tutorial

Monitoring WasmEdge with Vigilmon

WasmEdge is a high-performance WASM runtime built for edge, serverless, and AI workloads — but function execution latency spikes, plugin load failures, TensorFlow inference degradation, and container integration breaks silently impact your deployments. Here's how to monitor WasmEdge health, function performance, plugin status, and inference metrics with Vigilmon.

WasmEdge is a high-performance, lightweight WebAssembly runtime optimized for edge computing, serverless functions, and AI inference workloads. It extends the standard WASM sandbox with plugins for TensorFlow Lite, OpenCV, and FFMPEG, supports WASI-NN for neural network inference, and integrates with container runtimes like containerd and crun to run WASM modules as OCI containers. When WasmEdge function execution latency climbs due to plugin initialization overhead, when a TensorFlow Lite model fails to load on an edge node after a firmware update, when the containerd-shim loses its WasmEdge reference, or when plugin health degrades silently — your AI inference and edge compute workloads fail without any infrastructure-level alert. Vigilmon gives you external monitoring for WasmEdge process health, function execution latency, plugin availability, TensorFlow inference performance, and container integration status so you catch edge runtime failures before they propagate to end users.

What You'll Set Up

  • WasmEdge runtime process health via cron heartbeats
  • Function execution latency monitoring
  • Plugin health and load status checks
  • TensorFlow Lite inference performance tracking
  • Container integration status verification

Prerequisites

  • WasmEdge 0.13+ installed on your edge or serverless infrastructure
  • WasmEdge TensorFlow plugin (optional, for AI inference monitoring)
  • containerd or crun integration if running WASM as OCI containers
  • A free Vigilmon account

Step 1: Monitor WasmEdge Runtime Health

WasmEdge can run as a standalone CLI tool, embedded in a host application, or as a containerd shim. In all cases, the underlying runtime state is critical: if the runtime process is missing, if shared libraries are corrupt, or if the WasmEdge installation itself is broken, all downstream function invocations fail immediately. Monitor the runtime's ability to execute a trivial module as a liveness check:

  1. In Vigilmon, click Add Monitor → Cron Heartbeat.
  2. Set Expected ping interval to 2 minutes.
  3. Copy the heartbeat URL (e.g., https://vigilmon.online/heartbeat/abc123).

Create a smoke-test script that executes a minimal WASM module:

#!/bin/bash
# /usr/local/bin/wasmedge-health-check.sh

HEARTBEAT_URL="https://vigilmon.online/heartbeat/abc123"
SMOKE_MODULE="/opt/wasmedge/health-check.wasm"

# Verify wasmedge binary exists and is executable
if ! command -v wasmedge &>/dev/null; then
  echo "wasmedge binary not found"
  exit 1
fi

# Run the smoke-test module with a 5-second timeout
RESULT=$(timeout 5 wasmedge "$SMOKE_MODULE" 2>&1)
EXIT_CODE=$?

if [ $EXIT_CODE -eq 124 ]; then
  echo "WasmEdge health check timed out"
  exit 1
elif [ $EXIT_CODE -ne 0 ]; then
  echo "WasmEdge health check failed: $RESULT"
  exit 1
fi

echo "WasmEdge OK: $RESULT"
curl -s "$HEARTBEAT_URL"

A minimal health-check module in WAT (WebAssembly Text Format) that just returns 0 is sufficient:

;; health-check.wat — compile with: wat2wasm health-check.wat -o health-check.wasm
(module
  (func (export "_start"))
)

Install the cron job:

chmod +x /usr/local/bin/wasmedge-health-check.sh
(crontab -l 2>/dev/null; echo "*/2 * * * * /usr/local/bin/wasmedge-health-check.sh >> /var/log/wasmedge-health.log 2>&1") | crontab -

Step 2: Track Function Execution Latency

WasmEdge's primary use case in edge and serverless environments is executing short-lived functions on incoming requests. Function execution latency includes WASM module load time, JIT compilation (or AOT execution if pre-compiled), and the actual function body execution time. For pre-compiled AOT modules (.so files generated by wasmedge compile), latency should be near-native. Monitor latency with a timed probe:

#!/bin/bash
# /usr/local/bin/wasmedge-latency-check.sh

HEARTBEAT_URL="https://vigilmon.online/heartbeat/def456"
FUNCTION_MODULE="/opt/wasmedge/functions/request-handler.wasm"
LATENCY_THRESHOLD_MS=200

START_MS=$(date +%s%3N)
wasmedge --reactor "$FUNCTION_MODULE" handle_request 2>/dev/null
EXIT_CODE=$?
END_MS=$(date +%s%3N)

