Microservices and serverless for MegaStartups - DLD TLV 2017

Microservices & Serverless
for MegaStartups
Boaz Ziniman - Technical Evangelist, AWS
@ziniman
Entrepreneurship on Tap - DLD Meetup
September 2017

About me
• Technical Evangelist at AWS
• Events & Meetsup
• Webinars
• Blogs
• Community
• Social Media
• A long history of Web Development, IT and Operations
• AWS Customer since 2009

Agenda
• Breaking the Monolith
• An Introduction to Microservices
• Who needs servers?
• Lambda and Serverless on AWS
• 5 Principals for running Microservices at scale

2006 EC2 & S3
2017 90+ Managed Services
Kinesis Streaming Analytics, Mobile Testing, Redshift
Datawarehouse, Code Deploy/Build Tools, Elastic
Container Service, Application Load Balancer,
Lambda, API Gateway, DynamoDB, Elastic Map, AI,
Reduce (Hadoop/Spark/Presto/etc), Elastic
Beanstalk, Elastic Transcoder, RDS, Elasticsearch,
IoT, more..

AWS’ History of Innovation
AWS has been continually expanding its services to support virtually any
cloud workload, and it now has more than 90 services that range from
compute, storage, networking, database, analytics, application services,
deployment, management and mobile.
2011
Amazon
ElastiCache
Amazon SES
CloudFormation
Direct
Connect
AWS Elastic
Beanstalk
GovCloud
2013
Amazon
CloudTrail
Amazon
CloudHSM
Amazon
WorkSpaces
Amazon
Kinesis
Amazon Elastic
Transcoder
Amazon
AppStream
AWS OpsWorks
AWS Kinesis Firehose
AWS Database Migration
Service
AWS Kinesis Analytics
2015
Amazon EFS
Amazon API Gateway
Amazon WorkMail
Amazon Machine
Learning
AWS Device Farm
AWS WAF
Amazon
Elasticsearch Service
Amazon QuickSight
AWS Snowball
AWS RDS for MariaDB
Amazon Inspector
AWS IoT
Amazon EC2 Container
Registry
AWS Mobile Hub
Amazon CloudWatch
2009
Amazon RDS
Amazon VPC
AWS Auto Scaling
AWS Elastic Load
Balancing
AWS EMR
Amazon FPS
2010
Amazon SNS
AWS Identity
& Access
Management
Amazon
Route 53
AWS Import/Export
2012
Amazon SWF
AWS Redshift
Amazon Glacier
Dynamo DB
Amazon
CloudSearch
Storage
Gateway
AWS Data
Pipeline
Trusted Advisor
2014
AWS KMS
Amazon Config
Amazon Cognito
Amazon Mobile
Analytics
Amazon EC2
Container Service
RDS for Aurora
Amazon Lambda
Amazon WorkDocs
Directory Service
AWS CodeCommit
AWS CodePipeline
AWS Service Catalog
AWS CodeDeploy
CloudWatch Logs
2016
AWS Organizations
Amazon Quicksight
AWS step functions
Amazon Lex
Amazon Polly
Amazon Rekognition
AWS Greengrass
Amazon EC2 elastic GPU
Amazon EC2 FPGA (F1)
Amazon EC2 P2
AWS Batch
Amazon Lightsail
Lambda@Edge
Blox
Aurora with PostgreSQL
compability
AWS codeBuild
AWS X-ray
AWS Snowball Edge
Amazon Pinpoint
AWS Shield
Cloudwatch Events
AWS Glue
Amazon Pinpoint
48 61 82
159
280
516
722
~1,000

