real world development: peeling the onion – migrating a monolithic application to microservices

Adam LarterPrincipal Solutions Architect, Developer Specialist

Real-world developmentPeeling the onion - migrating a

monolithic application to microservices

• Approaches to taking an enterprise Java monolith and breaking it into microservices on AWS.

• Using the AWS developer tools - AWS CodeStar, AWS CodeCommit, AWS CodePipeline and AWS CodeBuild - to orchestrate and automate our deployment.

• Using AWS Lambda and Amazon API Gateway to hostpolyglot serverless microservices.

• Using AWS X-Ray to capture custom application events, trace requests through the AWS SDKs and analyse underlying service performance.

LEARNING OBJECTIVES

D E V L O U N G E

A compelling eventSome technical debtBig business opportunity

D E V L O U N G E

ARCHITECTURE

Single vertically-scaledserver hosted off-cloud

D E V L O U N G E

ARCHITECTURE

D E V L O U N G E

XML / JSON data dumps from 3rd party providers

WWW / HTMLend users

ARCHITECTURE

D E V L O U N G E

XML / JSON data dumps from 3rd party providers

XML / JSON REST endpoint for 3rd party integrators

WWW / HTMLend users

D E V L O U N G E

OUR MONOLITH

BUSINESS REQUIREMENTS• Go faster – deliver new features at increased cadence.

Speed wins in business

• Be more stable – no more business interruptions due to technical problems

• Increase quality – all changes and updates to production should work first time, every time

• Be cheaper – reduce TCO

• Business long-term and short-term solution“Let’s move this workload to the cloud”

D E V L O U N G E

How can we quickly set up anend-to-end DevOps toolchain for our monolith?

D E V L O U N G E

Quickly develop, build, and deploy applications on AWS

Start developing on AWS in minutes

Work across your team, securely

Manage software delivery easily

Choose from a variety of project templates

AWS CODESTAR

D E V L O U N G E

Let’s create a CodeStar projectfor our monolith

D E V L O U N G E

Quickly develop, build, and deploy applications on AWSAWS CODESTAR

D E V L O U N G E

Collaborate securely with your team: Manage team access, add team members to projects by role i.e. owners, contributors

Integrated issue tracking and project management: Integrates Atlassian JIRA Software to easily manage issues directly from CodeStar dashboard and monitor application progress and activity

D E V L O U N G E

Develop on AWS in minutes: Easily set up your entire development environment and programming tools for coding, building, testing, and deploying on AWS

Supported for popular programming languages: Develop variety of applications using language of choice including Java, NodeJS, JavaScript, PHP, Ruby, Python and now .Net Core

Preconfigured AWS CloudFormation templates for quick development project creation

• Automatic provisioning of underlying AWS services so the team can get coding quickly

Over twenty different AWS CodeStar project templatesSupport for websites, web services, microservices, Alexa Skills dev projects (and more)

3 Hosting environments§ Self-Managed: Amazon EC2 with AWS CodeDeploy§ Managed: Elastic Beanstalk§ Serverless: AWS Lambda

Amazon EC2

AWS CodeDeploy

AWS Elastic Beanstalk

AWSLambda

AWS CODESTAR PROJECT TEMPLATES

D E V L O U N G E

• Single pane of glass to manage your project & build pipeline• Coordinate your day-to-day development activities• Dashboard provides tools to view real time application activity,

monitor builds, and flow of code through deployment pipeline• Customize project dashboard by adding, removing, moving

tiles• Add customizable team wiki tile for team resources sharing or

other purposes (eg. show code snippets)• Use CodeStar project extensions to add tiles and functionality

dashboard

AWS CODESTAR PROJECT DASHBOARD

D E V L O U N G E

ARCHITECTURE

D E V L O U N G E

ARCHITECTURE

MONOLITH MONOLITH

D E V L O U N G E

HIDDEN COMPLEXITY

One Monolith – many components

Cold/Hot Read/Write master

D E V L O U N G E

Underlying Framework

Data Access Service

Flight / Hotel / Trip Services

User Experience & Session Manager

HIDDEN COMPLEXITY

• Monolithic codebase• Stateful application logic• Tight coupling• Technical debt• Performance issues• Maintenance difficulties• Implementation detail leakage in the API• Data tier complexities technology and lock-in• Lots of undifferentiated heavy lifting

