The document discusses challenges faced by monolithic software, including long development cycles and difficulty in maintaining architecture, advocating for a shift towards microservices and serverless technologies for improved agility and innovation. It outlines best practices for modern application development, emphasizing the importance of automation, observability, and security. Additionally, it details the functionalities and advantages of AWS serverless services like AWS Lambda, and how they contribute to efficient application management.

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Modern Applications Development
and Serverless Computing
Boaz Ziniman
Technical Evangelist - Amazon Web Services
@ziniman
boaz.ziniman.aws
ziniman

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“The Monolith”

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Challenges with monolithic software
Long Build/Test/Release
Cycles
(who broke the build?)
Operations
is a nightmare
(module X is failing,
who’s the owner?)
Difficult to
scale
New releases
take months
Long time to add
new features
Architecture is
hard to maintain
and evolve
Lack of innovation
Frustrated customers
Lack of agility

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Monolith development lifecycle
releasetestbuild
delivery pipeline
App (aka the “monolith”)developers

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Too much software coupling
Shared libraries
Shared data

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Development transformation at Amazon: 2001–2002
monolithic application
+ teams
2001
Lesson learned: decompose for agility
2002
microservices
+ 2 pizza teams

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Full ownership
Full accountability
“DevOps”
Focused innovation
Two-pizza teams

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Monolith development lifecycle
monitorreleasetestbuild
developers
delivery pipelines
services

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Microservice development lifecycle
???
developers
delivery pipelines
services

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Microservice development lifecycle
developers services
monitorreleasetestbuild
delivery pipelines
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild

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Approaches to modern application development
• Simplify environment management
• Reduce the impact of code changes
• Automate operations
• Accelerate the delivery of new, high-quality services
• Gain insight across resources and applications
• Protect customers and the business

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Approaches to modern application development
• Simplify environment management with serverless technologies
• Reduce the impact of code changes with microservice architectures
• Automate operations by modeling applications & infrastructure as code
• Accelerate the delivery of new, high-quality services with CI/CD
• Gain insight across resources and applications by enabling observability
• Protect customers and the business with end-to-end security & compliance

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What changes do you need to make to adopt these best practices?
Serverless
No provisioning/management
Automatic scaling
Pay for value billing
Availability and resiliency
Microservices
Componentization
Business capabilities
Products not projects
Infrastructure automation
DevOps
Cultural philosophies
Cross-disciplinary teams
CI/CD
Automation tools
DEV OPS
Architectural
patterns
Operational
Model
Software
Delivery

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Microservices on AWS
AWS Lambda
Serverless functions
AWS Fargate
Serverless containers
ECS/EKS
Container-management as a service
EC2
Infrastructure-as-a-Service
More opinionated
Less opinionated
AWS manages Customer manages
• Data source integrations
• Physical hardware, software, networking,
and facilities
• Provisioning
• Application code
• Container orchestration, provisioning
• Cluster scaling
• Physical hardware, host OS/kernel,
networking, and facilities
• Application code
• Data source integrations
• Security config and updates, network config,
management tasks
• Container orchestration control plane
• Physical hardware software,
networking, and facilities
• Application code
• Data source integrations
• Work clusters
• Security config and updates, network config,
firewall, management tasks
• Physical hardware software,
networking, and facilities
• Application code
• Data source integrations
• Scaling
• Security config and updates, network config,
management tasks
• Provisioning, managing scaling and
patching of servers

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What is serverless?
No infrastructure provisioning,
no management
Automatic scaling
Pay for value Highly available and secure

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Deliver on demand, never pay for idle
EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE

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Using AWS Lambda
Simple resource model
• Select power rating from
128 MB to 3 GB
• CPU and network
allocated proportionately
Flexible use
• Synchronous or
asynchronous
• Integrated with other
AWS services
Flexible authorization
• Securely grant access to
resources and VPCs
• Fine-grained control for
invoking your functions
Bring your own code
• Node.js, Java, Python, C#,
.Net Core 2.0, GO, Ruby
• NEW - Your own Runtime
• Bring your own libraries
• Layers

