argparse.ArgumentParser(description="Monitor Nightshift host resources via SSH") + parser.add_argument("--host", required=True, help="Host IP or hostname") + parser.add_argument("--key", required=True, help="Path to SSH private key") + parser.add_argument("--user", default="ubuntu", help="SSH username") + parser.add_argument("--interval", type=float, default=5.0, help="Sampling interval in seconds") + parser.add_argument("--output", default="loadtest/results/monitor.json", help="Output JSON file") + args = parser.parse_args() + + monitor = HostMonitor( + host=args.host, + key_path=args.key, + user=args.user, + interval=args.interval, + output_path=args.output, + ) + + print(f"[monitor] starting, host={args.host}, interval={args.interval}s") + monitor.start() + + try: + # Run forever until Ctrl-C + while True: + await asyncio.sleep(1) + except KeyboardInterrupt: + print("\n[monitor] interrupted") + finally: + await monitor.stop() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/loadtest/run.py b/loadtest/run.py new file mode 100644 index 0000000..86233e1 --- /dev/null +++ b/loadtest/run.py @@ -0,0 +1,657 @@ +"""Load test runner — ramps concurrent Nightshift VMs to find the concurrency ceiling. + +Deploys a test agent, launches runs in configurable waves, collects metrics, +and outputs a scaling report. + +Usage: + uv run python loadtest/run.py --waves 5,10,20,30,50,50,50 --duration 180 + uv run --with matplotlib --with numpy python loadtest/run.py --vis + +Options: + --api-url Nightshift API URL (default: https://api.nightshift.sh) + --api-key API key (default: 12345) + --waves Comma-separated wave sizes (default: 5,10,20,30,50,50,50) + --duration Run duration in seconds per agent (default: 180) + --wave-interval Seconds between wave launches (default: 30) + --host SSH host for monitoring (optional) + --key SSH key path for monitoring (optional) + --output-dir Output directory (default: loadtest/results) + --skip-deploy Skip agent deployment (reuse existing) + --fail-threshold Wave failure % to stop (default: 50) +""" + +from __future__ import annotations + +import argparse +import asyncio +import io +import json +import os +import sys +import tarfile +import time +from dataclasses import asdict, dataclass, field + +import httpx +import httpx_sse + +# Ensure the project root is on sys.path for imports +sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..")) + + +# ── Data types ─────────────────────────────────────────────────── + +@dataclass +class RunResult: + run_id: str = "" + wave: int = 0 + wave_index: int = 0 + status: str = "pending" # pending, started, completed, error, timeout + error: str = "" + + # Timing + submit_time: float = 0.0 + submit_done_time: float = 0.0 # when 202 came back + sse_connect_time: float = 0.0 # when SSE connection opened + first_event_time: float = 0.0 + end_time: float = 0.0 + + submit_duration_s: float = 0.0 # time for POST to return 202 + cold_start_s: float = 0.0 # time to first SSE event + total_duration_s: float = 0.0 + heartbeat_count: int = 0 + events: list[str] = field(default_factory=list) + + +@dataclass +class WaveResult: + wave_num: int = 0 + size: int = 0 + start_time: float = 0.0 + runs: list[RunResult] = field(default_factory=list) + + @property + def completed(self) -> int: + return sum(1 for r in self.runs if r.status == "completed") + + @property + def failed(self) -> int: + return sum(1 for r in self.runs if r.status in ("error", "timeout")) + + @property + def success_rate(self) -> float: + finished = self.completed + self.failed + return (self.completed / finished * 100) if finished else 0.0 + + @property + def failure_rate(self) -> float: + finished = self.completed + self.failed + return (self.failed / finished * 100) if finished else 0.0 + + @property + def avg_cold_start(self) -> float: + starts = [r.cold_start_s for r in self.runs if r.cold_start_s > 0] + return sum(starts) / len(starts) if