CS计算机代考程序代写 python javascript database Java flex AWS cache AI Serverless Applications

Serverless Applications
AWS Lambda

Outline

• Overview of Serverless
• Serverless Architectures
• AWS Lambda Example Architecture
• Overview of Containers
• Container Architectures
• Where we go from here
• AWS Lambda + AWS API Gateway

Need for Virtual Machines

The Issue
l Deployment of server applications is getting complicated since software can

have many types of requirements.

The Solution
l Run each individual application on a separate virtual machine. (One on

NodeJS VM, one on PHP VM, one on Java VM)

Virtualization
Offers a hardware abstraction layer that can adjust to the specific CPU, memory, storage

and network needs of applications on a per server basis.

Virtual Machines are expensive

The Problems with Virtual machines
l Money – You need to predict the instance size you need. You are charged for

every CPU cycle, even when the system is “running its thumbs”
l Time – Many operations related to virtual machines are typically slow

The Solution
l Serverless Architectures
l Containers

Containers
Operating System Level virtualization, a lightweight approach to virtualization

that only provides the bare minimum that an application requires to run and
function as intended.

What is Serverless?

• Serverless architectures refer to applications that significantly depend on third
party-services (known as Backend as a Service or “Baas”) or on custom code
that’s run in ephemeral containers (Function as a Service or “FaaS”), the best
known vendor host of which currently is AWS Lambda. By using these ideas,
and by moving much behavior to the front end, such architectures remove the
need for the traditional ‘always on’ server system sitting behind an
application.

• “No server is easier to manage than no server” – Werner Vogels

Note: slides provided by Nate Slater, Senior Manager AWS Solutions Architecture, “State of Container and Serverless
Architectures”

Features of Serverless Architectures

• No compute resource to manage
• Provisioning and scaling handled by the service itself
• You write code and the execution environment is provided by the service
• Core functionality (e.g., database, authentication and authorization) is

provided by at-scale Web Services

The origins of “Functions-as-a-Service”

• AWS Lambda – Announced at re:Invent 2014. First web service of it’s kind
that completely abstracted the execution environment from the code

• API Gateway – Launched in mid-2015. Critical ingredient for building
service endpoints with Lambda.

• Combined with existing back-plane services like DynamoDB, Cloudformation,
and S3 and “serverless” development was born.

The FaaS Development Framework
Ecosystem

• Serverless Framework (serverless.com)
– Open-source framework for building serverless

applications with AWS, Azure, IBM Cloud,
GCP, Knative, Apache OpenWhisk, CloudFlare
Workers

– Supports Node.js, Python, and Java
– Free-tier: 100,000 transactions / mo

• Chalice
– Python based framework for microservice

development with AWS Lambda
• Apex

– A set of tools written in Go to manage
serverless deployments to AWS Lambda

• • Serverless Application Module (SAM)
– AWS framework that extends CloudFormation

(common language to describe and provision
infrastructure resources in the cloud)

FaaS – How Does it Work?

• You write a function and deploy it to the cloud service for execution.
• Example: node.js with AWS Lambda:

module.exports.handler = function(event, context, callback) {
console.log(“event: ” + JSON.stringify(event));

if ((!event.hasOwnProperty(“email”) ||
!event.hasOwnProperty(“restaurantId”)) || (!event.email ||
!event.restaurantId)) { callback(“[BadRequest] email and
restaurantId are required”);

return; }

}

BaaS – Backend-as-a-Service

• Data Stores
– NoSQL Databases
– BLOB Storage
– Cache (CDN)

• Analytics
– Query
– Search
– IoT (Internet of Things)
– Stream Processing

• AI
– Machine Learning
– Image Recognition
– Natural Language Processing/Understanding
– Speech to Text/Text to Speech

Serverless Architecture – Stream Analytics/IoT

Serverless Architecture – Microservices

AWS Lambda Example Architecture

• Search
• Location-Awareness
• Machine-learning powered recommendations
• NoSQL
• Microservices
• API Management
• Static website with CDN
• Not a single server to manage!

AWS Lambda Example Architecture (cont’d)

What are Containers?