ENTERPRISE
APPS
DEVELOPMENT & OPERATIONSMOBILE SERVICESAPP SERVICESANALYTICS
Data
Warehousin
g
Hadoop/
Spark
Streaming Data
Collection
Machine
Learning
Elastic
Searc
h
Virtual
Desktops
Sharing &
Collaboration
Corporate
Email
Backup
Queuing &
Notifications
Workflow
Search
Email
Transcoding
One-click App
Deployment
Identity
Sync
Single Integrated
Console
Push
Notifications
DevOps Resource
Management
Application Lifecycle
Management
Containers
Triggers
Resource
Templates
TECHNICAL &
BUSINESS
SUPPORT
Account
Management
Support
Professional
Services
Training &
Certification
Security
& Pricing
Reports
Partner
Ecosystem
Solutions
Architects
MARKETPLACE
Business
Apps
Business
Intelligenc
e
Databases
DevOps
Tools
Networking
Securit
y
Storage
Regions
Availability
Zones
Points of
Presence
INFRASTRUCTURE
CORE SERVICES
Compute
VMs, Auto-scaling,
& Load Balancing
Storage
Object, Blocks,
Archival, Import/Export
Databases
Relational,
NoSQL, Caching,
Migration
Networking
VPC, DX, DNS
CDN
Access
Control
Identity
Management
Key
Management
& Storage
Monitoring
& Logs
Assessment
and reporting
Resource &
Usage Auditing
SECURITY & COMPLIANCE
Configuration
Compliance
Web
application
firewall
HYBRID
ARCHITECTURE
Data
Backups
Integrated
App
Deployments
Direct
Connect
Identity
Federation
Integrated
Resource
Management
Integrated
Networking
API
Gateway
IoT
Rules
Engine
Device
Shadows
Device
SDKs
Registry
Device
Gateway
Streaming Data
Analysis
Business
Intelligence
Mobile
Analytics

Migrating from Monolith
to Microservice

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

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

Too much software coupling
Shared libraries
Shared data

Evolving towards microservices
“IMG_1760” by Robert Couse-Baker. No alterations other than cropping. https://www.flickr.com/photos/29233640@N07/14859431605/
Image used with permissions under Creative Commons license 2.0, Attribution Generic License (https://creativecommons.org/licenses/by/2.0/)

“service-oriented
architecture
composed of
loosely coupled
elements
that have
bounded contexts”
Adrian Cockcroft (VP of Cloud Architecture @
AWS, former Cloud Architect at Netflix)

“service-oriented
architecture
composed of
loosely coupled
elements
that have
bounded contexts”
Services communicate with
each other over the network

“service-oriented
architecture
composed of
loosely coupled
elements
that have
bounded contexts”
You can update the services
independently; updating one
service doesn’t require
changing any other services.

“service-oriented
architecture
composed of
loosely coupled
elements
that have
bounded contexts”
Self-contained; you can
update the code without
knowing anything about the
internals of other
microservices

“Do one thing, and do it well”
“Swiss Army” by by Jim Pennucci. No alterations other than cropping. https://www.flickr.com/photos/pennuja/5363518281/

“Tools” by Tony Walmsley: No alterations other than cropping. https://www.flickr.com/photos/twalmsley/6825340663/
“Do one thing, and do it well”

Public API
POST /restaurants
GET /restaurants
Application/Logic
(code, libraries, etc)
Anatomy of a Microservice
Data Store
(eg, RDS, DynamoDB
ElastiCache, ElasticSearch)

Drivers
microservices
Payments
microservice Location
microservices
Ordering
microservices
Restaurant
microservice
Ecosystem of Microservices

= 50 million deployments a year
Thousands of teams
× Microservice architecture
× Continuous delivery
× Multiple environments
(5708 per hour, or every 0.63 second)

Servers
How will the application
handle server hardware failure?
How can I control
access from my servers?
When should I decide to
scale out my servers?
When should I decide to
scale up my servers?
What size servers are
right for my budget?
How much remaining
capacity do my servers have?
(AAHHHHHHHHH!!)

