Monitoring Edge Function resource usage

Last edited: 2/6/2026

Learn how to track your Edge Function's performance and identify potential resource issues.

Accessing metrics

Track your function's performance through the dashboard:

  1. Navigate to Edge Functions > [Your Function] > Metrics
  2. Review CPU, memory, and execution time charts
  3. Identify potential problems in resource consumption

Key metrics to monitor

CPU usage

High CPU usage indicates your function is performing intensive computations. Consider:

  • Optimizing algorithms
  • Caching computed results
  • Moving heavy processing to background jobs

Memory usage

Memory spikes can cause function failures. Watch for:

  • Large datasets loaded into memory
  • Accumulated objects that aren't garbage collected
  • Large dependency bundles

Execution time

Long execution times can lead to timeouts. Monitor for:

  • Slow external API calls
  • Inefficient database queries
  • Complex computational operations

Resource limits

Edge Functions have limited resources compared to traditional servers. Optimize for:

  • Memory efficiency: Avoid loading large datasets into memory
  • CPU optimization: Minimize complex computations
  • Execution time: Keep functions under 60 seconds

Best practices

Use streaming for large data

Instead of loading entire files into memory, stream data:

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// Stream responses instead of buffering
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return new Response(readableStream, {
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  headers: { 'Content-Type': 'application/json' },
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})

Process data in chunks

Break large operations into smaller batches:

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for (const batch of dataBatches) {
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  await processBatch(batch)
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}

Cache expensive operations

Store results of expensive computations to avoid recalculating:

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const cachedResult = await cache.get(key)
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if (cachedResult) {
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  return cachedResult
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}

Additional resources