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Using AWS Lambda
Authoring functions
• WYSIWYG editor or
upload packaged .zip
• Third-party plugins
(Eclipse, Visual Studio,
PyCharm)
Monitoring and logging
• Metrics for requests,
errors, and throttles
• Built-in logs to Amazon
CloudWatch Logs
Programming model
• Use processes, threads,
/tmp, sockets normally
• AWS SDK built in (Python
and Node.js)
Stateless
• Persist data using
external storage
• No affinity or access to
underlying infrastructure

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Serverless architectures
1. File put into bucket
2. Lambda invoked 2. Lambda invoked
1. Data published to a topic
Data
1. Message inserted into to a
queue
3. Function
removes
message from
queue
2. Lambda polls queue
and invokes function
Object Message
Amazon S3
Lambda
Function
Amazon Simple Queue
Service
Amazon Simple
Notification Service
Lambda
Function
Lambda
Function

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Web application
Data stored in Amazon
DynamoDB
Dynamic content in
AWS Lambda
Amazon API
Gateway
Browser
Amazon
CloudFront
Amazon S3

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Streaming data ingestion
Amazon S3:
Buffered files
Kinesis
Agent
Record
Producers Amazon Redshift:
Table loads
Amazon Elasticsearch Service:
Domain loads
Amazon S3:
Source record backup
AWS Lambda:
Transformations &
enrichment
Amazon DynamoDB:
Lookup tables
Raw records
Lookup
Transformed records
Transformed recordsRaw records
Amazon Kinesis Firehose:
Delivery stream

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Image recognition and processing
Web App
Amazon DynamoDB:
Image meta-data & tags
Amazon Cognito:
User authentication
Amazon S3:
Image uploads
Start state machine execution
1
Amazon Rekognition:
Object detection
Invoke Amazon Rekognition
Generate image thumbnail
3
3
Extract image meta-data
2
Store meta-data and tags
4
https://github.com/awslabs/lambda-refarch-imagerecognition
AWS Step Functions:
Workflow orchestration

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Cron
events
DATA STORES ENDPOINTS
CONFIGURATION REPOSITORIES EVENT/MESSAGE SERVICES
Example event sources that trigger AWS Lambda
… and a few more with more on the way!
Amazon S3 Amazon API
Gateway
Amazon
DynamoDB
AWS Step
Functions
Amazon
SNS
Amazon
SES
Amazon
Kinesis
Amazon
Kinesis
AWS IoT
Core
Alexa for
Business
Amazon
CloudWatch
AWS
CodeCommit
AWS
CloudTrail
AWS
CloudFormation

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FINRA

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Serverless is an operational model that spans many
different categories of services
AWS
Lambda
AWS
Fargate
Amazon
API Gateway
Amazon
SNS
Amazon
SQS
AWS
Step Functions
COMPUTE
DATA STORES
INTEGRATION
Amazon Aurora
Serverless
Amazon
S3
Amazon
DynamoDB
AWS
AppSync

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AWS SERVERLESS PORTFOLIO
APPLICATION PRIMITIVES – COMPUTE AND DATASTORES
AWS
Lambda
AWS
Fargate
Amazon
API Gateway
Amazon
SNS
Amazon
MQ
Amazon
SQS
AWS
Step Functions
APPLICATION INTEGRATION
DEVELOPER TOOLS
SECURITY AND ADMINISTRATION
Amazon Aurora
Serverless
Amazon
S3
Amazon
DynamoDB
AWS
IAM
Amazon
Cognito
Amazon
Inspector
Amazon
VPC
Amazon
GuardDuty
AWS
CloudFormation
AWS
Cloud9
AWS
CloudTrail
Amazon
CloudWatch
AWS
X-Ray
AWS
CodePipeline
AWS
Config
AWS
SSO
AWS
Shield
AWS
WAF
Amazon
Kinesis
AWS Serverless
Application
Repository
AWS
AppSync

32. Thank you!
© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Boaz Ziniman
Technical Evangelist, Amazon Web Services
@ziniman
boaz.ziniman.aws
ziniman