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Best Practices in
Architecting for the
Cloud
Jeff Barr Senior Evangelist jbarr@amazon.com
Cloud Best Practices Whitepaper
Prescriptive guidance to Cloud Architects
http://bit.ly/aws-best-practices
Abstract
Resources
No Servers or Hard drives but Instances and Volumes.
Cloud resources are fungible.
On-Demand
Provisioning
Ask for what you need, exactly when you need it. Get rid
of it when you don’t need.
Scalability in
Minutes
Scale out or in depending on usage needs.
Pay On
Consumption
You stop paying for resources when you turn them off
Automation
Cloud gives you access to scriptable infrastructure.
Allows you to automate using APIs.
Cloud Computing Attributes
Why Architects love the cloud?
The “Living and Evolving” CloudThe “Living and Evolving” Cloud
AWS services and basic terminology
Infrastructure
building blocks
Platform building
blocks
Tools to access
services
Cross Service
features
The “Living and Evolving” CloudAWS Building Blocks
Inherently Fault-Tolerant
Services
Fault-Tolerant
with the right
architecture Amazon S3
 Amazon
DynamoDB
 Amazon
CloudFront
 Amazon SWF
 Amazon SQS
 Amazon SNS
 Amazon SES
 Amazon Route53
 Elastic Load
Balancing
 AWS IAM
 AWS Elastic
Beanstalk
 Amazon
ElastiCache
 Amazon EMR
 Amazon
CloudSearch
 Amazon
Redshift
 Amazon EC2
 Amazon EBS
 Amazon RDS
 Amazon VPC
Scalability
Characteristics of Truly Scalable Service
Build a Scalable Architecture on AWS
A scalable architecture is critical to take advantage of a scalable
infrastructure
Increasing resources results in a proportional increase in
performance
A scalable service is operationally efficient
A scalable service is resilient
A scalable service becomes more cost effective when it
grows
Cloud Architecture Lessons
1. Design for failure and nothing fails
2. Loose coupling sets you free
3. Implement “Elasticity”
4. Build Security in every layer
5. Think Parallel
6. Leverage different storage options
using Amazon Web Services
1. Design for Failure
"Everything fails, all the time"
Werner Vogels, CTO Amazon.com
and nothing will really fail
Avoid single points of failure
Assume everything fails, and design backwards
Goal: Applications should continue to function even if the underlying physical
hardware fails or is removed or replaced.
Design for Failure with AWS
Tools to make your life easier
Use Fault-tolerant Services as Ingredients of your App
Use Amazon Elastic Block Store (EBS) Snapshots
Auto-scaling for Auto-Recovery
Multi-AZ Data Replication and Recovery
On-demand application provisioning in a different AZ
Multi-AZ Application Deployment and Data replication
2. Build Loosely Coupled Systems
The looser they're coupled, the bigger they scale
Independent components
Design everything as a Black Box
De-couple for Hybrid models
Load-balance clusters
Controller A Controller B Controller C
Controller A Controller B Controller C
Q Q Q
Tight Coupling
Loose Coupling
using Queues
Use Amazon SQS as Buffers
3. Implement Elasticity
Don’t assume health or fixed location of components
Use designs that are resilient to reboot and re-launch
Bootstrap your instances: Instances on boot will ask a
question “Who am I & what is my role?”
Enable dynamic configuration
Elasticity is fundamental property of the Cloud
Use Auto Scaling
Use Elastic Load Balancing on multiple layers
Use configurations in DynamoDB to bootstrap instance
Use Configuration Management tools like Chef & Puppet…
3. Implement Elasticity
Towards elastic architectures
Resilient to reboot and re-launch:
Design the system such that in the event of a failure, it is resilient enough to
automatically re-launch and restart. Forcefully fail and test (Chaos Monkey).
Stateless:
Extract stateful components and strive to make them stateless.
Packable into an AMI:
Package and deploy your application into an AMI so it can run on an Amazon
EC2 instance. Run multiple instances on multiple Amazon EC2 instances.
Decouple:
Isolate the components using Amazon SQS. Decouple code with deployment
and configuration.
Standardized Technology Stacks
Use a Chaos Monkey
Standardized Application Stacks
4. Build Security in every layer
In the Cloud, Security is a Shared
Responsibility and it has to be
implemented in every layer
Design with Security in mind
SOC 1, 2, 3
ISO 27001/2 Certification
PCI DSS 2.0 Level 1-5
HIPAA/SOX Compliance
FedRAMP
FISMA & DIACAP
ITAR
Enforce IAM policies
Use MFA, VPC, Leverage S3
bucket policies, EC2 Security
groups, EFS in EC2 Etc..
