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Hello Bharath Ram Chandrasekar,
Thank you for reaching out to us.
You preferred the solution that involves creating an Amazon OpenSearch cluster, writing AWS Lambda functions to query the ES cluster, creating an Amazon CloudFront distribution, and using Lambda@Edge for caching data points at edge locations for a 15-minute duration.
Based on the given explanation, this solution is possible as it offers several advantages, such as efficient querying with OpenSearch and global low-latency access with CloudFront and Lambda@Edge. However, it’s important to consider the default burst concurrency limits of AWS Lambda, which range between 500 to 3,000 requests per second depending on the region. During peak traffic times, these limits might prevent Lambda functions from quickly scaling to meet the demand, possibly affecting response times.
Hence, the correct answer is: Using Amazon EFS with a fleet of Auto Scaling Amazon EC2 instances behind an Elastic Load Balancer (ELB). This setup ensures high concurrency and can handle significant traffic spikes, with CloudFront caching helping to reduce latency.
We would appreciate your perspective on this matter. Could you please explain why you believe the Amazon OpenSearch and Lambda@Edge solution is more viable, given the potential scaling issues with Lambda functions during peak traffic?
Thank you once again.
Regards,
JR @ Tutorials Dojo
