Our customers used AWS X-Ray mainly because they were already utilizing other AWS products. The primary purpose of using AWS X-Ray was to observe code, product, and system performance. However, if we were seeking a top-tier solution, we would often opt for third-party products like AppDynamics, Instana, or Datadog.
Lead Software Engineer at a tech services company with 1,001-5,000 employees
Real User
Top 20
2025-04-08T09:27:26Z
Apr 8, 2025
I have been using a variety of AWS ( /products/amazon-aws-reviews ) services, such as AWS ( /products/amazon-aws-reviews ) EC2 ( /products/amazon-ec2-reviews ), Lambda, S3 ( /products/amazon-s3-reviews ), Glue jobs, Route 53 ( /products/amazon-route-53-reviews ), CloudFront, and SQS. I use AWS X-Ray ( /products/aws-x-ray-reviews ) for distributed tracing, collecting trace metrics from applications and AWS services.
Solutions Architect/ Analyst at a tech services company with 11-50 employees
Real User
Top 10
2025-02-12T19:34:41Z
Feb 12, 2025
I have two use cases with my customers. One involves using AWS Fargate, and the other involves an application running on WordPress. The WordPress application was very slow, and we used AWS X-Ray to understand the main problem. X-Ray helped us identify issues with our EFS, allowing us to adjust throughput and solve the problem.
I used X-Ray for the performance of my application. I have used X-Ray to check the performance of my applications to identify bottlenecks or lagging issues. I just use the tracing marks in X-Ray to address any latency.
We integrate solutions based on customer requirements. Therefore, the primary use case is to understand the system's behavior after several rounds of developers going into the team and building the system. Also, the big picture is sometimes missing when the system goes up. So, the ServiceNet and the segmentation, ordering, and timeline views on the segments, especially on the link traces, help understand how the system and microservices are interconnected. The second use case is to identify bottlenecks in terms of stability and performance and how long certain data lives in terms of response time and duration. These are important aspects on our side.
It's basically like a cloud stack. You can trace your entire HTTP request. Once you have submitted any request, it will be addressed as a 500 Error or 401 Error, or if there is any exception happening when this request, and how much time will take. X-Ray can trace all the information about the request and response. Wherever we require any API for any logging purpose, we use AWS X-Ray in our code.
Senior Java Developer at a tech services company with 1,001-5,000 employees
Real User
2021-02-12T22:35:35Z
Feb 12, 2021
In our company, we work with microservices. We use X-Ray to trace the flow of our endpoints and our requests. That's basically the only use case for us.
AWS X-Ray is a powerful debugging and performance analysis tool offered by Amazon Web Services. It allows developers to trace requests made to their applications and identify bottlenecks and issues.
With X-Ray, developers can visualize the entire request flow and pinpoint the exact location where errors occur. It provides detailed insights into the performance of individual components and helps optimize the overall application performance.
X-Ray integrates seamlessly with other...
Our customers used AWS X-Ray mainly because they were already utilizing other AWS products. The primary purpose of using AWS X-Ray was to observe code, product, and system performance. However, if we were seeking a top-tier solution, we would often opt for third-party products like AppDynamics, Instana, or Datadog.
I have been using a variety of AWS ( /products/amazon-aws-reviews ) services, such as AWS ( /products/amazon-aws-reviews ) EC2 ( /products/amazon-ec2-reviews ), Lambda, S3 ( /products/amazon-s3-reviews ), Glue jobs, Route 53 ( /products/amazon-route-53-reviews ), CloudFront, and SQS. I use AWS X-Ray ( /products/aws-x-ray-reviews ) for distributed tracing, collecting trace metrics from applications and AWS services.
I have two use cases with my customers. One involves using AWS Fargate, and the other involves an application running on WordPress. The WordPress application was very slow, and we used AWS X-Ray to understand the main problem. X-Ray helped us identify issues with our EFS, allowing us to adjust throughput and solve the problem.
I used X-Ray for the performance of my application. I have used X-Ray to check the performance of my applications to identify bottlenecks or lagging issues. I just use the tracing marks in X-Ray to address any latency.
The solution is used to trace dashboard databases and also as a new layer for Codesphere.
We integrate solutions based on customer requirements. Therefore, the primary use case is to understand the system's behavior after several rounds of developers going into the team and building the system. Also, the big picture is sometimes missing when the system goes up. So, the ServiceNet and the segmentation, ordering, and timeline views on the segments, especially on the link traces, help understand how the system and microservices are interconnected. The second use case is to identify bottlenecks in terms of stability and performance and how long certain data lives in terms of response time and duration. These are important aspects on our side.
It provides a telemetry solution, so we track activity within our applications in our implementation at Amazon.
It's basically like a cloud stack. You can trace your entire HTTP request. Once you have submitted any request, it will be addressed as a 500 Error or 401 Error, or if there is any exception happening when this request, and how much time will take. X-Ray can trace all the information about the request and response. Wherever we require any API for any logging purpose, we use AWS X-Ray in our code.
In our company, we work with microservices. We use X-Ray to trace the flow of our endpoints and our requests. That's basically the only use case for us.