What is
serverless?
Build and run applications
without thinking about servers

Let’s take a look at the evolution of computing
Physical Servers
Datacenters
Virtual Servers
Datacenters
Virtual Servers
in the cloud

Each progressive step was better
Physical Servers
Datacenters
Virtual Servers
Datacenters
Virtual Servers
in the cloud
• Higher utilization
• Faster provisioning speed
• Improved uptime
• Disaster recovery
• Hardware independence
• Trade CAPEX for OPEX
• More scale
• Elastic resources
• Faster speed and agility
• Reduced maintenance
• Better availability and fault
tolerance

But there are still limitations
Physical Servers
Datacenters
Virtual Servers
Datacenters
• Trade CAPEX for OPEX
• More scale
• Elastic resources
• Faster speed and agility
• Reduced maintenance
• Better availability and fault
tolerance
• Still need to administer
virtual servers
• Still need to manage
capacity and utilization
• Still need to size
workloads
• Still need to manage
availability, fault tolerance
• Still expensive to run
intermittent jobs
Virtual Servers
in the cloud

Evolving
to serverless
SERVERLESS
Virtual servers
in the cloud
Physical servers
in datacenters
Virtual servers
in datacenters

No server is easier to manage than any server
All of these responsibilities
go away
Provisioning and utilization
Availability and fault tolerance
Scaling
Operations and management

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

No servers to provision
or manage
Scales with usage
Never pay for idle Availability and fault
tolerance built in
Benefits of Lambda and serverless compute

Using AWS Lambda
Bring your own code
• Node.js, Java, Python,
C#
• Bring your own libraries
(even native ones)
Simple resource model
• Select power rating from
128 MB to 1.5 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

Using AWS Lambda
Authoring functions
• WYSIWYG editor or
upload packaged .zip
• Third-party plugins
(Eclipse, Visual Studio)
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

Amazon S3 Amazon
DynamoDB
Amazon
Kinesis
AWS
CloudFormation
AWS CloudTrail Amazon
CloudWatch
Amazon
Cognito
Amazon SNSAmazon
SES
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!
AWS
CodeCommit
Amazon
API Gateway
Amazon
Alexa
AWS IoT AWS Step
Functions

Common 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
IT
Automation
• Policy engines
• Extending
AWS services
• Infrastructure
management

Common use cases
Web Applications and Backends
Internet
Mobile Apps
Websites
Services
AWS Lambda
function
AWS
API Gateway
Cache
All publicly
accessible
endpoints
Amazon
CloudWatch
Monitoring
Amazon
CloudFront
Amazon S3 AWS Lambda
function
AWS Lambda
function
Amazon DynamoDB
Web
Applications
• Static
websites
• Complex web
apps
• Packages for
Flask and
Express
Backends
• Apps &
services
• Mobile
• IoT
</></>

Common 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
IT
Automation
• Policy engines
• Extending
AWS services
• Infrastructure
management
Lambda + S3

Customers innovating with serverless

1. User visits
HTTPS
GET /
S3 with
CloudFront
2. CSS & JS
HTTPS
GET
*.js
*.css
S3 with
CloudFront
index.html
3. Lang detect
API Gateway
w/
Lambda
HTTPS
GET
/users/
country
HTTPS
POST
/users/
update
4. User fills details
API Gateway
w/
Lambda
Inserted into
DynamoDB
PAGE LIFECYCLE

5.
6.
5. FB Login
(optional)
Hits Facebook
Hosted Endpoint
via Facebook
Javascript SDK
6. YouTube
YouTube iframe
7. Start recording
API Gateway w/
Lambda
Responds with
S3 upload token
Uploads directly
to S3 bucket
over HTTPS
using token
8. Upload recording
HTTPS
GET
api.facebook.com
HTTPS
GET
youtube.com
{
“email”: “xyz”,
“profile_id”: 123
}
HTTPS
GET
/recordings/token
HTTPS
POST
bucket.s3.amazon/UID/
recording-X.mp3
PAGE LIFECYCLE

