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©2015,  Amazon  Web  Services,  Inc.  or  its  affiliates.  All  rights  reserved

©2015,  Amazon  Web  Services,  Inc.  or  its  affiliates.  All  rights  reserved

Optimizing Cost and Efficiency on AWS

Michael Snyder Partner Development Manager / Cloud Economics Virtual Team

A Couple Assumptions…

1. You’re using AWS… 2. You like it!!

But maybe you are spending more than you planned…

Or you’d just like to spend less

Cost Optimization Is…

Going From:

•  Paying for what you use

To:

•  Paying for what you need

What should you do?

We’ll Talk Through Some…

Frameworks Tools Best Practices

…And

Some examples from other

customers like you

Cost Optimization Strategies: Policies and Processes

1. Limit Resource Provisioning…

By Controlling Who Can Provision Resources…

2. Understand What is Deployed and What it Costs…

By Employing Tags…

•  Key (Attribute): 127 Unicode characters

•  Value (Detail/Description): 255 Unicode characters

•  Tags per resource: 10 tags

Jane_Doe  

…And Using The Different Types of Tags Appropriately

Resource Tags

•  Provide the ability to organize and search within and across resources •  Filterable and Searchable •  Do not appear in Detail Billing Report

Cost Allocation Tags

•  Provide the ability to map AWS charges to organizational attributes for accounting purposes

•  Information presented in Detailed Billing Report and Cost Explorer (must be explicitly selected)

•  Only available on certain services or limited to components within a service (e.g. S3 bucket but not objects)

Tag Key Examples

Cost Center

Business Unit

Environ. Tier

Owner

Dept./ Group

Product / Application

Shutdown Time

Support Contact Endpoint

Backup

Customer Example

Large Financial Services Customer

“No tags? No instance”

3. Proactively Monitor Your Account Billing Usage…

By Using Detailed Billing Reports and Enabling Billing Alerts…

…And Configuring Simple…

…Or Advanced Alarms in CloudWatch…

…Alongside Cost Explorer

http://amzn.to/1zHE2Fj

Cost Explorer Example

We recently added the ability to budget. . .

. . . and forecast within cost explorer

…Or Using an AWS Partner Tool…

Customer Example – Kellogg

“CloudWatch helps our people make better decisions around the capacity they need, so that they can avoid waste…” “We were never able to do that with our on-premises infrastructure. AWS breaks down usage and cost to such a granular level that we can identify which costs come from which department, like a toll model.”

Best Practice: Manage How Resources are Provisioned and Monitored

•  Only allow specific groups or teams to deploy (certain) AWS resources

•  Create different environment (e.g. Dev/Test vs. Production) with different policies for each

•  Require tags in order to instantiate resources •  Monitor and send alerts or shut down instances improperly tagged •  Use CloudWatch to send alerts when billing thresholds are met •  Analyze your spend using AWS or Partner tools

Cost Optimization Strategies: Architecture and Design

4. Design for Elasticity Rather Than Deploy for Peak…

By Picking the Right Instance Type…

Instance Type

vCPU Mem (GiB)

Monthly Cost (OD)*

Ideal use case

m3.medium 1 3.75 $48.24 Always available, balanced m4.large 2 8 $90.72 Latest generation, always

available, balanced c4.large 2 8 $79.20 Always available, compute r3.large 2 15 $126.00 Always available, memory g2.xlarge 8 15 $468.00 Always available, GPU d2.xlarge 4 30.5 $496.80 Always available, storage t2.medium 2 4 $37.44 Bursty workloads

* Assumes Amazon Linux Instances in US-East at 720 hours per month

…And Determine if Bursting Works For You

•  2vCPU, 4 GiB RAM •  Baseline performance: 40% (of a single core) •  Bursts beyond this based on CPU credits •  Less than $40 per month •  Use Cases: Web servers, dev, small

databases •  Additional Details: http://amzn.to/1sl2bKa t2.medium

Customer Example – Nomura Research

For Nomura Research, the t2 instance provides enough performance for a development environment, remote desktop of evaluation environment requiring occasional CPU bursting

Customer Example – Kaplan

We quickly converted a hefty percentage of our systems to run under this EC2 Instance type, and have seen major cost reductions without affecting performance whatsoever. For all instances built for Kaplan moving forward, the T2 is going to be the preferred option unless measured or load-tested computing needs demand otherwise.

Using Autoscaling….

Automatic resizing of compute clusters based on demand

Trigger autoscaling policy

Feature Details

Control Define minimum and maximum instance pool sizes and when scaling and cool down occurs.

Integrated to Amazon

CloudWatch

Use metrics gathered by CloudWatch to drive scaling.

Instance types Run Auto Scaling for On-Demand and Spot Instances.