TECHNICAL CHALLENGES

D E V L O U N G E

• Deploy to AWS Elastic Beanstalk PaaS immediately (lift-and-shift to meet our compelling event deadline)

• Migrate over time to a microservices architecture as were-think and re-imagine our business and technical solution

• Use AWS Lambda to host our microservices as serverless

• Restructure organisation around business capability

• Delegate ownership of each microservice to a dedicated team

TECHNICAL SOLUTION

D E V L O U N G E

Monolithicoff-cloud

Elastic Beanstalk

?Identify candidate

microservice, design APIs

CodePipeline

CodeBuild

CodeCommit

CodeStar

Lambda

“Lift

ift”

Time D E V L O U N G E

TECHNICAL SOLUTION

API Gateway

Compelling event

Monolithicoff-cloud

Elastic Beanstalk

?Identify candidate

CodePipeline

CodeBuild

CodeCommit

CodeStar

Lambda

“Lift

ift”

Time D E V L O U N G E

TECHNICAL SOLUTION

API Gateway

Compelling event

How does AWS CodeStar help?

D E V L O U N G E

AWS CodePipeline AWS CodeCommit AWS CodeBuildAWS CodeDeployAWS CodeStar

AWS CODE SERVICES

D E V L O U N G E

• Integration tests with other systems

• Load testing• UI tests• Penetration

testing

Source Build Test Production

• Check-in source code such as .java files.

• Peer review new code

• Compile code• Unit tests• Style checkers • Code metrics• Create

container images

• Deployment to dev, staging, uator production environments

RELEASE PROCESSES HAVE FOUR MAIN PHASES

Continuous integration

Continuous delivery

Continuous deployment

RELEASE PROCESS LEVELS

AWS CodeCommit

Software Release Steps:AWS CODE SERVICES

D E V L O U N G E

AWS CodeBuild

D E V L O U N G E

Third PartyTooling

D E V L O U N G E

AWS CodeDeploy

D E V L O U N G E

Third PartyTooling

AWS CodeCommit AWS CodeBuild AWS CodeDeploy

AWS CodePipeline

D E V L O U N G E

Third PartyTooling

AWS CodeCommit AWS CodeBuild AWS CodeDeploy

AWS CodePipeline

AWS CodeStar

ü Project Templatesü Team Access Management with

AWS IAMü Managed Build Service with

AWS Code Buildü Unified Project Dashboard using

Amazon CloudWatch monitoring service

ü Issue tracking and project management tool in dashboard via integrated Atlassian JIRA Software

ü AWS CodeCommit for Secure Hosted Git Repository

ü Automated App Deployments with AWS CodeDeploy and AWS CloudFormation

ü Integration of AWS CodePipeline for Automated Continuous Delivery Pipeline

AWS CODESTAR FEATURES

D E V L O U N G E

THE 6 R’s OF MIGRATION

RetainR1 R4

• Keep host/application in source environment• Minimal analysis/validation of scope

& application affinity

Retire • Decommission• No migration of application

Rehost • Like-for-life app migration to AWS• Lift-and-shift approach• Minimal effort to make the app

work ‘on’ the cloud or take advantage of cloudnative services

Replatform • Up-version the OS/DB• Make use of Amazon RDS• Some app changes• App re-installation and clean-up

Refactor • OS/DB porting• Middleware and app changes

to use AWS services natively• Data conversion, DB transition

(eg: MySQL & Aurora)

Rearchitect • Application architecture changes• Using SaaS-based offerings• Porting of application architecture• Data modernisation, application

consolidation, make use of AWS-nativemanaged services

RetainR1 R4

ON the cloud

RetainR1 R4

IN the cloud

RetainR1 R4

FOR the cloud

• Cloud infrastructure introduces new concepts

• Off-cloud design doesn’t always translate to cloud principles

• Lift-and-shift often limits the value proposition but addresses our time constraints for the compelling event

• Applications that don’t embrace cloud-native design don’t fully realize scale, availability, and cost benefits