9. Submit details
API Gateway w/
Lambda
10. Artwork gen
HTTPS
POST
/users/generate_
artwork
API Gateway w/
Lambda.
Create image,
put on S3, return
S3 image URL
11. Artwork display
CloudFront w/ S3
HTTPS
GET
/domain.com/UID.png
AddThis.js is
populated with
the share texts,
and includes the
S3 URL
HTTP
GET
addthis.com/file.js
HTTPS
POST
/users/
update
{ url:
“domain.com/UID
.png” }
12. Social share 13. Social share
HTTPS
GET
https://twitter.com/intent/
tweet?text=XYZ
Directly hits the
social media
service
PAGE LIFECYCLE

Microservices Architecture on
Amazon Web Services

API Gateway
Build, Publish and Manage APIs
§ Performance at any scale via worldwide edge locations,
traffic throttling, and API output caching
§ Monitor API activity
§ Integrates with Lambda functions
§ Run multiple versions of the same API
§ Fully Managed
Application Services

Elastic Compute Cloud (EC2)
Virtual Servers in the Cloud
§ Resizable Compute Capacity
§ Complete control of your computing resources
§ Reduces time to obtain and boot new server
instances to minutes
§ Choose from 30+ different instance types
§ Scale as your requirements change
§ Pay only for what you use
Compute

EC2 Container Service
Run and Manage Docker Containers
§ A high performance container management service
for running Docker containers on EC2 instances
§ Use the built in scheduler, write your own, or use a
third-party scheduler
§ Integrates with other services like ELB and EBS
§ No additional charge
§ EC2 Container Registry
Compute

Lambda
Run Code in Response to Events
§ Runs code in response to triggers such as S3
upload, DynamoDB updates, Kinesis streams,
and API Gateway requests
§ Automatically scales
§ You only need to provide the code; there is no
infrastructure to manage
§ Pay only for what you use
Compute

DynamoDB
Predictable and Scalable NoSQL Data Store
§ Fast, fully-managed NoSQL Database Service
§ Capable of handling any amount of data
§ Durable and Highly Available
§ All SSD storage
§ Simple and Cost Effective
Database

Microservices Architecture
Internet
Mobile Apps
Websites
Services
AWS Lambda
functions
AWS
API Gateway
Cache
Endpoints on
Amazon EC2 /ECS
Amazon Elastic
Beanstalk
Any other publicly
accessible endpoint
Amazon
CloudWatch
Monitoring
Amazon
API Gateway

Principle 1
Microservices only
rely on each other’s
public API
“Contracts” by NobMouse. No alterations other than cropping.
https://www.flickr.com/photos/nobmouse/4052848608/
Image used with permissions under Creative Commons
license 2.0, Attribution Generic License
(https://creativecommons.org/licenses/by/2.0/)

Microservice A Microservice B
public API
Principle 1: Microservices only rely on each
other’s public API
public API

public API
public API

public API public API
Nope!

storeRestaurant (id, name, cuisine)
storeRestaurant (id, name, cuisine)
storeRestaurant (id, name, arbitrary_metadata)
addReview (restaurantId, rating, comments)
storeRestaurant (id, name, arbitrary_metadata)
addReview (restaurantId, rating, comments)
Version 1.0.0
Version 1.1.0
Version 2.0.0
public API
Microservice A

Principle 2
Use the right tool for the
job
“Tools #2” by Juan Pablo Olmo. No alterations other than cropping.
https://www.flickr.com/photos/juanpol/1562101472/
Image used with permissions under Creative Commons license
2.0, Attribution Generic License

public API
Amazon
Elasticsearch
Service
RDS
Aurora
DynamoDB
public API
Principle 2: Use the right tool for the job

public API
RDS
Aurora
Amazon
Elasticsearch
Service
DynamoDB
public API
Principle 2: Use the right tool for the job

Principle 3
Secure Your Services
“security” by Dave Bleasdale. No alterations other than cropping.
https://www.flickr.com/photos/sidelong/3878741556/
Image used with permissions under Creative Commons license 2.0,
Attribution Generic License