starts else 0.0 + + @property + def max_cold_start(self) -> float: + starts = [r.cold_start_s for r in self.runs if r.cold_start_s > 0] + return max(starts) if starts else 0.0 + + @property + def p95_cold_start(self) -> float: + starts = sorted(r.cold_start_s for r in self.runs if r.cold_start_s > 0) + if not starts: + return 0.0 + idx = int(len(starts) * 0.95) + return starts[min(idx, len(starts) - 1)] + + +# ── Agent deployment ────────────────────────────────────────────── + +AGENT_SOURCE = """\ +import asyncio +import os +import time + +from nightshift import AgentConfig, NightshiftApp + +app = NightshiftApp() + + +@app.agent( + AgentConfig( + vcpu_count=2, + mem_size_mib=2048, + timeout_seconds=1800, + max_concurrent_vms=200, + stateful=False, + ) +) +async def loadtest_agent(prompt: str): + try: + duration = int(prompt.strip()) + except ValueError: + duration = 180 + + start = time.monotonic() + heartbeat_num = 0 + + yield { + "type": "agent.message", + "role": "assistant", + "content": f"loadtest: starting, duration={duration}s, pid={os.getpid()}", + } + + while time.monotonic() - start < duration: + sieve = [True] * 5000 + sieve[0] = sieve[1] = False + for i in range(2, int(5000**0.5) + 1): + if sieve[i]: + for j in range(i * i, 5000, i): + sieve[j] = False + prime_count = sum(sieve) + + heartbeat_num += 1 + elapsed = time.monotonic() - start + yield { + "type": "agent.message", + "role": "assistant", + "content": ( + f"loadtest: heartbeat {heartbeat_num}, " + f"elapsed={elapsed:.1f}s, primes={prime_count}" + ), + } + + remaining = duration - (time.monotonic() - start) + if remaining > 0: + await asyncio.sleep(min(10, remaining)) + + total = time.monotonic() - start + yield { + "type": "agent.message", + "role": "assistant", + "content": f"loadtest: completed, total={total:.1f}s, heartbeats={heartbeat_num}", + } +""" + +PYPROJECT_TOML = """\ +[project] +name = "loadtest-agent" +version = "0.1.0" +requires-python = ">=3.12" +dependencies = ["nightshift-sdk"] +""" + + +def _make_archive(files: dict[str, str]) -> bytes: + """Create a tar.gz archive in memory from filename -> content pairs.""" + buf = io.BytesIO() + with tarfile.open(fileobj=buf, mode="w:gz") as tar: + for name, content in files.items(): + data = content.encode() + info = tarfile.TarInfo(name=name) + info.size = len(data) + tar.addfile(info, io.BytesIO(data)) + buf.seek(0) + return buf.read() + + +async def deploy_agent(client: httpx.AsyncClient, headers: dict) -> str: + """Deploy the load test agent. Returns the agent name.""" + agent_name = "loadtest_agent" + + archive = _make_archive({ + "agent.py": AGENT_SOURCE, + "pyproject.toml": PYPROJECT_TOML, + }) + + config = { + "vcpu_count": 2, + "mem_size_mib": 2048, + "timeout_seconds": 1800, + "max_concurrent_vms": 200, + "stateful": False, + } + + print(f"[deploy] deploying agent '{agent_name}'...") + r = await client.post( + "/api/agents", + data={ + "name": agent_name, + "source_filename": "agent.py", + "function_name": "loadtest_agent", + "config_json": json.dumps(config), + }, + files={"archive": ("archive.tar.gz", archive, "application/gzip")}, + headers=headers, + timeout=120, + ) + r.raise_for_status() + data = r.json() + print(f"[deploy] agent deployed: {data['status']} (id: {data['id']})") + return agent_name + + +# ── Single run executor ────────────────────────────────────────── + +async def execute_run( + client: httpx.AsyncClient, + headers: dict, + agent_name: str, + duration: int, + wave: int, + wave_index: int, +) -> RunResult: + """Submit a run and stream its SSE events until completion.""" + result = RunResult(wave=wave, wave_index=wave_index) + result.submit_time = time.time() + + # Phase 1: Submit the run (POST → 202) + try: + r = await client.post( + f"/api/agents/{agent_name}/runs", + json={"prompt": str(duration)}, + headers=headers, + timeout=30, + ) + result.submit_done_time = time.time() + result.submit_duration_s = result.submit_done_time - result.submit_time + r.raise_for_status() + data = r.json() + result.run_id = data["id"] + result.status = "started" + except httpx.HTTPStatusError as e: + result.submit_done_time = time.time() + result.submit_duration_s = result.submit_done_time - result.submit_time + result.status = "error" + result.error = f"submit: HTTP {e.response.status_code} {e.response.text[:200]}" + result.end_time = time.time() + result.total_duration_s = result.end_time - result.submit_time + return result + except Exception as e: + result.submit_done_time = time.time() + result.submit_duration_s = result.submit_done_time - result.submit_time + result.status = "error" + result.error = f"submit: {type(e).__name__}: {e}" + result.end_time = time.time() + result.total_duration_s = result.end_time - result.submit_time + return result + + # Phase 2: Connect to SSE stream + try: + async with httpx_sse.aconnect_sse( + client, + "GET", + f"/api/runs/{result.run_id}/events", + headers=headers, + timeout=httpx.Timeout(timeout=duration + 120, connect=30), + ) as sse: + result.sse_connect_time = time.time() + + async for event in sse.aiter_sse(): + now = time.time() + + if result.first_event_time == 0: + result.first_event_time = now + result.cold_start_s = now - result.submit_time + + result.events.append(event.event) + + if event.event == "agent.message": + try: + payload = json.loads(event.data) + if "heartbeat" in payload.get("content", ""): + result.heartbeat_count += 1 + except json.JSONDecodeError: + pass + + if event.event in ("nightshift.completed", "nightshift.error", "nightshift.interrupted"): + result.end_time = now + result.total_duration_s = now - result.submit_time + + if event.event == "nightshift.completed": + result.status = "completed" + elif event.event == "nightshift.error": + result.status = "error" + try: + payload = json.loads(event.data) + result.error = payload.get("error", "unknown") + except json.JSONDecodeError: + result.error = "unknown" + else: + result.status = "error" + result.error = "interrupted" + break + + except (httpx.ReadTimeout, asyncio.TimeoutError): + result.status = "timeout" + result.error = "SSE stream timed out" + result.end_time = time.time() + result.total_duration_s = result.end_time - result.submit_time + except Exception as e: + result.status = "error" + result.error = f"SSE stream error: {e}" + result.end_time = time.time() + result.total_duration_s = result.end_time - result.submit_time + + return result + + +# ── Wave orchestration ──────────────────────────────────────────── + +async def run_wave( + client: httpx.AsyncClient, + headers: dict, + agent_name: str, + duration: int, + wave_num: int, + wave_size: int, +) -> WaveResult: + """Launch a wave of concurrent runs and collect results.""" + wave = WaveResult(wave_num=wave_num, size=wave_size, start_time=time.time()) + + tasks = [ + execute_run(client, headers, agent_name, duration, wave_num, i) + for i in range(wave_size) + ] + results = await asyncio.gather(*tasks, return_exceptions=True) + + for r in results: + if isinstance(r, Exception): + wave.runs.append(RunResult( + wave=wave_num, status="error", error=str(r), + end_time=time.time(), + )) + else: + wave.runs.append(r) + + return wave + + +# ── Results output ──────────────────────────────────────────────── + +def print_summary(waves: list[WaveResult], total_elapsed: float) -> None: + """Print a summary table to stdout.""" + print("\n" + "=" * 100) + print("LOAD TEST RESULTS") + print("=" * 100) + print( + f"{'Wave':>5} {'Size':>5} {'OK':>4} {'Fail':>5} {'Rate':>7} " + f"{'Submit':>8} {'Avg CS':>8} {'P95 CS':>8} {'Max CS':>8} {'Zone':>8}" + ) + print("-" * 100) + + cumulative_vms = 0 + for w in waves: + cumulative_vms += w.size + zone = _classify_zone(w) + # Average submit duration for this wave + submits = [r.submit_duration_s for r in w.runs if r.submit_duration_s > 0] + avg_submit = sum(submits) / len(submits) if submits else 0 + print( + f"{w.wave_num:>5} {w.size:>5} {w.completed:>4} {w.failed:>5} " + f"{w.success_rate:>6.1f}% " + f"{avg_submit:>7.1f}s " + f"{w.avg_cold_start:>7.1f}s {w.p95_cold_start:>7.1f}s {w.max_cold_start:>7.1f}s " + f"{zone:>8}" + ) + + print("-" * 100) + total_runs = sum(w.size for w in waves) + total_ok = sum(w.completed for w in waves) + total_fail = sum(w.failed for w in waves) + print(f"Total: {total_runs} runs, {total_ok} completed, {total_fail} failed") + print(f"Duration: {total_elapsed:.0f}s") + + # Error breakdown + errors: dict[str, int] = {} + for w in waves: + for r in w.runs: + if r.error: + errors[r.error[:100]] = errors.get(r.error[:100], 0) + 1 + if errors: + print(f"\nError breakdown:") + for err, count in sorted(errors.items(), key=lambda x: -x[1]): + print(f" {count:>4}x {err}") + + # Scaling report + print("\n" + "=" * 90) + print("SCALING REPORT") + print("=" * 90) + + green_max = 0 + yellow_max = 0 + red_start = 0 + + cumulative = 0 + for w in waves: + cumulative += w.size + zone = _classify_zone(w) + if zone == "GREEN": + green_max = cumulative + elif zone == "YELLOW" and yellow_max == 0: + yellow_max = cumulative + elif zone == "RED" and red_start == 0: + red_start = cumulative + + if green_max: + print(f" GREEN zone (safe): up to ~{green_max} concurrent VMs") + print(f" Cold starts <10s, no errors, comfortable operating range") + if yellow_max: + print(f" YELLOW zone (caution): ~{green_max + 1}-{yellow_max} concurrent VMs") + print(f" Cold starts 10-30s, possible degradation, plan to scale") + if red_start: + print(f" RED zone (critical): >{red_start} concurrent VMs") + print(f" Errors appearing, cold starts >30s or failing") + + if green_max: + print(f"\n Recommendation: Set max concurrent VMs to ~{green_max} per c5.metal node.") + print(f" Scale to a second node when approaching {green_max} concurrent users.") + + print("=" * 90) + + +def _classify_zone(w: WaveResult) -> str: + """Classify a wave into GREEN/YELLOW/RED based on metrics.""" + if w.failure_rate > 5 or w.p95_cold_start > 30: + return "RED" + if w.avg_cold_start > 10 or w.p95_cold_start > 15: + return "YELLOW" + return "GREEN" + + +def save_results(waves: list[WaveResult], output_dir: str) -> str: + """Save detailed results to JSON.""" + os.makedirs(output_dir, exist_ok=True) + ts = time.strftime("%Y%m%d-%H%M%S") + path = os.path.join(output_dir, f"loadtest-{ts}.json") + + output = { + "timestamp": ts, + "waves": [], + } + for w in waves: + wave_data = { + "wave_num": w.wave_num, + "size": w.size, + "start_time": w.start_time, + "completed": w.completed, + "failed": w.failed, + "success_rate": w.success_rate, + "avg_cold_start": w.avg_cold_start, + "p95_cold_start": w.p95_cold_start, + "max_cold_start": w.max_cold_start, + "zone": _classify_zone(w), + "runs": [asdict(r) for r in w.runs], + } + output["waves"].append(wave_data) + + with open(path, "w") as f: + json.dump(output, f, indent=2) + + print(f"\n[results] detailed results written to {path}") + return path + + +# ── Main ────────────────────────────────────────────────────────── + +async def main(): + parser = argparse.ArgumentParser(description="Nightshift load test runner") + parser.add_argument("--api-url", default="https://api.nightshift.sh", help="API base URL") + parser.add_argument("--api-key", default="12345", help="API key") + parser.add_argument("--waves", default="5,10,20,30,50,50,50", help="Comma-separated wave sizes") + parser.add_argument("--duration", type=int, default=180, help="Run duration per agent (seconds)") + parser.add_argument("--wave-interval", type=int, default=30, help="Seconds between wave launches") + parser.add_argument("--host", help="SSH host for monitoring") + parser.add_argument("--key", help="SSH key path for monitoring") + parser.add_argument("--output-dir", default="loadtest/results", help="Output