Using AWS X-Ray to Monitor a Node.js App
The course is part of these learning paths
AWS X-Ray makes it possible for you to monitor, trace and visualize activity across multiple application touchpoints.
In this course we will:
- Introduce the AWS X-Ray service and the functionality that it provides.
- Explain the functions of the AWS X-Ray service and how to use AWS X-Ray with other AWS services.
- Demonstrate how to use the AWS X-Ray Console - highlighting key areas such as the Service Map and Tracing windows
- Demonstrate how to implement a Docker-based Node.js application using the AWS X-ray SDK.
This is an intermediate-level course aimed at AWS professionals looking to learn how to use this important new AWS service in real-world deployments.
The demo/build files for this course are available here.
Before we finish, let's do a quick review of what we have been through. We learned the core aspects of application instrumentation and telemetry. We gained an understanding of core AWS X-Ray concepts. We learned about AWS X-Ray as a fully managed service by Amazon, providing visualization and tracing tools. We implemented a locally hosted Dockerised microservices architecture. We reviewed how to leverage the AWS X-Ray SDK within our application. And finally, we learned how to monitor and debug our microservices architecture using the AWS X-Ray console. As a reminder, the X-Ray instrumented source code for the calculator application as presented within this course is available from Cloud Academy's public GitHub repo. Thank you for your participation! I do hope you have enjoyed this course on AWS X-Ray. Feel free to connect with Jeremy Cook with regard to any questions at email@example.com. Alternatively, you can always get in touch with us here at Cloud Academy using the community forum where one of our cloud experts will reply to your question.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, GCP, and Kubernetes (CKA, CKAD, CKS).