Gradual Increase in Execution Time for Azure Function Retrieving Data from External APIs

Question

Hello,

I’m experiencing an issue with an Azure Function that’s been running smoothly for some time. This function is designed to retrieve a substantial amount of data from external APIs. Initially, the execution time is within expected limits, but as the function continues to run throughout the day, the execution time gradually increases, eventually becoming significantly longer. As first run may take 4 min, then the execution time starts to increase by 1 or 2 min each time.

Interestingly, when I redeploy the Azure Function without making any changes, the performance resets, and the execution time returns to normal. However, this improvement is temporary, and the execution time starts to increase again as the function continues to run.

I've monitored CPU and memory usage, and both appear to be stable, so I don’t suspect a memory leak or CPU resource issue. Additionally, I’ve checked for potential issues with open file descriptors and resource management, but these seem to be within normal ranges.

Could you provide guidance on what might be causing this gradual increase in execution time? Are there any known issues with long-running Azure Functions that might affect performance in this way, or any recommended practices for maintaining consistent performance over time?

Best regards,

Sameh

Answer 1

Hello @Sameh Tawfik (External - PwC AB (SE))

This issue can be caused by a number of factors, including resource utilization, network latency, and API throttling.

One possible cause of this issue is resource utilization. Even if CPU and memory usage appear to be stable, it's possible that your function is consuming resources in a way that is not immediately apparent.

One way to address this is to monitor resource utilization over time to see if there are any patterns or trends that might indicate a problem. You can also try scaling up your function to see if this improves performance.

Another possible cause of this issue is network latency. If your function is making a large number of requests to external APIs, it's possible that network latency is causing delays in data retrieval.

To address this, you can try optimizing your function's network settings, such as increasing the connection timeout or adjusting the maximum number of concurrent connections.

Finally, API throttling can also cause gradual increases in execution time. If the external APIs you are accessing have rate limits or other throttling mechanisms in place, it's possible that your function is being throttled over time.

To address this, you can try adjusting the rate at which your function makes requests to the API, or implementing a caching mechanism to reduce the number of requests your function needs to make.

In general, it's a good practice to monitor your function's performance over time and make adjustments as needed to maintain consistent performance. This can include scaling up or down as needed, optimizing network settings, and implementing caching or other performance-enhancing mechanisms.

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