High Performance Web Applications

High Performance
Web Applications
Dr. Matt Wood
matthew@amazon.com
@mza

Building blocks for wonderful applications
Storage, compute, databases, managed services

Retail Merchant Web
services services

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Getting started with
Amazon Web Services

quick review

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Utility computing

Available at the end of an API call.
Metered billing.

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Family of 20 services

Adding new services and reﬁnement weekly.
Rapid rate of innovation.

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Undi!erentiated heavy lifting

Focus on your app, customers and business

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aws.amazon.com
Free account.
Free tier.

r
Building High Performance
Web Applications

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Deliver a great experience to
your customers.

Responsive, fast web applications.

SCALE
g DECOUPLED OUT OPTIMIZE FOR COST S

5 patterns for
performance

v
CALIBRATED FOR:

CPU performance
v
CALIBRATED FOR:

IO performan
ce
C
AUTOMATE

Assets

Application

Analytics

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Images, javascript, stylesheets,
HTML pages

Deliver as fast as possible to customers

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Websites without the servers

Highly durable: 99.999999999%
Zero conﬁg: ﬁre and forget

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Low latency delivery of assets

Local caching for fast downloads
Amazon CloudFront

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Create content distributions

From objects in S3
Any custom origin
Dynamic, streaming and static content

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CNAME?

Map to any custom URL
assets.domain.com, www.domain.com

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Application architecture

Small things, loosely coupled

Assets

Load balancer

App servers
Application

Database

Asynchronous processing

Analytics

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Shared responsibility

Infrastructure by AWS
OS, application and data by customers
Tools to help meet best practices

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Security groups

Customer controlled ﬁrewalls
All ports are closed by default

Assets

Load balancer

x App servers
Application

Database


Analytics

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Decoupling provides an architectural
framework for performance

Easier to separate concerns: assets, streaming, etc.
Easier to manage and scale.

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Elasticity is a tenet of the cloud

Scale up when you need to
Scale down when you don’t

r Predictable peaks
Demand

Capacity

Time

r Variable usage
Demand

Capacity

Time

r Variable usage
Demand

Time

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Horizontal scaling
drives performance up

...and costs down

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Amazon Machine Images
encapsulate your app

Customize your virtual machines
AMI can be the unit of deployment

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1. Spin up a new instance
using your AMI

Conﬁgured to bootstrap the app.

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2. Pull down latest code base

From S3 or code repository

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3. Start up the app on the instance

Ready to receive requests

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4. Register with the load balancer

Job done.

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Horizontal scaling allows for
fault tolerance

Assets

Load balancer

:( App servers
Application

Database


Analytics

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Deploying and scaling a datastore

Follow the same patterns:
horizontal scale, availability, automation.

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One question:
Does your application require a
strict, controlled schema for query ﬂexibility?

Does your application require a strict, controlled schema
r for query ﬂexibility? Yes

Amazon Relational Database Service

Management systems: CRM, ERP, ﬁnance

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Focus on your app

Handles tedious database admin tasks
Designed for availability

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Multi-engine

MySQL, Oracle, Microsoft SQL Server
Up and running in six clicks

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Point in time snapshots

Automatic. Easy recovery.

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High availability

Deployed across multiple availability zones.
Synchronous writes.

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Read replicas

Perfect for read heavy applications.
Asynchronous writes.
Replication metrics available.

Does your application require a strict, controlled schema
r for query ﬂexibility? No

Amazon DynamoDB

Web apps, social apps, mobile apps,
user generated content,
unstructured data integration, lots of data.

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Focus on your app

Managed NoSQL database service.
No schema.

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Unlimited scale

Unlimited storage
Pay as you go

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High performance

Single digit millisecond latencies

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Zero admin

No instances to manage
Tiny API, perfectly formed

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Resize images. Transcode movies.
Resample media.

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Follow the same best practices

Decouple. Stateless. Horizontal scale.

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CloudFront for dynamic content

Edge caching for dynamic content
Cache by query string parameters
Multiple origin servers
Persistent connections to origin servers

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Automate everything

The tedious.
The time consuming.
The error prone.

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For example:
when increasing capacity
Launch instance.
Update application code.
Register with load balancer.

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Auto-scaling

CloudWatch
Auto-scaling service
Elastic Load Balancer

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Set operational thresholds

Network capacity > 80%
Memory utilization > 75%
CPU < 50%

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Automatically respond to
operational alarms
Network capacity > 80%: add instances
Memory utilization > 75%: add instances
CPU < 50%: remove instances

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Set bounds

Step change conﬁgured by number or
percentage of instances

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Custom metrics

Respond to custom metrics
Page load time
Database query time

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Automatic load balancer
conﬁguration
Instances added/removed automatically
Health check for running application before
routing tra"c

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Stateless operations are important

Decoupled, but stateless
Instances are naive to other instances

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Treat your data as a royal garden

Backup to S3: high durability
Compute is a disposable resource

CALIBRATED FOR:
v CPU performance

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Range of resources

Choose the best instance type
for performance

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t1.micro m1.small cc2.8xlarge

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High memory High CPU + memory

t1.micro m1.small High CPU cc2.8xlarge

1 instance for 100 hours
=
100 instances for 1 hour

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Balance cost/performance

Mix instance types for application servers,
databases, ancillary services, analytics etc.

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Migrate to large instance types

As your application grows
Use 64 bit from the outset, if possible

CALIBRATED FOR:
v IO performance

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IO bound web applications are
more common

Application requires predictable, consistent IO

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Provisioned throughput with
DynamoDB
No need to provision storage
Provision IO requirements:
reads and writes per second

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Scale up, and carry on

DynamoDB will manage resources to
achieve and maintain throughput

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Low latency, unlimited scale

Writes acknowledged when saved to disk in
multiple data centres. Backed on SSDs.

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hi1.4xlarge instances

High capacity, high performance storage
2 x 1Tb SSD drives

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Perfect match for databases

Relational and NoSQL storage

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Perfect match for databases

Relational and NoSQL storage
90k to 120k IOPS

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High performance network

10 gigabit ethernet
Placement groups
Perfect for distributed stores

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Economies of scale

Drive down prices for customers
20 price drops in past 6 years

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Maximize utilization

Greater utilization drives down cost

Utilization

Reserved capacity

Time

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Reserved instances

Small upfront payment
Guaranteed capacity for 1 or 3 years
Lower hourly rate

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Reserved instance resale

Sell your reservations on the resale market
Sellers set your own price
Buyers select and check out

Utilization

On-demand

Reserved capacity

Time

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Spot instances

Name your price computing

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Spot instances

Lower costs
‘Overclock’ your app: more bang for your buck

Assets

Load balancer

App servers
Application

Database on SSDs


Analytics

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Become price aware

Price is a driver of your architecture

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Automated bidding

Automate bids based on on-demand price
Run on spot only when cost e!ective

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Continuous cost optimization

Evaluate your reserved instance/on-demand/
spot mix regularly as app requirements change

g DECOUPLED

5 patterns for
performance

SCALE
g DECOUPLED OUT

5 patterns for
performance

SCALE

5 patterns for
performance

SCALE

5 patterns for
performance

CALIBRATED FOR:
v CPU performance
CALIBRATED FOR:

v IO performan
ce

Thank you
matthew@amazon.com

aws.amazon.com
@mza

High Performance Web Applications

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