LATENCY_MS=$((END_MS - START_MS))

if [ $EXIT_CODE -ne 0 ]; then
  echo "Function execution failed (exit $EXIT_CODE)"
  exit 1
fi

if [ $LATENCY_MS -gt $LATENCY_THRESHOLD_MS ]; then
  echo "Function latency too high: ${LATENCY_MS}ms > ${LATENCY_THRESHOLD_MS}ms threshold"
  exit 1
fi

echo "Function latency OK: ${LATENCY_MS}ms"
curl -s "$HEARTBEAT_URL"

Run this check every 5 minutes. If your function latency suddenly jumps — typically because an AOT-compiled binary was replaced with an interpreted .wasm file during a deploy — the heartbeat stops and you get an immediate alert.

For functions that accept HTTP requests via WasmEdge's built-in HTTP server support, add a standard Vigilmon HTTP monitor pointing to the function's endpoint alongside the heartbeat monitor.

Step 3: Verify Plugin Health

WasmEdge's plugin system extends the runtime with native capabilities: TensorFlow Lite inference, image processing via OpenCV, and video processing via FFMPEG. Plugins load as shared libraries at runtime startup. If a plugin's shared library is missing, has the wrong version, or references unavailable system libraries (e.g., after a system update changed a .so version), WasmEdge silently degrades — functions that use the plugin fail at the import resolution stage, but the WasmEdge process itself is still running.

Monitor plugin availability directly:

#!/bin/bash
# /usr/local/bin/wasmedge-plugin-check.sh

HEARTBEAT_URL="https://vigilmon.online/heartbeat/ghi789"
WASMEDGE_PLUGIN_DIR="${WASMEDGE_PLUGIN_PATH:-/usr/local/lib/wasmedge}"

REQUIRED_PLUGINS=(
  "libwasmedgePluginWasiNN.so"
  "libwasmedgePluginWasiCrypto.so"
)

MISSING=0
for plugin in "${REQUIRED_PLUGINS[@]}"; do
  if [ ! -f "${WASMEDGE_PLUGIN_DIR}/${plugin}" ]; then
    echo "Missing plugin: $plugin"
    MISSING=$((MISSING + 1))
  fi
done

if [ $MISSING -gt 0 ]; then
  echo "$MISSING required plugins missing from $WASMEDGE_PLUGIN_DIR"
  exit 1
fi

# Verify plugins are loadable (check for broken library links)
for plugin in "${REQUIRED_PLUGINS[@]}"; do
  if ! ldd "${WASMEDGE_PLUGIN_DIR}/${plugin}" 2>&1 | grep -q "not found"; then
    echo "Plugin library links OK: $plugin"
  else
    echo "Broken library dependencies in: $plugin"
    exit 1
  fi
done

echo "All plugins healthy"
curl -s "$HEARTBEAT_URL"

Customize the REQUIRED_PLUGINS array to match the plugins your deployment relies on. Run this check every 10 minutes — plugin failures are typically caused by system updates or incomplete deployments, not runtime volatility.

Step 4: Monitor TensorFlow Lite Inference Performance

WasmEdge's WASI-NN backend with TensorFlow Lite is commonly used for on-device AI inference at the edge — image classification, object detection, and NLP processing without round-tripping to a cloud API. TensorFlow Lite inference performance degrades when the model file is corrupt, when hardware acceleration (GPU/NPU) becomes unavailable, or when memory pressure forces inference onto slower code paths. Monitor inference latency with a benchmark probe:

#!/bin/bash
# /usr/local/bin/wasmedge-tflite-check.sh

HEARTBEAT_URL="https://vigilmon.online/heartbeat/jkl012"
INFERENCE_MODULE="/opt/wasmedge/ai/classify.wasm"
TEST_IMAGE="/opt/wasmedge/ai/test-image.jpg"
TFLITE_MODEL="/opt/wasmedge/ai/mobilenet_v1.tflite"
MAX_INFERENCE_MS=500   # Threshold for TFLite inference on edge hardware

START_MS=$(date +%s%3N)
wasmedge \
  --dir /opt/wasmedge/ai:/opt/wasmedge/ai \
  --nn-preload "default:TensorflowLite:AUTO:${TFLITE_MODEL}" \
  "$INFERENCE_MODULE" \
  "$TEST_IMAGE" > /tmp/wasmedge-inference-result.txt 2>&1
EXIT_CODE=$?
END_MS=$(date +%s%3N)