• Cloud design principles are still emerging, but based on well-known highly scalable application patterns

D E V L O U N G E

Monolithicoff-cloud

Elastic Beanstalk

?Identify candidate

CodePipeline

CodeBuild

CodeCommit

CodeStar

Lambda

“Lift

ift”

D E V L O U N G E

TECHNICAL SOLUTION

API Gateway

Rehost• Like-for-life app migration to AWS• Lift-and-shift approach• Minimal effort to make the app

• Quickly deploy and manage applications in the AWS cloud without worrying about the application infrastructure

• True PaaS – automatically handles allthe details of patching, resource provisioning, load balancing & auto-scaling

• Launch your Java, PHP, .NET, Node.js, Python, and Ruby applications in a matter of minutes

Automate N-tier web apps on PaaSAWS ELASTIC BEANSTALK

D E V L O U N G E

Automate N-tier web apps on PaaSAWS ELASTIC BEANSTALK

192.168.96.0/20

AZ-BAZ-A

Public Subnet 192.168.100.0/24

Public Subnet 192.168.102.0/24

192.168.100.210NAT1 NAT2

WWW WWW

Private Subnet 192.168.104.0/24 Private Subnet 192.168.105.0/24

Private Subnet 192.168.106.0/24 Private Subnet 192.168.107.0/24

192.168.101.10AD DC

1AD DC

Public ELB

AWS Region

D E V L O U N G E

Test customers

WWW WWWPublic ELB

Elastic Load Balancer

Web servers

Security GroupsAuto-scaling &self-healing

D E V L O U N G E

Re-architecting our applicationas serverless microservices

D E V L O U N G E

D E V L O U N G Ehttps://martinfowler.com/articles/microservices.html

Microservices approach advocates creating a system from a collection of small,

isolated services, each of which owns their data, and is independently isolated, scalable and resilient to failure

D E V L O U N G E

• Organized around business capability

• Decentralised ownership of services

• Automated deployment

• Intelligent endpoints

MICROSERVICES CHARACTERISTICS

D E V L O U N G E

Monolithic Microservices• Simple deployments• Binary failure modes• Inter-module refactoring• Technology monoculture• Vertical scaling• Shared datastore• Owned by everyone

• Partial deployments• Graceful degradation• Strong module boundaries• Technology diversity• Horizontal scaling• Discrete datastores• Owned by single dev or team

D E V L O U N G E

• Increased speed and agility and ability to innovateChanges can be made to the decoupled architecture quickly with low risk

• Reduced costDesigning, implementing and scaling microservices is cost effective because they are decoupled and have no dependencies

• Improved resilienceIf one microservice fails, the entire system will continue to function

• Be small enough to be re-written in two weeks• Follow DDD bounded contexts• Be run by the team that built them• Own their own state and do not share• Be developed by a team that can be fed by 2 pizzas• Have freedom to use the right technology stack for the job

• Isn’t it just Service-Oriented Architecture (SOA)?

• How micro is ‘micro’? How many is enough/too many?

• Just like object oriented code -low coupling, highly cohesive, data hidden, encapsulation, defined interface

• Not just a technology change!

MICROSERVICES ARCHITECTURES

D E V L O U N G E

MONOLITHIC ORGANISATION

D E V L O U N G E

Organised on technology capabilities (Conway’s Law)

Web Tier

App Tier

l Stru

icatio

eUI Team

App Logic Team

DBA Team

MICROSERVICES ORGANISATION

D E V L O U N G E

Organised on business initiativesO

isatio

icatio

Flight ServiceTeam

TripsServiceTeam

HotelServiceTeam

Web Tier

App Tier

Requirements

Quality Deployment

DevelopmentTechnology Stack

Operations

OWNERSHIP – TEAMS CONTROL THEIR DESTINY

D E V L O U N G E

Peeling the onion:How do we identify candidate microservices?