AWS autoscaling create-autoscaling-group — Auto Scaling-group-name MyGroup — Launch-configuration-name MyConfig — Min size 4 — Max size 200 — Availability Zones us-west-2c

…And Adjusting for Utilization and Granularity More smaller instances vs. less larger instances

29 m4.large @ $0.126/hr $2,630.88 / mo*

59 t2.medium @ $0.052/hr $2,203.20 / mo*

*Assumes Linux instances in US-East at 720 hours per month

Customer Example

Large Aerospace Customer

Challenge Workloads arrive asynchronously and require isolation

Solution Use Amazon SQS and Autoscaling Groups to launch / terminate instances

5. Identify Idle Resources and Turn Off Unused Instances…

…Using Trusted Advisor…

…Or Amazon CloudWatch to Monitor, Collect and Track Metrics…

Amazon CloudWatch

…Or (Again) Using an AWS Partner Tool…

Customer Example – Samsung

We are using AWS Trusted Advisor to improve cost efficiency and to audit the configurations of service platforms

Best Practice: Match Your Usage and Capacity

Start Choose an instance that best meets your basic requirements

Start with memory & then choose closest virtual

cores

Look for peak IOPS storage requirements

Tune Use CloudWatch and

Trusted Advisor to assess

Change instance size up or down based upon

monitoring

Expand Run multiple instances in multiple Availability

Zones

Use Autoscaling to scale up and down based on

demand and usage (e.g. spikes)

6. Architect Your Workload with Cost in Mind

Select Reserved Instances for Steady State Workloads…

Commitment Level •  1 Year •  3 Year AWS Services Offering RIs •  Amazon EC2 •  Amazon RDS •  Amazon DynamoDB •  Amazon Redshift •  Amazon ElastiCache

* Dependent on specific AWS Service, size/type and Region

Or Spot Instances for Non-Stateful (Time Insensitive or Fault Tolerant) Workloads…

Minimum Commitment •  Commit to 1 hour

Tradeoff •  Potential for interruption

* Compared to On Demand price based on specific EC2 instance type, region and availability zone

…Or A Combination of All Three

1.  Start by using RIs for known/steady-state workloads

2.  Set-up multiple autoscaling groups

3.  Autoscale first using Spot first 4.  If Spot instances are

unavailable (or priced too high), use On-Demand

0

2

4

6

8

10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

/Spot Instances

On Demand Spot Reserved Instance

And When You Have Excess RIs…

Use the Amazon EC2 Reserved Instance Marketplace

http://amzn.to/1FkzUZp

Customer Example – Novartis

Goal: Screen 10 million compounds against a common cancer target in < 1 week Set Up: 10,600 AWS Instances (39 drug design years in 11 hours) Result: 3 promising compounds Cost: $4,232

Leverage The Right Storage Classes…

AWS Cloud

Amazon Glacier

Gateway Appliance/ AWS Storage Gateway

Amazon S3

Block File

On-premises Data Center

Archive Backup Disaster Recovery

Amazon EBS

•  Amazon S3 Reduced Redundancy ‒  99.99% durability vs. 99.999999999% ‒  Up to 20% savings ‒  Great for everything that is easy to

reproduce

•  Amazon Glacier ‒  Same durability as S3 ‒  3 to 5 hours restore time ‒  Up to 65% savings ‒  Great for archiving, long-term backups

and old data Amazon EFS (Preview)

…Alongside AWS Managed or Application Services…

Elastic Load Balancing

(ELB)

Amazon Relational Database Service

(RDS)

Amazon ElastiCache

Amazon DynamoDB

Amazon Simple Queue Service

(SQS)

Amazon Simple Email Service

(SES)

Amazon Lambda

Amazon Elastic MapReduce

(EMR)

Amazon Simple Notification Service

(SNS)

Amazon Kinesis

Amazon Route 53

Amazon Redshift

To Offload Your Architecture…

+

Standard Setup

•  4 x Medium Instances $193

•  AWS Data Transfer 1 TB $92

•  Total = $285

Optimized •  1 x Medium Instance

$48 •  CloudFront Data 1 TB

$87 •  CloudFront Requests (10M)

$7.5 •  Total = $142.5

50%

6X

Cheaper

Faster

Customer Example – Infospace

•  Chooses the right instance types (using Cloudwatch)

•  Uses Reserved Instances (reduced monthly costs by 28%)

•  Monitors and turns off unused instances (own tool – Junkyard Dog)

•  Offloads architecture by moving to Cloudfront

•  Leverages App services: ELB, SNS, SES

•  Uses Trusted Advisor •  Moves Data warehouse to Redshift

Cost Optimization Strategies: Technology Updates

7. Be Cognizant of Technology Lifecycle Updates

Including…

•  New Instance Types/Families (e.g. m4s)

•  New Technologies (e.g. Amazon RDS for Aurora, AWS Service Catalog)

New Prices

…And Remember to Use Consolidated Billing •  Receive a single bill for all

charges incurred across all linked accounts ‒  Share RI discounts ‒  Combine tiering benefits /

Volume discounts •  View & manage linked accounts •  Add additional accounts

Best Practice: Pull all Levers Available When Architecting Your Solution

•  Utilize On-Demand, Reserved and Spot Instances •  Use the Amazon EC2 RI Marketplace when you have excess Ris •  Use the appropriate storage class based on your requirements (not

on what you use today) •  Use micro services where possible in your architecture •  Review your architecture when new services or technologies are

announced •  Use consolidated billing to take advantage of tiered pricing

Cost Optimization Strategies – Putting It All Together

Frameworks

ü  Limit Resource Provisioning ü  Understand What is Deployed and

What it Costs ü  Proactively Monitor Your Account

Billing Usage ü  Design for Elasticity Rather Than

Deploy for Peak ü  Identify Idle Resources and Turn

Off Unused Instances ü  Architect Your Workloads with

Cost in Mind ü  Be Cognizant of Technology

Lifecycle Updates

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