INFERENCE_MS=$((END_MS - START_MS))

if [ $EXIT_CODE -ne 0 ]; then
  STDERR=$(cat /tmp/wasmedge-inference-result.txt)
  echo "TFLite inference failed: $STDERR"
  exit 1
fi

if [ $INFERENCE_MS -gt $MAX_INFERENCE_MS ]; then
  echo "TFLite inference too slow: ${INFERENCE_MS}ms > ${MAX_INFERENCE_MS}ms threshold"
  exit 1
fi

echo "TFLite inference OK: ${INFERENCE_MS}ms"
curl -s "$HEARTBEAT_URL"

If your inference pipeline uses a known-good test image and a stable model, the latency variance across runs reflects hardware state — GPU/NPU availability, thermal throttling, and memory bandwidth. A sudden latency increase without model changes indicates a hardware health issue, not a software bug.

Run this check every 15 minutes on edge nodes that serve inference requests. For nodes where inference is user-triggered (not background), run the check every 5 minutes during business hours via a time-windowed cron expression:

# Run every 5 minutes during business hours (UTC)
*/5 8-18 * * 1-5 /usr/local/bin/wasmedge-tflite-check.sh
# Run every 15 minutes outside business hours
*/15 * * * * /usr/local/bin/wasmedge-tflite-check.sh 2>/dev/null || true

Step 5: Verify Container Integration Status

WasmEdge integrates with containerd via containerd-shim-wasmedge-v1 and with crun/youki via the WasmEdge OCI runtime integration. In containerized deployments, Kubernetes pods or Docker containers run WASM modules as if they were Linux containers. When the containerd shim crashes, when the WasmEdge OCI runtime integration breaks after a containerd upgrade, or when the crun integration loses its WasmEdge library reference, WASM container starts fail with cryptic errors that look like generic container failures.

Monitor the containerd shim availability:

#!/bin/bash
# /usr/local/bin/wasmedge-container-check.sh

HEARTBEAT_URL="https://vigilmon.online/heartbeat/mno345"

# Check containerd shim binary is present
SHIM_PATHS=(
  "/usr/local/bin/containerd-shim-wasmedge-v1"
  "/usr/bin/containerd-shim-wasmedge-v1"
)

SHIM_FOUND=0
for shim_path in "${SHIM_PATHS[@]}"; do
  if [ -x "$shim_path" ]; then
    SHIM_FOUND=1
    SHIM_PATH="$shim_path"
    break
  fi
done

if [ $SHIM_FOUND -eq 0 ]; then
  echo "containerd-shim-wasmedge-v1 not found"
  exit 1
fi

# Verify containerd knows about the WasmEdge runtime
if command -v ctr &>/dev/null; then
  if ! sudo ctr plugins ls 2>/dev/null | grep -q "io.containerd.runtime.v2.task"; then
    echo "containerd runtime plugin not responding"
    exit 1
  fi
fi

echo "WasmEdge container integration OK: $SHIM_PATH"
curl -s "$HEARTBEAT_URL"

For Kubernetes deployments using WasmEdge via the RuntimeClass feature, add a Vigilmon HTTP monitor for the kubelet's node status endpoint to verify the node reports Ready with the WasmEdge runtime class available.

Putting It All Together

With these five monitors active, your Vigilmon dashboard covers every critical layer of a WasmEdge deployment:

| Monitor | Type | Check Interval | Alert On | |---------|------|----------------|----------| | Runtime health | Cron heartbeat | 2 min | Missing ping | | Function execution latency | Cron heartbeat | 5 min | Latency > 200ms | | Plugin health | Cron heartbeat | 10 min | Missing or broken plugin | | TFLite inference latency | Cron heartbeat | 15 min | Latency > 500ms | | Container integration | Cron heartbeat | 10 min | Shim missing or broken |

The most critical monitor to set up first is runtime health — a broken WasmEdge installation fails all functions silently. The second priority is plugin health, because plugin failures are the most common production issue after system updates and the hardest to detect without external monitoring.

WasmEdge's design goal is running WASM modules with near-native performance at the edge, but that performance guarantee only holds when all the layers below it are healthy — the runtime, the plugins, the AI backends, and the container integration. External monitoring with Vigilmon is the only way to catch degradation in any of those layers before your edge functions start failing user requests.

Sign up for a free Vigilmon account and add your first WasmEdge heartbeat monitor in under two minutes.

Monitor your app with Vigilmon

Free plan — 5 monitors, no credit card required. Up and running in 60 seconds.

Start free →
← Back to all articles