Principle 3: Secure Your Services
• Defense-in-depth
• Network level (e.g. VPC, Security Groups, TLS)
• Server/container-level
• App-level
• IAM policies
• Gateway (“Front door”)
• API Throttling
• Authentication & Authorization
• Client-to-service, as well as service-to-service
• API Gateway: custom Lambda authorizers
• IAM-based Authentication
• Token-based auth (JWT tokens, OAuth 2.0)
• Secrets management
• S3 bucket policies + KMS + IAM
• Open-source tools (e.g. Vault, Keywhiz)
API Gateway

Principle 4
More than just
technology
transformation
“rowing on the river in Bedford” by Matthew Hunt.
No alterations other than cropping.
https://www.flickr.com/photos/mattphotos/19189529/
Attribution Generic License (https://creativecommons.org/licenses/by/2.0/)

“Any organization that designs a system
will inevitably produce a design whose
structure is a copy of the organization’s
communication structure.”
Melvin E. Conway, 1967
Conway’s Law

Silo’d functional teams à silo’d application architectures
Image from Martin Fowler’s article on microservices, at
http://martinfowler.com/articles/microservices.html
Permission to reproduce: http://martinfowler.com/faq.html

Cross functional teams à self-contained services

(“Two-pizza teams” at Amazon)

(“Two-pizza teams” at Amazon)
Full ownership
Full accountability
Aligned incentives

Principle 5
Automate Everything
“Robot” by Robin Zebrowski. No alterations other than cropping.
https://www.flickr.com/photos/firepile/438134733/
Attribution Generic License
(https://creativecommons.org/licenses/by/2.0/)§

Focused agile teams
delivery pipeline service
releasetestbuild
releasetestbuild
releasetestbuild
releasetestbuild
releasetestbuild
releasetestbuild
2-pizza team

Principle 6: Automate everything
AWS
CodeCommit
AWS
CodePipeline
AWS
CodeDeploy
EC2 ELB
Auto
ScalingLambdaECS
DynamoDBRDS ElastiCache SQS SWF
SES SNS
API GatewayCloudWatch Cloud Trail
KinesisElastic
Beanstalk

It’s a journey…
Expect challenges along the way…
• Understanding of business domains
• Coordinating txns across multiple
services
• Eventual Consistency
• Service discovery
• Lots of moving parts requires increased
coordination
• Complexity of testing / deploying /
operating a distributed system
• Cultural transformation

Benefits of Microservices
Rapid
Build/Test/Release
Cycles
Clear ownership and
accountability
Easier to scale
each individual
microservice
New releases
take minutes
Short time to add
new features
Easier to
maintain and
evolve
Increase innovation
Delighted customers
Increased agility

Benefits of Microservices
Rapid
Build/Test/Release
Cycles
Clear ownership and
accountability
Easier to scale
each individual
microservice
New releases
take minutes
Short time to add
new features
Easier to
maintain and
evolve system
Faster innovation
Delighted customers
Increased agility

AWS resources:
• Microservices without the Servers
https://aws.amazon.com/blogs/compute/
microservices-without-the-servers
• Microservices with ECS:
https://aws.amazon.com/blogs/compute/using-amazon-
api-gateway-with-microservices-deployed-on-amazon-
ecs/
• Serverless Service Discovery:
https://aws.amazon.com/blogs/developer/
serverless-service-discovery-part-1-get-started/
• ECS Service Discovery:
https://aws.amazon.com/blogs/compute/
service-discovery-an-amazon-ecs-reference-
architecture/
• Serverless Webapp - Reference Architecture:
https://github.com/awslabs/lambda-refarch-webapp
• Zombie Microservices Workshop:
https://github.com/awslabs/aws-lambda-zombie-
workshop
Popular open-source tools:
• Serverless – http://serverless.com
• Apex - http://apex.run/
https://aws.amazon.com/devops/
Additional Resources

Join Amazon Web Services at DLD
September 7, 2017 | 09:30 – 17:00
http://bit.ly/AWSDLD

Thank you
@ziniman
http://bit.ly/EventsIL

Microservices and serverless for MegaStartups - DLD TLV 2017

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Microservices and serverless for MegaStartups - DLD TLV 2017