Encrypt data in transit
Encrypt data at rest
Protect your AWS Credentials
Rotate your keys
Secure your application, OS,
Stack and AMIs
In the cloud, Security is a Shared Responsibility
Application
Security
Services Security
Infrastructure
Security
How we secure our
infrastructure
What security options
and features are available
to you?
How can you secure your
application and what is
your responsibility?
Availability Zone #2
RDS
Slave
Availability Zone #1
Cache Tier
Auto Scaling group : Web Tier
RDS
Master
Elastic Load
Balancer
Memcache
LB
Tomcat
Memcache
Distribution
Buckets
Amazon
CloudFront
Amazon S3
www.myphpwebsite.com
(dynamic data)
media.myphpwebsite.com
(static data)
Amazon Route 53
(DNS)
Amazon EC2
# Permit HTTP(S) access to Web
Layer from the Entire Internet
ec2auth Web -p 80,443 -s 0.0.0.0/0
# Permit Web Layer access to App
Layer
ec2auth App -p 8000 –o Web
# Permit App Layer access to DB
ec2auth DB -p 3209 –o App
# Permit admin access SSH to all
three layers
# First allow connection from
office to Web tier, and from there
to the other layers
ec2auth Web -p 22 -s <for example,
network block of your office>
ec2auth App -p 22 -o Web
ec2auth DB -p 22 -o Web
Web Server
App Server
Web Server
App Server
5. Think Parallel
Experiment with different architectures in parallel
Multi-threading and Concurrent requests to cloud services
Run parallel MapReduce Jobs on Amazon Elastic MapReduce
Use Elastic Load Balancing to distribute load across multiple servers
Decompose a Job into its simplest form
Serial and Sequential is now history
Hadoop
Amazon
Elastic
MapReduce
Cluster
Compute
HPC
Spot
Instances
Expand/
Shrink
Elastic
Super
computer
Distributed
Processing
Framework
On-demand
Infrastructure
(Cloud) +
Automation
Each VM =
2 Xeon
“Nehalem”
Quad-core
10G Ethernet
2 GPGPUs
Cost savings
due to lower
“Spot price”
(Time-insensitive
tasks)
Expand or
Shrink a
running
cluster
Big Data
power
house
5. Think Parallel
This is where AWS really shines..
6. Leverage many storage options
Amazon S3: large static objects
Amazon Cloudfront: content distribution
Amazon DynamoDB : data indexing/querying
Amazon EC2 local disc drive : transient data
Amazon EBS: persistent storage for any RDBMS + Snapshots on S3
Amazon RDS: RDBMS service - Automated and Managed
Amazon Redshift: Data warehouse service
Use Scalable Ingredients
6. Leverage many storage options
Which storage option to use when?
Amazon S3 +
CloudFront
Amazon
EC2
Ephemeral
Store
Amazon EBS Amazon
DynamoDB
Amazon RDS Amazon
Redshift
al for Storing Large
write-once,
read-many
types of
objects, Static
Content
Distribution
Storing non-
persistent
transient
updates
Off-instance
persistent
storage for any
kind of data
Querying light-
weight attribute
data
(SimpleDB)
Highly scalable
applications
(DynamoDB)
Storing and
querying
structured
Relational and
referential
Data
Storing and
rapidly
querying
vast
amounts of
Relational
data
al examples Media files,
audio, video,
images,
Backups,
archives,
versioning
Config Data,
scratch files,
TempDB
Clusters, boot
data, Log or
data of
commercial
RDBMS like
Oracle, DB2
Querying,
Mapping,
tagging, click-
stream logs,
metadata,
shared-state
management,
indexing
Complex
transactional
systems,
inventory
management
and order
fulfillment
systems
Enterprise
data
warehouse,
DW cube
lookups
ommended
Querying,
Searching
Storing
Database
logs or
backups,
customer
data
Relational
(joins) query
Moderately
sized data
sets
Database, File Sensitive Content OLTP, DW cube Simple Simple
Cloud Architecture Lessons
Best Practices
1. Design for failure and nothing fails
2. Loose coupling sets you free
3. Implement Elasticity
4. Build Security in every layer
5. Think Parallel
6. Leverage many storage options
Photo: Grand Canyon Hopi Point SunSet
Additional Info..
