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Conclusion
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Difficulty
Advanced
Duration
39m
Students
6805
Ratings
4.5/5
Description

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.

Transcript

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 support@cloudacademy.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.

About the Author
Students
142723
Labs
69
Courses
109
Learning Paths
209

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, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).