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WIFI: awsDevDay | PASS: CodeHappy
U P N E X T :
Distributed Serverless Stack
Tracing and Monitoring
T H A N K S T O O U R F R I E N D S A T :
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Kashif Imran, Sr. Solutions Architect AWS
09/12/2017
Distributed Serverless Stack
Tracing and Monitoring
What to expect from the session
• Concepts
• Overview
• Use cases
• Demo
• API
• Getting started
AWS Lambda Concepts
Serverless means…
No servers to provision
or manage
Scales with usage
Never pay for idle Availability and fault
tolerance built in
Never pay for Idle
EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE
Common Serverless Use Cases
Web
Applications
• Static websites
• Complex web
apps
• Packages for
Flask and
Express
Data
Processing
• Real time
• MapReduce
• Batch
Chatbots
• Powering
chatbot logic
Backends
• Apps &
services
• Mobile
• IoT
</></>
Amazon
Alexa
• Powering
voice-enabled
apps
• Alexa Skills
Kit
Autonomous
IT
• Policy engines
• Extending
AWS services
• Infrastructure
management
Monolithic
Monolithic vs. Service Oriented Architecture
Service Oriented Architecture
Drawbacks of Monolithic Architecture
Hard to Iterate Fast CI/CD Time ConsumingHard to scale Efficiently
Reliability Challenges
Benefits of Service Oriented Architecture
Increased Agility Easy to Scale Improved Innovation
Reduced Human Errors
AWS X-Ray Concepts
X-Ray Key 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
Sampling Percentage of requests to your application to capture as
traces
How X-Ray works
Debugging applications
Traditional Debugging
Developer Local Test
Developer
Add
Breakpoints
Add Log
Statements
The traditional process of debugging doesn’t scale well for
production applications or those built using a service-
oriented, microservice, or serverless architecture
It’s tedious, repetitive, and time consuming.
Debugging applications with X-Ray
Identify Performance
Bottlenecks
How does AWS X-Ray help?
Pinpoint Specific
Service Issues
Identify Errors Identify Impact to
Users
Use cases
Visualize service call graph
Identify impact
Identify performance bottlenecks
Identify performance bottlenecks
Identify performance bottlenecks
Pinpoint issues
Pinpoint issues
Pinpoint issues
How does AWS X-Ray work?
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
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.
Can be run anywhere as long as AWS credentials are provided
(e.g.: EC2, ECS, on premise, developer machine, etc.)
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.
AWS X-Ray API
X-Ray API
Raw trace data is available using batch get APIs.
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. (e.g. you can write your own SDKs for languages/frameworks not currently supported)
You can build your own data analysis applications on top of the data
collected by X-Ray.
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
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
}
Getting started
Agent installation (Amazon Linux)
#!/bin/bash
curl https://s3.dualstack.us-east-1.amazonaws.com/aws-xray-assets.us-east-1/xray-daemon/aws-xray-
daemon-1.x.rpm -o /home/ec2-user/xray.rpm
yum install -y /home/ec2-user/xray.rpm
Agent Installation (Windows)
Agent installation (Amazon ECS)
Application instrumentation (Node.js)
Example pseudo code:
Demo
Pricing
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
Available Today!
The AWS X-Ray service is available today.
Go to https://aws.amazon.com/xray to get started.
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
Thank You!
Don’t Forget Evaluations!

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Distributed Serverless Stack Tracing and Monitoring - DevDay Austin 2017

  • 1.
  • 2. WIFI: awsDevDay | PASS: CodeHappy U P N E X T : Distributed Serverless Stack Tracing and Monitoring
  • 3. T H A N K S T O O U R F R I E N D S A T :
  • 4. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Kashif Imran, Sr. Solutions Architect AWS 09/12/2017 Distributed Serverless Stack Tracing and Monitoring
  • 5. What to expect from the session • Concepts • Overview • Use cases • Demo • API • Getting started
  • 7. Serverless means… No servers to provision or manage Scales with usage Never pay for idle Availability and fault tolerance built in
  • 8. Never pay for Idle EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE
  • 9. Common Serverless Use Cases Web Applications • Static websites • Complex web apps • Packages for Flask and Express Data Processing • Real time • MapReduce • Batch Chatbots • Powering chatbot logic Backends • Apps & services • Mobile • IoT </></> Amazon Alexa • Powering voice-enabled apps • Alexa Skills Kit Autonomous IT • Policy engines • Extending AWS services • Infrastructure management
  • 10. Monolithic Monolithic vs. Service Oriented Architecture Service Oriented Architecture
  • 11. Drawbacks of Monolithic Architecture Hard to Iterate Fast CI/CD Time ConsumingHard to scale Efficiently Reliability Challenges
  • 12. Benefits of Service Oriented Architecture Increased Agility Easy to Scale Improved Innovation Reduced Human Errors
  • 14. X-Ray Key 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 Sampling Percentage of requests to your application to capture as traces
  • 17. Traditional Debugging Developer Local Test Developer Add Breakpoints Add Log Statements
  • 18. The traditional process of debugging doesn’t scale well for production applications or those built using a service- oriented, microservice, or serverless architecture It’s tedious, repetitive, and time consuming.
  • 20. Identify Performance Bottlenecks How does AWS X-Ray help? Pinpoint Specific Service Issues Identify Errors Identify Impact to Users
  • 30. How does AWS X-Ray work?
  • 31. 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
  • 32. 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. Can be run anywhere as long as AWS credentials are provided (e.g.: EC2, ECS, on premise, developer machine, etc.)
  • 33. 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.
  • 35. X-Ray API Raw trace data is available using batch get APIs. 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. (e.g. you can write your own SDKs for languages/frameworks not currently supported) You can build your own data analysis applications on top of the data collected by X-Ray.
  • 36. 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
  • 37. 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 }
  • 39. Agent installation (Amazon Linux) #!/bin/bash curl https://s3.dualstack.us-east-1.amazonaws.com/aws-xray-assets.us-east-1/xray-daemon/aws-xray- daemon-1.x.rpm -o /home/ec2-user/xray.rpm yum install -y /home/ec2-user/xray.rpm
  • 43. Demo
  • 45. 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
  • 46. Available Today! The AWS X-Ray service is available today. Go to https://aws.amazon.com/xray to get started. 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