AWS Architecture Center - http://aws.amazon.com/architecture
AWS Premium Support - http://aws.amazon.com/premiumsupport
AWS Blog – http://aws.amazon.com/blog
jbarr@amazon.com
Twitter: @jeffbarr
Thank you!
http://aws.amazon.com

More Related Content

AWS Webcast - Best Practices in Architecting for the Cloud

  • 1. Best Practices in Architecting for the Cloud Jeff Barr Senior Evangelist jbarr@amazon.com
  • 2. Cloud Best Practices Whitepaper Prescriptive guidance to Cloud Architects http://bit.ly/aws-best-practices
  • 3. Abstract Resources No Servers or Hard drives but Instances and Volumes. Cloud resources are fungible. On-Demand Provisioning Ask for what you need, exactly when you need it. Get rid of it when you don’t need. Scalability in Minutes Scale out or in depending on usage needs. Pay On Consumption You stop paying for resources when you turn them off Automation Cloud gives you access to scriptable infrastructure. Allows you to automate using APIs. Cloud Computing Attributes Why Architects love the cloud?
  • 4. The “Living and Evolving” CloudThe “Living and Evolving” Cloud AWS services and basic terminology Infrastructure building blocks Platform building blocks Tools to access services Cross Service features
  • 5. The “Living and Evolving” CloudAWS Building Blocks Inherently Fault-Tolerant Services Fault-Tolerant with the right architecture Amazon S3  Amazon DynamoDB  Amazon CloudFront  Amazon SWF  Amazon SQS  Amazon SNS  Amazon SES  Amazon Route53  Elastic Load Balancing  AWS IAM  AWS Elastic Beanstalk  Amazon ElastiCache  Amazon EMR  Amazon CloudSearch  Amazon Redshift  Amazon EC2  Amazon EBS  Amazon RDS  Amazon VPC
  • 6. Scalability Characteristics of Truly Scalable Service Build a Scalable Architecture on AWS A scalable architecture is critical to take advantage of a scalable infrastructure Increasing resources results in a proportional increase in performance A scalable service is operationally efficient A scalable service is resilient A scalable service becomes more cost effective when it grows
  • 7. Cloud Architecture Lessons 1. Design for failure and nothing fails 2. Loose coupling sets you free 3. Implement “Elasticity” 4. Build Security in every layer 5. Think Parallel 6. Leverage different storage options using Amazon Web Services
  • 8. 1. Design for Failure "Everything fails, all the time" Werner Vogels, CTO Amazon.com and nothing will really fail Avoid single points of failure Assume everything fails, and design backwards Goal: Applications should continue to function even if the underlying physical hardware fails or is removed or replaced.
  • 9. Design for Failure with AWS Tools to make your life easier Use Fault-tolerant Services as Ingredients of your App Use Amazon Elastic Block Store (EBS) Snapshots Auto-scaling for Auto-Recovery Multi-AZ Data Replication and Recovery On-demand application provisioning in a different AZ Multi-AZ Application Deployment and Data replication
  • 10. 2. Build Loosely Coupled Systems The looser they're coupled, the bigger they scale Independent components Design everything as a Black Box De-couple for Hybrid models Load-balance clusters Controller A Controller B Controller C Controller A Controller B Controller C Q Q Q Tight Coupling Loose Coupling using Queues Use Amazon SQS as Buffers
  • 11. 3. Implement Elasticity Don’t assume health or fixed location of components Use designs that are resilient to reboot and re-launch Bootstrap your instances: Instances on boot will ask a question “Who am I & what is my role?” Enable dynamic configuration Elasticity is fundamental property of the Cloud Use Auto Scaling Use Elastic Load Balancing on multiple layers Use configurations in DynamoDB to bootstrap instance Use Configuration Management tools like Chef & Puppet…
  • 12. 3. Implement Elasticity Towards elastic architectures Resilient to reboot and re-launch: Design the system such that in the event of a failure, it is resilient enough to automatically re-launch and restart. Forcefully fail and test (Chaos Monkey). Stateless: Extract stateful components and strive to make them stateless. Packable into an AMI: Package and deploy your application into an AMI so it can run on an Amazon EC2 instance. Run multiple instances on multiple Amazon EC2 instances. Decouple: Isolate the components using Amazon SQS. Decouple code with deployment and configuration.
