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...
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.