• Virtualization at the OS level
• Based on Linux kernel features

– cgroups (control groups)
– namespaces

• Concept has been around for a while
– Solaris ”zones” – early form of containerization
– LXC – Early form of containerization on Linux

• Docker has brought containers mainstream

Containers – Key Features

• Lightweight
– All containers running on the same host share a single Linux kernel
– Container images don’t require a full OS install like a virtual machine image

• Portable
– Execution environment abstracts the underlying host from the container
– No dependency on a specific virtual machine technology
– Container images can be shared using GitHub-like repositories, such as Docker

Hub (hub.docker.com)

Docker

l Docker is a tool that allows developers, sys-admins etc. to easily deploy their
applications in a sandbox (called containers) to run on the host operating
system, i.e., Linux.

l Key Benefit : Allows users to package an application with all its
dependencies into a standardized unit for software development.

l Unlike virtual machines, Containers do not have the high overhead and
hence enable more efficient usage of the underlying system and resources.

l Allow extremely higher efficient sharing of resources
l Provides standard and minimizes software packaging
l Decouples software from underlying host w/ no hypervisor

Container Issues

l Security
l Less Flexibility in Operating Systems, Networking
l Management of Docker and Container in production is challenge

Docker Runtime Architecture

Docker – Platform Architecture

The Docker Ecosystem

Docker on macOS

• Install Docker Desktop on macOS:
https://docs.docker.com/docker-for-mac/install/
https://hub.docker.com/editions/community/docker-ce-desktop-mac
• macOS 10.15 or newer, Docker Desktop 4.2.0 (70708)
• 4GB RAM

Docker on Windows

• Install Docker Desktop for Windows
https://docs.docker.com/desktop/windows/install/
https://hub.docker.com/editions/community/docker-ce-desktop-windows
• Windows 10/11
• 4GB RAM

Container-Based Microservice Example

Sinatra is a lightweight web application library and domain-specific language that provides a faster and simpler alternative to Ruby
frameworks such as Ruby on Rails. See: https://github.com/sinatra/sinatra/

Serverless – Where we go from here

• Backend-as-a-Service
– AI

• Fraud detection
• Latent sematic analysis

– Geospatial
• Satellite imagery
• Hyper-Locality

– Analytics
• Query
• Search
• Stream Processing

– Database
• Graph

– HPC (High Performance Computing)

Serverless – Where we go from here (cont’d)

• Function-as-a-Service
– Polyglot language support (each function written in a different language)
– Stateful endpoints (Web Sockets)
– Remote Debugging
– Enhanced Monitoring
– Evolution of CI/CD Patterns (Continuous Integration / Continuous Depoyment)
– IDE’s
– See “Ten Attributes of Serverless Computing Platforms”:

Ten Attributes of Serverless Computing Platforms

Containers – Where we go from here

• Networking
– Overlay networks between containers running across separate hosts

• Stateful Containers
– Support for container architectures that read and write persistent data

• Monitoring and Logging
– Evolution of design patterns for capturing telemetry and log data from running

containers
• Debugging

– Attach to running containers and debug code
• Security

– Better isolation at the kernel level between containers running on the same host
– Secret/Key management – Transparently pass sensitive configuration

AWS Lambda

l Compute Service using Amazon’s infrastructure
l Code === function
l Supported – Java, Python and Node.js (i.e. JavaScript)
l Can say it to be Docker under the covers
l A system that uses Linux Containers
l Pay only for the compute time you use
l Triggered by events or called from HTTP
l It still has SERVERS, but we do not care about them
l Functions are unit of deployment and scaling
l No Machines, no Vms or containers visible in Programming Model
l Never pay for idle
l Auto-Scaling and Always Available, adapts to rate of incoming requests

Using AWS Lambda

• No Servers to Manage
• Continuous Scaling
• Subsecond metering
• Bring your own code
• Simple resource model
• Flexible Authorization and Use
• Stateless but you can connect to others to store state
• Authoring functions
• Makes it easy to

– Perform real time data processing
– Build scalable backend services
– Glue and choreograph systems

AWS Lambda – How It Works

AWS Lambda – How It Works (cont’d)

Amazon API Gateway

• Amazon API Gateway is a fully managed service that makes it easy for
developers to create, publish, maintain, monitor, and secure APIs at any scale.

