Optimizing Your AWS

Apps and Usage to

Reduce Costs

Ianni Vamvadelis Manager, Solution Architecture

Agenda

• Objective

- Review the spectrum of ways to save money on your AWS application

• Tenet: Fit the cloud to your product and business model

- Use Only What You Need (and pay only for what you use!)

- Measure and Manage

- Scale Opportunistically

• Customer Spotlight

- National Rail Enquiries

Use Only What You Need

And pay only for what you use!

Customer Example

• Chris Scoggins

• CEO, National Rail Enquiries

Background

• Private company created in 1996 owned by the TOCs

• From the busiest phone number in the UK to the #1 website in travel

• Over 1 million visits everyday across web & mobile

• Achieved over 99% migration to self-service

• Customer complaints 1.3 per 100,000 contacts

• Over £800m of sales leads provided to TOCs and 3rd parties p.a.

• Over 500 services provided to 150 clients

• Annual growth of 50%

The Challenge

• Volatility of up to 10x peak demand

• Large deployed computer estate across 6 data centres

• Ageing computer estate

• Rapid growth in B2C and B2B business

• Ever increasing rich functionality in channels

• Multiple service desks

• Suppliers experts in application development not hosting

Why Cloud?

• Agility and elasticity – use what we need, when needed

• High performance – availability & resilience

• Market knowledge – solution provided by hosting & SIAM experts

• Low cost – pay for use, savings of 30%

• Commodity culture – ready and easy to use

• Flexibility and freedom – keep up to date & not locked in

Scale on demand

Rigid On-Premise Resources

Waste

Customer

Dissatisfaction

Actual demand

Predicted Demand

Ca

pa

city

Time

Elastic Cloud Resources

Actual demand

Resources scaled to demand

Ca

pa

city

Time

VS.

Use only what you need: AWS cost savings opportunities

Right-size your cloud resources

- Use resources that suit your needs (instance types, storage options, etc.)

- Improve performance: reduce churn, underutilization, bottlenecks

- Lower costs: maximize your output per dollar, don’t pay for performance you don’t require

Fit your payment model to your business model

- Do you value flexibility or predictability?

- Use a portfolio of payment models

Measure and manage your application and cloud resources

- Monitor your applications to identify new savings opportunities

Right-size your cloud resources

• An instance size for every purpose

• Assess your memory & CPU requirements

- Fit your application to the resource

- Fit the resource to your application

• Only use a larger instance when needed

Optimize your storage choice too: S3 & Glacier

S3 and Glacier are both:

- Secure

- Flexible

- Low-cost

- Scalable: over 2 trillion

- Durable: 99.999999999% (11 “9”s)

Amazon

Glacier

Choosing between S3 and Glacier

Amazon Simple Storage Service (S3)

- Designed to serve static content at high volumes, low latency, frequent access

- Low cost: as low as 5.5¢ per GB-month (or 3.7¢ for reduced redundancy)

Amazon Glacier

- Designed for long-term cold storage: infrequent access, long retrieval times (3-5 hrs)

- Extremely low-cost: 1¢ per GB-month

Tips:

- Optimize access: Reduce payload size, # of accesses (e.g., consolidated logs)

- Monitor for unexpected access/growth patterns: e.g., misconfigured log archiving

- Set Lifecycle Policies: object expiration dates; auto-move S3 files to Glacier

Illumina, the leading provider of DNA sequencing

instruments, uses Glacier to store large blocks of

genomic data all over the world

Fit your payment model to your business model: EC2 pricing plans

On-Demand

Instances

Reserved

Instances

Spot

Instances

Pay as you go for computing

power

Flat hourly rate, no up-front

commitments

Pay an up-front fee for a

capacity reservation and a lower

hourly rate (up to 72% savings)

1-year or 3-year terms

RI Marketplace: sell RIs you no

longer need; buy RIs at a

discount

Pay what you want for spare

EC2 capacity: your instances run

if your bid exceeds the Spot price

Potential for large scale at low

cost: When they’re available,

take advantage of 1,000s of Spot

Instances at up to 90% savings

10:00

10:05

10:10

10:15

Use a spectrum of payment models

For example:

Frontend Applications

on On-Demand/Reserved Instances

+

Backend Applications*

on Spot Instances

* e.g., batch video transcoding

Reserved Instance Marketplace: Buy and Sell

• Benefits for Buyers:

• Same underlying EC2 hardware

• Buy RIs at a discount from AWS price

• Increased selection of term lengths & prices

• Benefits for Sellers:

• Moving to a new AWS region

• Changing your instance type

• Switching operating systems

• Selling capacity when project ends

Measure and Manage

“If you cannot measure it, you cannot improve it.”

