Monitoring Edge Function resource usage

了解如何跟踪你的 Edge Function 性能并找出潜在的资源问题。

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

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🌐 Accessing metrics

通过仪表板追踪你功能的表现：

🌐 Track your function's performance through the dashboard:

🌐 Key metrics to monitor

🌐 CPU usage

高 CPU 使用率表示你的函数正在进行高强度计算。可以考虑：

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

🌐 Memory usage

内存峰值可能会导致功能故障。注意：

🌐 Memory spikes can cause function failures. Watch for:

🌐 Execution time

长时间的执行可能会导致超时。注意监控以下内容：

🌐 Long execution times can lead to timeouts. Monitor for:

🌐 Resource limits

与传统服务器相比，边缘函数的资源有限。优化重点：

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

🌐 Best practices

🌐 Use streaming for large data

不要把整个文件加载到内存里，而是要流式传输数据：

🌐 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

把大操作分成更小的批次：

🌐 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

存储昂贵计算的结果以避免重复计算：

🌐 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