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#