directory") + parser.add_argument("--skip-deploy", action="store_true", help="Skip agent deployment") + parser.add_argument("--fail-threshold", type=float, default=50, help="Wave failure %% to stop test") + parser.add_argument("--vis", nargs="?", const=True, default=False, + help="Visualize results (optionally pass a result JSON path)") + args = parser.parse_args() + + # Visualization-only mode + if args.vis is not False: + from loadtest.visualize import visualize + path = args.vis if isinstance(args.vis, str) and args.vis is not True else None + visualize(result_path=path, output_dir=args.output_dir) + return + + wave_sizes = [int(x) for x in args.waves.split(",")] + headers = {"Authorization": f"Bearer {args.api_key}"} + + print(f"[config] API: {args.api_url}") + print(f"[config] waves: {wave_sizes}") + print(f"[config] duration: {args.duration}s per run") + print(f"[config] wave interval: {args.wave_interval}s") + print(f"[config] fail threshold: {args.fail_threshold}%") + + # Start host monitor if SSH details provided + monitor = None + if args.host and args.key: + from loadtest.monitor import HostMonitor + monitor = HostMonitor( + host=args.host, + key_path=args.key, + output_path=os.path.join(args.output_dir, "monitor.json"), + ) + monitor.start() + print(f"[monitor] started background monitoring of {args.host}") + + # Use a large connection pool — each SSE stream holds an open connection, + # and we need enough headroom for new POSTs alongside hundreds of streams. + pool_limits = httpx.Limits( + max_connections=1000, + max_keepalive_connections=500, + ) + async with httpx.AsyncClient( + base_url=args.api_url, + limits=pool_limits, + ) as client: + # Deploy agent + agent_name = "loadtest_agent" + if not args.skip_deploy: + try: + agent_name = await deploy_agent(client, headers) + except httpx.HTTPStatusError as e: + print(f"[deploy] failed: {e.response.status_code} {e.response.text}") + return + except Exception as e: + print(f"[deploy] failed: {e}") + return + + # Run waves + test_start = time.time() + wave_results: list[WaveResult] = [] + wave_tasks: list[asyncio.Task] = [] + + for i, size in enumerate(wave_sizes): + wave_num = i + 1 + elapsed = time.time() - test_start + cumulative = sum(wave_sizes[:i + 1]) + + print(f"\n[wave {wave_num}] t={elapsed:.0f}s launching {size} runs (cumulative: {cumulative})") + + # Fire wave as a background task (don't await — waves accumulate) + task = asyncio.create_task( + run_wave(client, headers, agent_name, args.duration, wave_num, size) + ) + wave_tasks.append(task) + + # Wait for interval before next wave (unless it's the last) + if i < len(wave_sizes) - 1: + # Check completed waves for failure threshold + completed_waves = [] + for t in wave_tasks: + if t.done(): + try: + result = t.result() + if result not in wave_results: + wave_results.append(result) + _print_wave_summary(result) + except Exception as e: + print(f"[error] wave task failed: {e}") + + # Check if we should stop + if wave_results: + last = wave_results[-1] + if last.runs and last.failure_rate > args.fail_threshold: + print( + f"\n[STOP] wave {last.wave_num} failure rate " + f"{last.failure_rate:.0f}% exceeds threshold {args.fail_threshold}%" + ) + break + + await asyncio.sleep(args.wave_interval) + + # Wait for all remaining waves to complete + print("\n[wait] waiting for all waves to complete...") + remaining = [t for t in wave_tasks if not t.done()] + if remaining: + done, _ = await asyncio.wait(remaining, timeout=args.duration + 300) + for t in done: + try: + result = t.result() + if result not in wave_results: + wave_results.append(result) + _print_wave_summary(result) + except Exception as e: + print(f"[error] wave task failed: {e}") + + # Sort waves by number + wave_results.sort(key=lambda w: w.wave_num) + + total_elapsed = time.time() - test_start + + # Stop monitor + if monitor: + await monitor.stop() + + # Output results + save_results(wave_results, args.output_dir) + print_summary(wave_results, total_elapsed) + + +def _print_wave_summary(w: WaveResult) -> None: + """Print a one-line summary when a wave completes.""" + zone = _classify_zone(w) + submits = [r.submit_duration_s for r in w.runs if r.submit_duration_s > 0] + avg_submit = sum(submits) / len(submits) if submits else 0 + # Show first error type if any + first_err = "" + for r in w.runs: + if r.error: + first_err = f" err={r.error[:60]}" + break + print( + f"[wave {w.wave_num} done] " + f"{w.completed}/{w.size} ok, {w.failed} failed, " + f"submit={avg_submit:.1f}s, avg_cs={w.avg_cold_start:.1f}s, p95_cs={w.p95_cold_start:.1f}s " + f"[{zone}]{first_err}" + ) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/loadtest/visualize.py b/loadtest/visualize.py new file mode 100644 index 0000000..b27cb42 --- /dev/null +++ b/loadtest/visualize.py @@ -0,0 +1,496 @@ +""" +Usage: + uv run python loadtest/run.py --vis # latest result + uv run python loadtest/run.py --vis loadtest/results/loadtest-20260226-114607.json +""" + +from __future__ import annotations + +import json +import os +import glob +from datetime import datetime + +import matplotlib + +matplotlib.use("Agg") +import matplotlib.pyplot as plt +import matplotlib.patches as FancyBboxPatch +import numpy as np + + +BG = "#0f1117" +PANEL_BG = "#161b22" +TEXT = "#e6edf3" +TEXT_MUTED = "#7d8590" +GRID = "#21262d" + +GREEN = "#3fb950" +GREEN_BG = "#0d4a28" +YELLOW = "#d29922" +YELLOW_BG = "#4a3a0a" +RED = "#f85149" +RED_BG = "#5a1a18" +ORANGE = "#e3974e" +ORANGE_BG = "#4a2e10" +ACCENT = "#58a6ff" + +ZONE_LINE = {"GREEN": GREEN, "YELLOW": YELLOW, "RED": RED} + + +def _setup_style(): + plt.rcParams.update( + { + "figure.facecolor": BG, + "axes.facecolor": PANEL_BG, + "axes.edgecolor": GRID, + "axes.labelcolor": TEXT_MUTED, + "axes.grid": True, + "grid.color": GRID, + "grid.alpha": 0.5, + "grid.linewidth": 0.4, + "text.color": TEXT, + "xtick.color": TEXT_MUTED, + "ytick.color": TEXT_MUTED, + "xtick.labelsize": 11, + "ytick.labelsize": 11, + "legend.facecolor": PANEL_BG, + "legend.edgecolor": GRID, + "legend.fontsize": 11, + "font.family": "monospace", + } + ) + + +def _callout(ax, x, y, label, value, color, bg_color, *, offset=(0, 40), fontsize=18): + """Rounded-rectangle callout at a data point.""" + ax.plot( + x, + y, + "o", + color=color, + markersize=7, + zorder=10, + markeredgecolor=bg_color, + markeredgewidth=1.5, + ) + ax.annotate( + f" {label} \n {value} ", + xy=(x, y), + xytext=offset, + textcoords="offset points", + fontsize=fontsize, + fontweight="bold", + color=color, + fontfamily="monospace", + ha="center", + va="center", + bbox=dict( + boxstyle="round,pad=0.5", facecolor=bg_color, edgecolor=color, alpha=0.95, linewidth=1.5 + ), + arrowprops=dict(arrowstyle="-", color=color, lw=1, alpha=0.6), + zorder=11, + ) + + +def _gradient_fill(ax, x, y, color, alpha=0.3, n_bands=25): + """Vertical-fade fill under a curve.""" + x, y = np.asarray(x, float), np.asarray(y, float) + if len(x) < 2: + return + for j in range(n_bands): + frac_hi = 1 - j / n_bands + frac_lo = 1 - (j + 1) / n_bands + ax.fill_between( + x, y * frac_lo, y * frac_hi, color=color, alpha=alpha * frac_hi, linewidth=0 + ) + + +def _zone_line(ax, x, y, zones, lw=3): + """Line colored per-segment by zone.""" + x, y = np.asarray(x, float), np.asarray(y, float) + for i in range(len(x) - 1): + c = ZONE_LINE.get(zones[i], GREEN) + ax.plot(x[i : i + 2], y[i : i + 2], color=c, lw=lw, solid_capstyle="round", zorder=5) + for i, z in enumerate(zones): + ax.plot(x[i], y[i], "o", color=ZONE_LINE.get(z, GREEN), ms=6, zorder=6) + + +def _chart_cold_start(ax, waves): + valid = [(i, w) for i, w in enumerate(waves) if w["avg_cold_start"] > 0] + if not valid: + ax.text( + 0.5, + 0.5, + "No cold start data (all waves failed)", + transform=ax.transAxes, + ha="center", + va="center", + fontsize=16, + color=TEXT_MUTED, + ) + return + + indices = [i