AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. Learn how to use X-Ray to analyze both applications in development and in production, from simple three-tier applications to complex microservices applications consisting of thousands of services.

1. ©2017, Amazon Web Services, Inc. or its affiliates. All rights reserved
Introduction to AWS X-Ray
Overview and Use Cases
Chris Munns – Senior Developer Advocate - Serverless

2. About me:
Chris Munns - munns@amazon.com,@chrismunns
– Senior Developer Advocate - Serverless
– NewYorker
– Previously:
• Business Development Manager – DevOps, July ’15 - Feb ‘17
• AWS Solutions Architect Nov, 2011- Dec 2014
• Formerly on operations teams @Etsy and @Meetup
• Little time at a hedge fund, Xerox and a few other startups
– Rochester Institute of Technology: Applied Networking and
Systems Administration ’05
– Internet infrastructure geek

3. Agenda
• Overview
• Concepts
• API
• Use cases
• Getting started
• Demo
• Q & A

4. Debugging applications

5. Development vs. production
Traditional debugging involves:
• A development environment
• Search through logs for clues to reproduce the issue
• Set breakpoints in code to stop execution, and inspect variables and call stack
• Add additional log statements as necessary and redeploy application
• Repeat until the issue is fixed
Traditional process of debugging doesn’t scale well to production
applications or those built using a service-oriented, microservice, or
serverless architecture
It’s tedious, repetitive, and time consuming

6. Monolithic vs. service-oriented applications
Applications traditionally developed using a monolithic architecture
Move to service oriented (microservices) architecture to overcome the
drawbacks of a monolithic application architecture
But microservices come with their own set of challenges
Benefits:
• Simple to develop
• Simple to test and debug
• Simple to deploy
• Simple to scale
Drawbacks:
• Hard to iterate fast
• Hard to scale efficiently
• CI/CD time consuming and difficult
• Reliability challenges — a problem
with a single component can take
down the whole app

7. Challenges
Deploying and managing service-oriented applications is more work
compared to monolithic applications
Services such as AWS Lambda, Amazon EC2 Container Service, AWS
Elastic Beanstalk, AWS CloudFormation, etc. make it easier to deploy
and manage applications consisting of hundreds of services
Still hard to debug application issues in production applications due
to:
• Cross-service interactions
• Varying log formats across services
• Collecting, aggregating, and collating logs from services

8. Solution
AWS X-Ray makes it easy to:
• Identify performance bottlenecks and errors
• Pinpoint issues to specific service(s) in your application
• Identify impact of issues on users of the application
• Visualize the service call graph of your application

9. How does X-Ray help?

10. X-Ray service

11. X-Ray SDK
Available for Java, .NET, and Node.js
Adds filters to automatically captures metadata for calls to:
• AWS services using the AWS SDK
• Non-AWS services over HTTP and HTTPS
• Databases (MySQL, PostgreSQL, and Amazon DynamoDB)
• Queues (Amazon SQS)
Enables you to get started quickly without having to manually
instrument your application code to log metadata about requests

12. X-Ray daemon
• Receives data from the SDK over UDP and acts as a local buffer.
Data is flushed to the backend every second or when the local
buffer fills.
• Available for Amazon Linux AMI, RHEL, Ubuntu, OS X, and
Windows

13. Concepts

14. X-Ray Concepts
Trace End-to-end data related a single request across services
Segments Portions of the trace that correspond to a single service
Sub-segments Remote call or local compute sections within a service
Annotations Business data that can be used to filter traces
Metadata Business data that can be added to the trace but not used
for filtering traces
Errors Normalized error message and stack trace

15. Sampling configuration
• {
• "rules": {
• "move": {
• "id": 1,
• "service_name": "*",
• "http_method": "*",
• "url_path": "/api/move/*",
• "fixed_target": 0,
• "rate": 0.05
• },
• "base": {
• "id": 2,
• "service_name": "*",
• "http_method": "*",
• "url_path": "*",
• "fixed_target": 1,
• "rate": 0.1
• }
• }
• }
This example defines two rules.
The first rule applies a five-percent sampling rate
with no minimum number of requests to trace to
requests with paths under /api/move
The second overrides the default sampling rule
with a rule that traces the first request each
second and 10 percent of additional requests.

16. APIs

17. X-Ray API
• X-Ray provides a set of APIs to enable you to send, filter, and
retrieve trace data
• You can send trace data directly to the service without having to
use our SDKs (i.e. you can write your own SDKs for languages not
currently supported)
• Raw trace data is available using batch get APIs
• You can build your own data analysis applications on top of the
data collected by X-Ray

18. X-Ray API
PutTraceSegments Uploads segment documents to AWS X-Ray
BatchGetTraces Retrieves a list of traces specified by ID
GetServiceGraph Retrieves a document that describes services in
your application and their connections
GetTraceSummaries Retrieves IDs and metadata for traces available for a
specified time frame using an optional filter

19. Segment document
• Minimal example
• {
• "name" : "example.com",
• "id" : "70de5b6f19ff9a0a",
• "start_time" : 1.478293361271E9,
• "trace_id" : "1-581cf771-a006649127e371903a2de979",
• "end_time" : 1.478293361449E9
• }
• Example showing an in-progress segment
• {
• "name" : "example.com",
• "id" : "70de5b6f19ff9a0b",
• "start_time" : 1.478293361271E9,
• "trace_id" : "1-581cf771-a006649127e371903a2de979",
• “in_progress”: true
• }

20. Use cases

21. Visualize service call graph

22. Identify impact

23. Identify impact

24. Identify performance bottlenecks

25. Identify performance bottlenecks

26. Identify performance bottlenecks

27. Identify performance bottlenecks

28. Pinpoint issues

29. Pinpoint issues

30. Pinpoint issues

31. Getting started

32. Agent installation (Amazon EC2 Linux)

33. Agent Installation (Amazon EC2 Windows)

34. Agent installation (Amazon ECS)

35. //Add aws-xray-sdk package to package.json
var XRay = require('aws-xray-sdk');
var AWS = captureAWS(require('aws-sdk'));
…
XRay.config([XRay.plugins.EC2]);
XRay.captureHTTPs(http);
XRay.setDefaultName('myfrontend-dev');
…
app.use(XRay.express.openSegment());
app.get('/', function(req, res) {
…
});
…
app.use(XRay.express.closeSegment());
Application instrumentation (Node.js)

36. Demo

37. Pricing

38. X-Ray pricing
Free during the preview.
After that:
Free tier
• The first 100,000 traces recorded per month are free
• The first 1,000,000 traces retrieved or scanned per month are free
Additional charges
• Beyond the free tier, traces recorded cost $5.00 per million per month
• Beyond the free tier, traces retrieved or scanned cost $0.50 per million
per month

39. Available today!
• The AWS X-Ray service is available in preview today.
• Go to https://aws.amazon.com/xray to sign up for the preview.
• Documentation: http://docs.aws.amazon.com/xray/latest/devguide/aws-xray.html
• .NET Sample: https://github.com/awslabs/aws-xray-dotnet-webapp
• Java Sample: https://github.com/awslabs/eb-java-scorekeep/tree/xray
• Node.js Sample: https://github.com/awslabs/eb-node-express-sample/tree/xray

40. Chris Munns
munns@amazon.com
@chrismunnshttps://www.flickr.com/photos/theredproject/3302110152/

41. ?
https://secure.flickr.com/photos/dullhunk/202872717/