D E V L O U N G E

Monolithicoff-cloud

Elastic Beanstalk

?Identify candidate

CodePipeline

CodeBuild

CodeCommit

CodeStar

Lambda

“Lift

ift”

D E V L O U N G E

TECHNICAL SOLUTION

API Gateway

D E V L O U N G E

• Domain-driven design aligns well with the characteristics of microservices – encapsulated, defined-interfaces, isolated

• Microservices should have a well-defined bounded contextand should “just do one thing”

• A bounded context encapsulates a single domain (eg, application service or data model)

• Defines the integration points with other domains

• Beware of creating monolithic microservices!

DDD & BOUNDED CONTEXT

D E V L O U N G E

• Look for ‘seams’ between service classes

• Many of these will own their own DAO and will be well isolated

• Services with CRUD-style interfaces with some related business logic are good candidates

• Look for classes with no or few dependencies

• Try some refactoring to clean up the code before you start

PEELING THE ONION

Serverless microserviceswith AWS Lambda

D E V L O U N G E

• VMs – machine as the unit of scale• “I want to configure machines, storage,

networking, and my OS”

• Containers – application as the unit of scale• “I want to run servers, configure applications,

and control scaling”

• Serverless – functions as the unit of scale• “Run my code when it’s needed”

AWS Lambda

CHOOSING COMPUTE INFRASTRUCTURE

D E V L O U N G E

Continuous scaling No servers to manage

Never pay for idle –no cold servers

D E V L O U N G E

AWS LAMBDA FOR MICROSERVICES

Monolithicoff-cloud

Elastic Beanstalk

?Identify candidate

CodePipeline

CodeBuild

CodeCommit

CodeStar

Lambda

“Lift

ift”

D E V L O U N G E

TECHNICAL SOLUTION

API Gateway

Let’s create a CodeStar projectfor our first microservice on AWS Lambda

D E V L O U N G E

Team Members

AWS CodeStarAdministrator

Developers commit changes

BuildChanges are built

DeploymentCode is

deployed

MonitoringApplication and infrastructure

IdeasRequestsBug fixes

DevelopersBest practices

Team decisions

ChangesUpdates

Creates project and adds users Customer

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

Secure, scalable, and managed git source control

Use standard git tools

Scalability, availability, and durability of Amazon S3

Encryption at rest with customer-specific keys

No repo size limit

Post-commit hooks to call out to SNS/Lambda

AWS CODECOMMIT

D E V L O U N G E

git pull/push CodeCommit

git objects inAmazon S3

git index inAmazon DynamoDB

Encryption keyin AWS KMS

SSH or HTTPS

D E V L O U N G E

AWS CODECOMMIT

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

Fully managed build service that compiles source code, runs tests, and produces software packages

Scales continuously and processes multiple builds concurrently

You can provide custom build environments suited to your needs via Docker images

Only pay by the minute for the compute resources you use

CodePipeline and Jenkins integration

D E V L O U N G E

AWS CODEBUILD

“Building” code typically refers to languages that require compiled binaries:• .NET languages: C#, F#, VB.net, etc.• Java and JVM languages: Java, Scala, JRuby• Go

We also refer to the process of creating Docker container images as “building” the image.

BUILDING YOUR CODE

Many languages don’t require building. These are considered interpreted languages:• PHP• Ruby• Python• Node.js

CodeBuild can package dependencies ready for deployment

D E V L O U N G E

PACKAGING YOUR CODE

1. Downloads source code

2. Executes commands configured in the buildspec in temporary compute containers (created fresh on every build)

3. Streams the build output logs to the service console and CloudWatch logs

4. Uploads the generated artifact to an S3 bucketD E V L O U N G E

AWS CODEBUILDBuild process

version: 0.1

environment_variables:plaintext:JAVA_HOME: "/usr/lib/jvm/java-8-openjdk-amd64"

phases:install:commands:- apt-get update -y- apt-get install -y maven

pre_build:commands:- echo Nothing to do in the pre_build phase...

build:commands:- echo Build started on `date`- mvn install

post_build:commands:- echo Build completed on `date`

artifacts:type: zipfiles:- target/messageUtil-1.0.jar

discard-paths: yesD E V L O U N G E

EXAMPLE buildspec.yml

version: 0.1

environment_variables:plaintext:JAVA_HOME: "/usr/lib/jvm/java-8-openjdk-amd64"

phases:install:commands:- apt-get update -y- apt-get install -y maven

pre_build:commands:- echo Nothing to do in the pre_build phase...

build:commands:- echo Build started on `date`- mvn install

post_build:commands:- echo Build completed on `date`

artifacts:type: zipfiles:- target/messageUtil-1.0.jar

discard-paths: yes

• Variables to be used by phases of build

• Examples for what you can do in the phases of a build:

• You can install packages or run commands to prepare your environment in ”install”.