  • 13. Standardized Technology Stacks Use a Chaos Monkey Standardized Application Stacks
  • 14. 4. Build Security in every layer In the Cloud, Security is a Shared Responsibility and it has to be implemented in every layer Design with Security in mind
  • 15. SOC 1, 2, 3 ISO 27001/2 Certification PCI DSS 2.0 Level 1-5 HIPAA/SOX Compliance FedRAMP FISMA & DIACAP ITAR Enforce IAM policies Use MFA, VPC, Leverage S3 bucket policies, EC2 Security groups, EFS in EC2 Etc.. Encrypt data in transit Encrypt data at rest Protect your AWS Credentials Rotate your keys Secure your application, OS, Stack and AMIs In the cloud, Security is a Shared Responsibility Application Security Services Security Infrastructure Security How we secure our infrastructure What security options and features are available to you? How can you secure your application and what is your responsibility?
  • 16. Availability Zone #2 RDS Slave Availability Zone #1 Cache Tier Auto Scaling group : Web Tier RDS Master Elastic Load Balancer Memcache LB Tomcat Memcache Distribution Buckets Amazon CloudFront Amazon S3 www.myphpwebsite.com (dynamic data) media.myphpwebsite.com (static data) Amazon Route 53 (DNS) Amazon EC2 # Permit HTTP(S) access to Web Layer from the Entire Internet ec2auth Web -p 80,443 -s 0.0.0.0/0 # Permit Web Layer access to App Layer ec2auth App -p 8000 –o Web # Permit App Layer access to DB ec2auth DB -p 3209 –o App # Permit admin access SSH to all three layers # First allow connection from office to Web tier, and from there to the other layers ec2auth Web -p 22 -s <for example, network block of your office> ec2auth App -p 22 -o Web ec2auth DB -p 22 -o Web Web Server App Server Web Server App Server
  • 17. 5. Think Parallel Experiment with different architectures in parallel Multi-threading and Concurrent requests to cloud services Run parallel MapReduce Jobs on Amazon Elastic MapReduce Use Elastic Load Balancing to distribute load across multiple servers Decompose a Job into its simplest form Serial and Sequential is now history
  • 18. Hadoop Amazon Elastic MapReduce Cluster Compute HPC Spot Instances Expand/ Shrink Elastic Super computer Distributed Processing Framework On-demand Infrastructure (Cloud) + Automation Each VM = 2 Xeon “Nehalem” Quad-core 10G Ethernet 2 GPGPUs Cost savings due to lower “Spot price” (Time-insensitive tasks) Expand or Shrink a running cluster Big Data power house 5. Think Parallel This is where AWS really shines..
  • 19. 6. Leverage many storage options Amazon S3: large static objects Amazon Cloudfront: content distribution Amazon DynamoDB : data indexing/querying Amazon EC2 local disc drive : transient data Amazon EBS: persistent storage for any RDBMS + Snapshots on S3 Amazon RDS: RDBMS service - Automated and Managed Amazon Redshift: Data warehouse service Use Scalable Ingredients
  • 20. 6. Leverage many storage options Which storage option to use when? Amazon S3 + CloudFront Amazon EC2 Ephemeral Store Amazon EBS Amazon DynamoDB Amazon RDS Amazon Redshift al for Storing Large write-once, read-many types of objects, Static Content Distribution Storing non- persistent transient updates Off-instance persistent storage for any kind of data Querying light- weight attribute data (SimpleDB) Highly scalable applications (DynamoDB) Storing and querying structured Relational and referential Data Storing and rapidly querying vast amounts of Relational data al examples Media files, audio, video, images, Backups, archives, versioning Config Data, scratch files, TempDB Clusters, boot data, Log or data of commercial RDBMS like Oracle, DB2 Querying, Mapping, tagging, click- stream logs, metadata, shared-state management, indexing Complex transactional systems, inventory management and order fulfillment systems Enterprise data warehouse, DW cube lookups ommended Querying, Searching Storing Database logs or backups, customer data Relational (joins) query Moderately sized data sets Database, File Sensitive Content OLTP, DW cube Simple Simple
  • 21. Cloud Architecture Lessons Best Practices 1. Design for failure and nothing fails 2. Loose coupling sets you free 3. Implement Elasticity 4. Build Security in every layer 5. Think Parallel 6. Leverage many storage options
  • 22. Photo: Grand Canyon Hopi Point SunSet Additional Info.. AWS Architecture Center - http://aws.amazon.com/architecture AWS Premium Support - http://aws.amazon.com/premiumsupport AWS Blog – http://aws.amazon.com/blog