for i, _ in valid] + p95 = [w["p95_cold_start"] for _, w in valid] + avg = [w["avg_cold_start"] for _, w in valid] + maxcs = [w["max_cold_start"] for _, w in valid] + zones = [w["zone"] for _, w in valid] + sizes = [w["size"] for _, w in valid] + + # cumulative VMs for x-axis + cum = 0 + cum_all = [] + for w in waves: + cum += w["size"] + cum_all.append(cum) + x = [cum_all[i] for i in indices] + + ax.set_ylim(0, max(maxcs) * 1.35) + + # gradient fill per segment, colored by zone + for i in range(len(x) - 1): + c = ZONE_LINE.get(zones[i], GREEN) + seg_x = np.array([x[i], x[i + 1]]) + seg_y = np.array([p95[i], p95[i + 1]]) + _gradient_fill(ax, seg_x, seg_y, c, alpha=0.22) + + # lines + _zone_line(ax, x, p95, zones, lw=3) + ax.plot(x, avg, color=ACCENT, lw=1.8, alpha=0.7, ls="--", label="avg", zorder=4) + ax.plot(x, maxcs, color=RED, lw=1.2, alpha=0.35, ls=":", label="max", zorder=3) + + # annotations + pk = int(np.argmax(p95)) + bt = int(np.argmin(p95)) + + _callout( + ax, x[pk], p95[pk], "PEAK", f"{p95[pk]:.1f}s", RED, RED_BG, offset=(0, 50), fontsize=16 + ) + if bt != pk: + _callout( + ax, + x[bt], + p95[bt], + "BEST", + f"{p95[bt]:.2f}s", + GREEN, + GREEN_BG, + offset=(0, -55), + fontsize=14, + ) + last = len(p95) - 1 + if last not in (pk, bt) and len(p95) > 2: + _callout( + ax, + x[last], + p95[last], + "LAST", + f"{p95[last]:.2f}s", + ORANGE, + ORANGE_BG, + offset=(40, -45), + fontsize=13, + ) + + # title + subtitle + best_v, peak_v = min(p95), max(p95) + spread = f"{peak_v / best_v:.0f}x spread · " if best_v > 0 else "" + ax.text( + 0.0, + 1.14, + "P95 Cold Start", + transform=ax.transAxes, + fontsize=24, + fontweight="bold", + color=TEXT, + fontfamily="monospace", + va="bottom", + ) + ax.text( + 0.0, + 1.10, + f"{spread}{best_v:.2f}s → {peak_v:.1f}s", + transform=ax.transAxes, + fontsize=13, + color=GREEN, + fontfamily="monospace", + fontweight="bold", + va="top", + ) + + ax.set_xlabel("Cumulative Concurrent VMs", fontsize=12) + ax.set_ylabel("Seconds", fontsize=12) + ax.set_xticks(x) + ax.set_xticklabels([f"{v}\n(+{s})" for v, s in zip(x, sizes)]) + ax.legend(loc="upper left", framealpha=0.9) + + +def _chart_success_rate(ax, waves): + x = list(range(1, len(waves) + 1)) + rates = [w["success_rate"] for w in waves] + zones = [w["zone"] for w in waves] + sizes = [w["size"] for w in waves] + + colors = [ZONE_LINE.get(z, GREEN) for z in zones] + ax.bar( + x, rates, color=colors, alpha=0.85, width=0.55, edgecolor=colors, linewidth=1.5, zorder=5 + ) + + for xi, rate, z in zip(x, rates, zones): + c = ZONE_LINE.get(z, GREEN) + y_pos = max(rate, 3) + 2 # ensure label visible even at 0% + ax.text( + xi, + y_pos, + f"{rate:.0f}%", + ha="center", + va="bottom", + fontsize=13, + fontweight="bold", + color=c, + fontfamily="monospace", + ) + + ax.axhline(100, color=GREEN, alpha=0.25, lw=1, ls="--") + ax.axhline(95, color=YELLOW, alpha=0.15, lw=1, ls="--") + + ax.set_ylim(0, 118) + total_ok = sum(w["completed"] for w in waves) + total = sum(w["size"] for w in waves) + pct = total_ok / total * 100 if total else 0 + c = GREEN if pct > 95 else YELLOW if pct > 80 else RED + + ax.text( + 0.0, + 1.13, + "Success Rate by Wave", + transform=ax.transAxes, + fontsize=20, + fontweight="bold", + color=TEXT, + fontfamily="monospace", + va="bottom", + ) + ax.text( + 0.0, + 1.09, + f"Overall: {pct:.0f}% · {total_ok}/{total} runs passed", + transform=ax.transAxes, + fontsize=12, + color=c, + fontfamily="monospace", + fontweight="bold", + va="top", + ) + + ax.set_xlabel("Wave", fontsize=12) + ax.set_ylabel("Success %", fontsize=12) + ax.set_xticks(x) + ax.set_xticklabels([f"W{i}\n({s})" for i, s in zip(x, sizes)]) + + +def _chart_memory(ax, samples): + t = np.array([s["elapsed_s"] / 60 for s in samples]) + mem = np.array([s["mem_used_mb"] / 1024 for s in samples]) + total_gb = samples[0]["mem_total_mb"] / 1024 + + _gradient_fill(ax, t, mem, ACCENT, alpha=0.25) + ax.plot(t, mem, color=ACCENT, lw=2.5, zorder=5) + + pk = int(np.argmax(mem)) + # position PEAK callout away from the line + pk_offset_x = -80 if t[pk] > t[-1] * 0.7 else 60 + _callout( + ax, + t[pk], + mem[pk], + "PEAK", + f"{mem[pk]:.1f} GB", + RED, + RED_BG, + offset=(pk_offset_x, 45), + fontsize=15, + ) + + if pk > 5: + _callout( + ax, + t[0], + mem[0], + "START", + f"{mem[0]:.1f} GB", + ORANGE, + ORANGE_BG, + offset=(55, -40), + fontsize=12, + ) + if pk < len(mem) - 5: + _callout( + ax, + t[-1], + mem[-1], + "END", + f"{mem[-1]:.1f} GB", + GREEN, + GREEN_BG, + offset=(-55, -40), + fontsize=12, + ) + + ratio = mem[pk] / mem[0] if mem[0] > 0 else 0 + ax.text( + 0.0, + 1.13, + "Memory Usage", + transform=ax.transAxes, + fontsize=20, + fontweight="bold", + color=TEXT, + fontfamily="monospace", + va="bottom", + ) + ax.text( + 0.0, + 1.09, + f"{ratio:.0f}x increase · {mem[0]:.1f} GB → {mem[pk]:.1f} GB peak", + transform=ax.transAxes, + fontsize=12, + color=RED if ratio > 5 else YELLOW, + fontfamily="monospace", + fontweight="bold", + va="top", + ) + ax.set_xlabel("Time (minutes)", fontsize=12) + ax.set_ylabel("GB", fontsize=12) + ax.set_ylim(0, max(mem) * 1.35) + + +def _chart_vms(ax, samples): + t = np.array([s["elapsed_s"] / 60 for s in samples]) + vms = np.array([s["firecracker_count"] for s in samples]) + load = np.array([s["load_avg_1m"] for s in samples]) + + _gradient_fill(ax, t, vms, GREEN, alpha=0.2) + ax.plot(t, vms, color=GREEN, lw=2.5, zorder=5, label="VMs") + + pk = int(np.argmax(vms)) + _callout( + ax, t[pk], vms[pk], "PEAK", f"{vms[pk]} VMs", GREEN, GREEN_BG, offset=(0, 45), fontsize=15 + ) + + # Load average — normalised onto the same y-axis (no twinx) + max_vms = max(vms) if max(vms) > 0 else 1 + max_load = max(load) if max(load) > 0 else 1 + load_scaled = load * (max_vms / max_load) * 0.85 + + ax.plot( + t, + load_scaled, + color=ORANGE, + lw=1.5, + alpha=0.65, + ls="--", + label=f"Load 1m (scaled, peak {max_load:.0f})", + zorder=4, + ) + + ax.text( + 0.0, + 1.13, + "Active VMs & System Load", + transform=ax.transAxes, + fontsize=20, + fontweight="bold", + color=TEXT, + fontfamily="monospace", + va="bottom", + ) + ax.text( + 0.0, + 1.09, + f"Peak: {vms[pk]} VMs · Max load: {max_load:.0f}", + transform=ax.transAxes, + fontsize=12, + color=GREEN, + fontfamily="monospace", + fontweight="bold", + va="top", + ) + ax.set_xlabel("Time (minutes)", fontsize=12) + ax.set_ylabel("Firecracker VMs", fontsize=12) + ax.set_ylim(0, max(vms) * 1.3) + ax.legend(loc="upper left", framealpha=0.9) + + +def visualize(result_path: str | None = None, output_dir: str = "loadtest/results"): + """Generate visualisation from load test results.""" + _setup_style() + + if result_path is None: + files = sorted(glob.glob(os.path.join(output_dir, "loadtest-*.json"))) + if not files: + print(f"[vis] no result files found in {output_dir}") + return + result_path = files[-1] + + print(f"[vis] loading {result_path}") + with open(result_path) as f: + data = json.load(f) + + waves = data["waves"] + ts = data.get("timestamp", "") + + # monitor data (optional) + monitor_path = os.path.join(os.path.dirname(result_path), "monitor.json") + monitor = None + if os.path.exists(monitor_path): + with open(monitor_path) as f: + monitor = json.load(f) + if monitor: + print(f"[vis] loaded {len(monitor)} monitor samples") + + has_monitor = monitor and len(monitor) > 2 + n_rows = 4 if has_monitor else 2 + + fig, axes = plt.subplots( + n_rows, + 1, + figsize=(16, 6.5 * n_rows), + gridspec_kw={"hspace": 0.45}, + ) + axes = list(axes) + + # header + try: + dt = datetime.strptime(ts, "%Y%m%d-%H%M%S") + ts_label = dt.strftime("%b %d, %Y %H:%M") + except (ValueError, TypeError): + ts_label = ts + + fig.suptitle( + "Load Test Results", + fontsize=30, + fontweight="bold", + color=TEXT, + y=0.985, + fontfamily="monospace", + ) + fig.text( + 0.5, 0.975, ts_label, 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