• Run syntax checking, commands in “pre_build”.

• Execute your build tool/command in “build”

• Test your app further or ship a container image to a repository in post_build

• Create and store an artifact in S3

EXAMPLE buildspec.yml

Strangling the monolith

D E V L O U N G E

BrowserAccountService

UserService

CartService

Common monolithic database

Store FrontUser Interface

STRANGLING THE MONOLITHReducing risk by using a Strangler pattern rather than a direct cut-over

UserService

CartService

New Microservice

NO MORE NEW FEATURES ON THE MONOLITHReducing risk by using a Strangler pattern rather than a direct cut-over

UserService

CartService

New Microservice

ANTI-CORRUPTION LAYER FOR INTEGRATIONIndirection Pattern An ACL is used as a layer of abstraction and indirection between bounded contexts. It translates from one context to the other.

UserService

Client

CartService

New Microservice

UserMicroservice

START WITH A SIMPLE EXISTING SERVICEIndirection Pattern An ACL is used as a layer of abstraction and indirection between bounded contexts. It translates from one context to the other.

UserService

Client

CartService

New Microservice

UserMicroservice

CartMicroservice

MOVE ON TO MORE COMPLICATED SERVICES

Browser

UserMicroservice

AccountMicroservice

AccountService

UserService

Client

CartService

New Microservice

UserMicroservice

CartMicroservice

AccountMicroservice

MOVE ON TO MORE COMPLICATED SERVICES

Browser

UserMicroservice

AccountMicroservice

New Microservice

UserMicroservice

CartMicroservice

AccountMicroservice

END STATE

D E V L O U N G E

Next step – UX modernisationto an SPA using Angular/Reactand hosted on S3

Polyglot microservices

D E V L O U N G E

TravelBuddyUI

FlightsDatabase

FlightService

HotelService

HotelsDatabase

Trips SearchService

TripsDatabase

Web clients Load Balancer API Gateway

OWNERSHIP – TEAMS CONTROL THEIR DESTINY

DevelopmentTechnology Stack

D E V L O U N G E

Polyglot persistence

D E V L O U N G E

AmazonElastiCache

Amazon DynamoDB

Amazon RDS

Amazon Redshift

AmazonS3

Object

AmazonGlacier

POLYGLOT PERSISTENCE

D E V L O U N G E

ACID Transactions

Fast readsNoSQL

BLOBs High-throughputvolatile cache

HotelSpecials-SvcTripSearch-SvcFlightSpecials-Svc

Amazon ElastiCache

Amazon RDS

Amazon DynamoDB

AmazonRDS

DECENTRALISED DATA STORES

D E V L O U N G E

Scale each independentlyto optimise its scale for performance and cost

Let’s do polyglot!