- Lord Kelvin

Overview of AWS Monitoring and Management Services

AWS provides detailed cloud monitoring and management

- Consolidated Billing (see “Account Activity” navigation panel)

- CloudWatch (see AWS Management Console)

- Billing Alerts (see “Account Activity” navigation panel)

- Trusted Advisor (see “Support Center”)

- Other APIs: tags, programmatic access, etc.

Third-party services are also available

Consolidated Billing: Single payer for a group of accounts • One Bill for multiple accounts

• Easy Tracking of account charges (e.g., download CSV of cost data)

• Group Activities by Paying Account (e.g., Dev, Stage, Test, Prod)

• Volume Discounts can be reached faster with combined usage

• Reserved Instances are shared across accounts (including RDS Reserved DBs)

• AWS Credits are combined to minimize your bill

Consolidated Billing Demo (1/3)

Get an overall summary total for all your users and accounts

Consolidated Billing Demo (2/3)

From your payment account login, view details of each linked account in one place

Consolidated Billing Demo (3/3)

• Drill down into detail’s of each account

• Download a CSV file for line item details, then analyze via spreadsheet, pivot tables, etc.

Amazon CloudWatch

• Overview

- Monitoring for AWS cloud resources and applications

• AWS Resources: EC2, RDS, EBS, ELB, SQS, SNS, DynamoDB, EMR, Auto Scaling, …

• Custom metrics from your application (use Put API call)

- Gain insight, set alarms and notifications, react immediately

- Start using within minutes, auto-scale with your application

• Sophisticated Automation

- Use CloudWatch metrics with Auto Scaling to dynamically scale EC2 instances

Use CloudWatch to monitor & manage resource usage

• Monitor your resource utilization

- Are you using the right instance type?

- Have you left instances idle?

- Is your instance usage level or bursty?

• Manage your resource utilization

- Move bursty workloads to other instances

- Rebalance your worker nodes

- Scale nodes automatically with Auto Scaling

Use CloudWatch to create Billing Alerts

• Billing Alerts notify you when estimated charges reach a given threshold

• Use Billing Alerts to track an individual developer, or your whole business

• Easily set up your billing alarm and actions

Trusted Advisor: Enterprise Strength Monitoring/Optimization

• Monitors and recommends optimizations for:

• Cost

• Security

• Fault Tolerance

• Performance

• Available to customers with Business and Enterprise-level support

http://aws.amazon.com/premiumsupport/trustedadvisor/

Trusted Advisor: Cost Optimization Tips

Trusted Advisor: Performance Tips

Third-party services to optimize your AWS usage

Scale Opportunistically

Opportunity favors the prepared application

Time-to-Result Case 1: Value of result quickly diminishes

Example:

Engineering

simulation

Delay Loss of

productivity,

project slips

Time-to-Result Case 2: Result is valuable…until it’s not

Example:

Weekend

regression tests

Delay Minimal

impact until

8:00AM Monday

Consider Spot Instances for greater savings and scale

• Spot in a nutshell

- Spot instances run when Your Bid ≥ Spot Price

- Spot instances = Spare EC2 instances

- Spot instances might be interrupted at any time

• Benefits

- Savings: Up to 90% off On-Demand

- Scale: Access up to 1,000s of EC2 instances

• To use Spot

- Decide on a bid price

- Launch via Console, API, Auto Scaling

- Monitor Bid Statuses via Console/API

What applications work on Spot?

• Good Spot applications are: - Delayable: to balance SLA/cost - Scalable: “embarrassingly parallel” - Fault-tolerant: can be terminated without losing all work - Portable across regions, AZs, instance types

• Examples:

- MapReduce (Hadoop, Amazon EMR) - Scientific Computing (Monte Carlo simulations) - Batch Processing (video transcoding) - Financial Computing (high-frequency trading algorithm backtesting) - and many others…

Lucky Oyster crawled 3.4B Web

Pages, building a 400M entry index

in around 14 hours for $100 (>85%

savings)!