• Creates a unified API front end for multiple microservices
• DDoS (Distributed Denial of Service) Protection and throttling for back end

systems
• Authenticate and authorize requests

Amazon API Gateway Call Flow

Amazon API Gateway Request Processing
Workflow

AWS Lambda Supported Event Sources

• Amazon S3
• Amazon DynamoDB
• Amazon Kinesis Streams
• Amazon Simple Notification Service
• Amazon Simple Email Service
• Amazon Cognito
• AWS CloudFormation
• Amazon CloudWatch Logs
• Amazon CloudWatch Events
• AWS CodeCommit
• Scheduled Events (powered by Amazon CloudWatch Events)’
• AWS Config
• Amazon Echo
• Amazon Lex
• Amazon API Gateway
See: https://docs.aws.amazon.com/lambda/latest/dg/lambda-services.html

Create a Simple Microservice using
Lambda and API Gateway

In this exercise you will use the Lambda console to create a Lambda function (MyLambdaMicroservice), and
an Amazon API Gateway endpoint to trigger that function. You will be able to call the endpoint with any
method (GET, POST, PATCH, etc.) to trigger your Lambda function. When the endpoint is called, the entire
request will be passed through to your Lambda function. Your function action will depend on the method you
call your endpoint with:

• DELETE: delete an item from a DynamoDB table
• GET: scan table and return all items
• POST: Create an item
• PUT: Update an item

AWS Lambda (cont’d)

Follow the steps in this section to
create a new Lambda function and
an API Gateway endpoint to trigger
it:

1. Sign into the AWS
Management Console and
open the AWS Lambda
Management Console under
Compute Lambda.

AWS Lambda (cont’d)

2. Choose Create function.

AWS Lambda (cont’d)

3. 3. Select Use a blueprint. On
the Blueprints page, choose
the microservice-http-
endpoint blueprint. You can
use the Filter to find it. Just
type “micro” and click enter.
Select the microservice-http-
endpoint hyperlink. Click
Configure.

AWS Lambda (cont’d)

4. In the Basic information section, do the
following:

a) Enter the function name
MyLambdaMicroservice in Name.

b) In Role name, enter a role name for
the new role that will be created, like
myLambdaRoleName.

5. The API Gateway trigger section will be
populated with an API Gateway trigger.
Select Create an API. Click Additional
settings. Select the REST API API type.
The default API name that will be created is
MyLambdaMicroservice-API (You can
change this name via the API name field if
you wish).

6. In the Deployment stage leave default. In
the Security field, select Open, as we will
be creating a publicly available REST API.

AWS Lambda (cont’d)

7. On the Lambda function code section,
do the following:

a) Review the preconfigured
Lambda function configuration
information, including:
• Runtime is Node.js

12.x

• Code authored in
JavaScript is provided.
The code performs
DynamoDB operations
based on the method
called and payload
provided.

8. Chose Create function.

AWS Lambda (cont’d)

9. The “Congratulations!” page is
displayed, showing the
Configuration > Designer tab.
Notice Code > index.js shows
export.handler.

AWS Lambda (cont’d)

10. Click the API Gateway. Notice
the API endpoint, the HTTP
REST service URL entry point.

AWS Lambda (cont’d)

11. To test our AWS Lambda REST
Service, select Database
DynamoDB from the Services
console.

AWS Lambda (cont’d)

12. Click Cretae Table. Create a
table named MyTable, with
LastName as Primary key.
Click Create. Click Create
item and add items with
FirstName, and enter a few
rows.

AWS Lambda (cont’d)

13. Back to the AWS
Lambda console. In this
step, we will use the
console to test the Lambda
function. That is, send an
HTTPS request to the API
method and have Amazon
API Gateway invoke your
Lambda function.

14. Select Functions from left
navigation. Click the
function name. The With
the
MyLambdaMicroService
function still open in the
console, choose the Select
a test event dropdown
and then choose
Configure test events.

AWS Lambda (cont’d)

13. In the dropdown “select a test
even”, select Configure test
events, select Event template
“Common – Hello World” (scroll
down to the end) and enter an
Event Name such as
MyEventName. Replace the
existing text with the following:

{
“httpMethod”: “GET”,
“queryStringParameters”: {
“TableName”: “MyTable”
}

}

14. After “copy / paste” the text
above choose Create.

AWS Lambda (cont’d)

15. Click Test. Check the Execution
result output, by clicking Details.
Notice the JSON returned with
the table content (GET scans or
“lists” the items in the table).

AWS Lambda (cont’d)

16. Close the Execution result. Click
the API Gateway. Click the
arrow next to API endpoint.
Notice the value of API
Endpoint URL. This is the entry
point of the API Gateway for your
new microservice.

AWS Lambda (cont’d)

16. You can now execute the REST API from your browser as in:
https://qug56qkck8.execute-api.us-east-1.amazonaws.com/default/MyNewFunction?TableName=MyTable

AWS Lambda (cont’d)

17. Check out the Monitor tab for
CloudWatch metrics.

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