D E V L O U N G E

Orchestrating build and deploywith pipelines

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

Continuous delivery service for fast and reliable application updates

Model and visualize your software release process

Builds, tests, and deploys your code every time there is a code change

Integrates with third-party tools and AWS

AWS CODEPIPELINE

D E V L O U N G E

Source

SourceGitHub

CodeBuildAWS CodeBuild

Deploy

JavaAppElastic Beanstalk

PipelineStage

Action

Transition

CodePipelineMyApplication

D E V L O U N G E

NotifyDevelopersLambda

Parallel actions

Source

SourceGitHub

Deploy

D E V L O U N G E

NotifyDevelopersLambda

TestAPIRunscope

Sequential actions

Deploy

Source

SourceGitHub

D E V L O U N G E

Staging-Deploy

Prod-Deploy

QATeamReviewManual Approval Manual Approvals

Review

D E V L O U N G E

Debugging and traceability

D E V L O U N G E

MONOLITHIC ARCHITECTURE

D E V L O U N G E

Underlying Framework

Data Access Service

Flights, Trips & Hotels in monolithic database

Flight / Hotel / TripsService

User Experience & Session Manager

Complexity is hiddeninside the monolithic

codebase

TravelBuddyUI

FlightsDatabase

FlightService

HotelService

HotelsDatabase

Trips SearchService

TripsDatabase

Web clients Load Balancer API Gateway

MICROSERVICES ARCHITECTURE

Complexity in Code Base

Complexity inInteractions & Deployment

CHALLENGES OF MICROSERVICES

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

D E V L O U N G E

Team Members

DeploymentCode is

deployed

Team decisions

ChangesUpdates

• Complex distributed apps are the new normal• Debugging distributed apps is hard• Performance management of microservice-oriented

applications is more work compared to monolithic applications• Tracing across distributed applications is a challenge because:

• Interactions occur across many services• Variations in logging formats – lacking standardisation• Collection, aggregation, and collation of logs from many services

involved in a single interaction is complex

DEBUGGING AND TRACABILITY

D E V L O U N G E

Analyze and debug production, distributed applications

Simple setup: instrument your application with X-Ray SDK and install X-Ray Daemon (already installed for AWS Lambda and Amazon Elastic Beanstalk environments)

End-to-End Tracing, cross-service view of requests made to your application.

AWS X-RAY

D E V L O U N G E

Service Map provides a view of connections between services in your application and aggregated data for each service, including average latency and failure rates

The service provides facilities for custom injection, data annotation, adding metadata and filtering

AWS X-RAY

D E V L O U N G E

Amazon ECS

Amazon EC2

AWS Elastic Beanstalk

AmazonSQS

AmazonSNS

Amazon RDS: Postgres, MySQL, Aurora

AmazonDynamoDB

AWSLambda

AWS X-RAY SERVICE INTEGRATIONS

D E V L O U N G E

Amazon API Gateway

AWS Lambda

Amazon DynamoDB

AmazonSQS queue

AWS X-RAY COMPONENTS

D E V L O U N G E

AWS X-RAY – INSTRUMENTING YOUR APPLICATION

1. Add the SDK as a dependency in your build configuration.

AWS X-RAY RECORDER FOR JAVA

pom.xml

2. Add a servlet filter to your deployment descriptor to trace incoming HTTP requests.

web.xml

D E V L O U N G E

3. Configure JDBC interceptor in DataSource bean

servlet-context.xml

D E V L O U N G E

Easily Gain Benefits of DevOpsAWS CODESTAR

Reliability

Rapid Delivery

Security

Improved Collaboration

D E V L O U N G E

Programming Languages

JavaScript

Python

.Net Core

IDE/Code Editors

Visual Studio

Eclipse

AWS CLIAWS CLI

CodeStar project templates support popular languages and IDEsAWS CODESTAR

D E V L O U N G E

• Integrates with Atlassian JIRA Software issue tracking and project management tool

• Easy JIRA and AWS CodeStar setupü Log into JIRA and Copy URL from any projectü Enter JIRA URL field in the CodeStar Extensions

• Monitor application activity and manage all JIRA issues in CodeStar dashboard

• Create new JIRA tickets for work items directly dashboard

D E V L O U N G E

AWS CODESTAREasily Gain Benefits of DevOps

THINK BIGSTART SMALLACT NOW>

HOW DO I START?

Learn more about CodeStar:https://aws.amazon.com/codestar

Check out Blog Post: Introducing AWS CodeStar:https://aws.amazon.com/blogs/aws/new-aws-codestar/

Get started with AWS CodeStar:https://console.aws.amazon.com/codestar

REFERENCES

D E V L O U N G E

Learn more about AWS X-Ray:https://aws.amazon.com/x-ray

Check out Blog Post: Introducing AWS CodeStar:https://aws.amazon.com/blogs/aws/category/aws-x-ray/

Get started with AWS CodeStar:https://console.aws.amazon.com/xray/home

REFERENCES

D E V L O U N G E

Adam LarterPrincipal Solutions Architect, Developer Specialist

Thank you!

real world development: peeling the onion – migrating a monolithic application to microservices

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