Use Auto Scaling to dynamically scale your app

• Auto Scaling auto-sizes your fleet based on preset alarms and schedules

• Integrates with CloudWatch metrics

• Use Auto Scaling to

- Improve customer experience, application performance

- Maximize CPU/IO/Memory utilization

- Optimize other metrics Scale with Real-Time Demand

Auto-Scaling Example: Netflix

Follow the Money vs. Follow the Customer

• Optimize utilization

- Auto Scale on utilization metrics: CPU, memory, requests, connections, …

• Optimize price paid

- Scale with Spot instances when Spot prices are low

- e.g., Run batch processes off-peak (nights, weekends) when Spot prices are lower

Follow the Money vs. Follow the Customer

• Optimize customer experience with Auto Scaling

• Example 1: Scale resources to meet customer demand

- Video service Auto Scales instances to respond to customer web service requests

• Example 2: Scale resources to ensure fresh results

- A scientific paper search engine Auto Scales on queue depth (# of new docs to crawl)

- 10 instances steady state and up to 5,000+ to ensure minimum throughput time

• Example 3: Scale resources preemptively before large demand

- A TV show marketing site scales up before the show and back down after

Cost-Saving Examples

Achieve potentially large savings by profiling your application and paying only for what you need

Base Case Savings Examples

You run 10

m3.2xlarge’s On-

Demand 24x7:

10 instances

X $1.00/inst-hours

X 24 hours/day

X ~30.5 days/month = $7,320/month

If you need to run 100% of the time, indefinitely:

10x 3-yr Heavy RIs @ 100% Utilization = $2,731/month (63% savings)

If you can layer RIs and On Demand to meet

demand:

4x 3-yr Heavy RIs @ 100% Utilization

4x 3-yr Light RIs @ 15% Utilization

2x On-Demand @ 5% Utilization

= $1,843/month (75% savings)

If you Auto Scale from 2 to 10 instances around

primetime TV (6-11pm, Mon-Fri):

2x 3-yr Heavy RIs @ 100% Utilization

8x 3-yr Light RIs @ 15% Utilization

= $1,683/month (77% savings)

If you can use 40x Spot Instances at 25% up-time:

= $840/month (89% savings)

Conclusion (Part I): Fit the cloud to your product and business model

• Use Only What You Need (and pay only for what you use!)

• Measure and Manage

• Scale Opportunistically

An example putting it all together: Saving on Batch Processing

http://aws.amazon.com/architecture/

3. Scale

Opportunistically:

Auto Scale worker

nodes based on size

of input queue

1. Pay Only

for What You

Use: Right-

size your cloud

resources

2. Monitor and

Manage your system

with CloudWatch,

Billing Alerts, Trusted

Advisor

Conclusion (Part II): Use the cloud to create new products & business models

On-Premises

• Failure is

expensive

• Experiment

infrequently

• Less Innovation

Optimized Cloud

• Failure is

inexpensive

• Experiment early

and often

• More Innovation

THANK YOU

http://aws.amazon.com/economics

APPENDICES

Other simple optimization tips

• Don’t forget to… - Disassociate unused EIPs

- Delete unassociated Amazon EBS volumes

- Delete older Amazon EBS snapshots

- Leverage Amazon S3 Object Expiration

- Defer batch activity (e.g., Hadoop) to periods when your RIs are regularly underutilized

(For Enterprise-level support, Trusted Advisor can help with some of these.)

• Netflix’s Janitor Monkey automates clean-up - Reduces “unintentional” resource usage

- Reduces cost and clutter

Other Spot Instance Use Cases

• Batch Processing: Generic batch processing (scale out computing)

• Hadoop: MapReduce processing (e.g., Search, Big Data)

• Scientific Computing: Scientific trials, simulations, analysis

• Video/Image Processing: Encoding, transcoding, rendering

• Testing: Continuous testing, load testing websites, etc.

• Web/Data Crawling: Analyzing data and processing it

• Financial: Hedge fund analytics, energy trading, etc.

• HPC/HTC: Embarrassingly parallel jobs

• Cheap Compute: Backend servers for Facebook games, MineCraft

Steady State

Example: Corporate Website

Spiky Predictable

Example: Marketing Promotions Website

Uncertain unpredictable

Example: Social game or Mobile Website

Application Usage Patterns

Amazon Elastic MapReduce

Hadoop Cluster

HDFS

Task Node

Task Node

Core Node

Core Node

Input

Data Outpu

tData

Amazon S3

Metadata

Amazon SimpleDB

BI Apps

Upload large datasets or

log files directly Data

Source

Code/

Scripts

Amazon S3

Service

Amazon Elastic

MapReduce

HiveQL

Pig Latin

Cascading

Mapper

Reducer

Runs multiple

JobFlow Steps

Name Node

JDBC/ODB

C

HiveQL

Pig Latin Query

Amazon EMR (Hadoop): Run Task Nodes on Spot

Paying as you go on AWS lowers your Total Cost of Ownership

• By paying only for what you use, you can save on: - Servers

- Storage

- Network

- Environment

- Administration

• Example: 82% TCO savings for Thomsen Reuters

• Learn more: aws.amazon.com/economics

Example Spot Customers

Example Architecture 2: Web Application Hosting

http://aws.amazon.com/architecture/