I am currently trying to execute a function in AWS Lambda that launches a headless Chromium browser via Puppeteer. To optimize deployment and avoid uploading the entire browser, I use chrome-aws-lambda. My Lambda function is deployed using Serverless and interacts with a DynamoDB table for various tasks.
The code snippet below illustrates a function that checks for advertising presence in a YouTube video:
async function detectAd(page, selector) {
await wait(10000);
try {
const adCheck = await page.evaluate((selector) => {
const adElement = document.querySelector(selector);
const adCount = adElement.children.length;
return adCount > 0;
}, selector);
return adCheck;
} catch (error) {
return "No ad found";
}
}
This function is executed multiple times, waiting for 10 seconds each time as seen in the wait function defined below:
function wait(milliseconds) {
return new Promise((resolve) => {
setTimeout(resolve, milliseconds);
});
}
However, after executing this function roughly four times (approximately 40 seconds into the video), I receive the following error in the Lambda console:
Invoke API action failed with: Network Error
There are no additional error messages in my logs; it simply halts without further information. Would anyone have insights into what might be triggering this issue?
It seems you're facing a common challenge when running headless browsers in AWS Lambda environments. Here are a few additional considerations and enhancements you might try to resolve the network error:
-
Concurrency Management: Ensure that concurrent executions are not overwhelming your Lambda function. By default, Lambda limits the number of concurrent executions, and if exceeded, it might result in network errors. Try limiting the concurrency setting in your AWS Lambda configuration or staggering your function calls.
-
Network Configuration: If your Lambda function requires VPC access, ensure it is properly configured. A misconfiguration in subnet or security group can lead to network issues. Double-check that all necessary outbound and inbound traffic rules are set correctly.
-
Use Chunks: Instead of treating a video as a whole, consider breaking the process into smaller chunks or segments. Analyze small parts sequentially to reduce the overall processing time and avoid hitting resource limits.
-
Optimized Ad Detection: Reassess how frequently the ad detection function runs. Since you're using a 10-second wait, try reducing unnecessary iterations by predicting intervals or only running it during specific sections known for interruptions.
-
Lambda Layers: Ensure you're using the latest version of
chrome-aws-lambda and puppeteer-core. Lambda Layers can be an efficient way to manage dependencies, especially in preventing package size issues.
-
Debug Connections: Try logging network requests/responses to better understand where the breakdown might occur. Enhance your logging with
console.log() to capture network activities, particularly focusing on any discrepancies when the error occurs.
While you've already received valuable input from others, consider these additional steps to further refine your execution strategy. Remember to closely monitor your Lambda metrics and AWS CloudWatch Logs for deeper insights.
Hi DancingFox,
Given the specifics of your issue, it seems that the network error in your AWS Lambda could be due to exceeding the Lambda function's time or resource limits, particularly due to multiple evaluations with a headless browser. Here are some steps to optimize and possibly resolve the problem:
- Optimize Execution Time: Ensure your function execution time is under Lambda's default limits. You might try shorter wait times or consider if all checks are necessary within a single execution.
- Check Timeout Settings: Increase your Lambda timeout set in the Serverless configuration. Go to your Serverless configuration file and update the timeout setting.
functions:
myFunction:
handler: handler.myFunction
timeout: 60 # set to a higher value like 60 seconds if needed
- Investigate Resource Allocation: Consider increasing allocated memory and CPU power. AWS Lambda adjusts CPU power relative to memory size, which can sometimes alleviate performance bottlenecks.
functions:
myFunction:
handler: handler.myFunction
memorySize: 1024 # or higher if needed
- Review Network Access and Permissions: Ensure that your Lambda function has proper network permissions, especially if interacting with DynamoDB or external networks.
- Logs and Error Handling: Enhance your functions with better error handling and logging to get more insights. For instance, use
console.error(err) inside your catch block to check for additional error messages.
Try implementing these suggestions to see if they help alleviate your issue. If the problem persists, consider checking AWS CloudWatch for more detailed logs or enabling VPC if required by your function's network access pattern.
Best regards,
David
Hi DancingFox,
It looks like the "Network Error" might be tied to Lambda execution limits or network configuration. Here are some focused tips:
- Reduce Execution Time: Check if all wait periods are essential. You could shorten wait times or limit checks within the function.
- Adjust Timeouts: Ensure your Lambda's timeout setting accommodates the entire function's execution length.
functions:
myFunction:
handler: handler.myFunction
timeout: 60 # Increase if necessary
- Resource Adjustment: Consider bumping up the allocated memory as more memory increases CPU power, which might help.
functions:
myFunction:
handler: handler.myFunction
memorySize: 1024 # Use a higher value if needed
- Network Configurations: Ensure your Lambda has the correct permissions/roles and is correctly set up if it's accessing resources like DynamoDB.
- Enhanced Logging: Add
console.error(error) in your catch blocks for more detailed error insights.
Try these tweaks and monitor your AWS CloudWatch logs for further hints on the issue.
Hi DancingFox,
The network error you're encountering in your AWS Lambda function could be due to execution limits or inefficient networking configurations, especially when utilizing headless browsers like Puppeteer. To address this problem effectively, consider the following practical steps:
- Efficient Execution: Since your function waits 10 seconds each iteration, ensure each wait is necessary. Reducing unnecessary wait times can help keep execution within Lambda's limits.
- Increase Timeout: Check your AWS Lambda timeout settings. If the execution frequently exceeds this limit, consider increasing it. This adjustment can be made in your Serverless configuration file:
functions:
myFunction:
handler: handler.myFunction
timeout: 60 # or higher, if needed
- Optimize Resources: Enhancing memory and CPU allocation might alleviate restrictions impacting performance. AWS Lambda scales CPU power with increased memory settings:
functions:
myFunction:
handler: handler.myFunction
memorySize: 1024 # Higher values may be beneficial
- Verify Network Configurations: Ensure your VPC, subnet, and security group settings do not restrict necessary network traffic. Adequate permissions for accessing DynamoDB and other external resources are critical.
- Logging for Insights: Implement detailed logging to capture network activities and errors, using
console.error(error) for better diagnostics. This improves understanding of where bottlenecks or errors happen.
Applying these strategies should help resolve the "Network Error" and optimize your Lambda function's performance. Monitoring in AWS CloudWatch will provide additional specifics if issues persist.
Best,
David