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Page 1: Optimizing Costs and Efficiency of AWS Services

Chicago

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

Enterprise Pre-Day

Page 2: Optimizing Costs and Efficiency of AWS Services

Do you • Wear green eye-shades? • Work from the console?

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You’re using AWS. You like it.

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But maybe you are spending more than you planned

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Or you’d just like to spend less

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What should you do?

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How about some

frameworks

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Some tools

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Some best practices

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And some examples from other customers

like you

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How are you controlling the provisioning of

resources?

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Control who can provision resources

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Require tagging

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“No tags? No instance” – Large financial services customer in Boston

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Best practices: • Control who can provision

resources via IAM • Require tagging

– Inspect – Stop instances without tags

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Savings potential

100% if you don’t start instances you don’t need!

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Are you identifying and terminating idle

resources?

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How do I identify idle resources?

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AWS Trusted Advisor runs 100+ configuration

checks and recommends savings

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Trusted Advisor Demo

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We are using AWS Trusted Advisor to improve cost efficiency and to audit

the configurations of service platforms

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Trusted Advisor

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How do I handle demand spikes?

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Design for elasticity rather than deploy for

peak

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Use Auto Scaling or queue-based approaches

to add resources when needed, and turn them

off when not

Amazon SQS Queue

Auto Scaling

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Problem: Workloads arrive asynchronously and require isolation

Solution: Amazon

Simple Queue Service and launch/

termination of instances

Amazon SQS

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Problem: How to scale up to accommodate sudden traffic

spikes?

Solution: Auto Scaling Auto Scaling

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Auto Scaling real world example •  Baseline traffic: 300+ thousand pages / hour

130 TB/month outbound traffic •  Peak: 2.0+ million pages / hour (~7x baseline)

•  Architectural changes: e.g., move from local SSDs to provisioned IOPS needed due to this scale

•  Auto Scaling provides 23% savings over three years

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Best practices •  Identify idle resources using Trusted

Advisor •  Turn them off

•  Design to scale up and scale down using Auto Scaling or a queue-based approach

•  Match your usage and capacity — don’t pay for idle resources!

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Are you using the most cost-effective

instances or resources?

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Match resources to

workload

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How can I tell if there’s a match or mismatch?

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Use Amazon CloudWatch to

collect and track metrics

CloudWatch

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Amazon CloudWatch monitoring Basic •  7 metrics for Amazon EC2

including: –  CPU utilization –  Data transfer –  Disk usage and more

•  5-minute frequency •  Metrics for Amazon EBS,

Amazon DynamoDB, Amazon RDS, etc.

Detailed •  1-minute frequency •  Aggregation by instance type and

AMI

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Why does this matter?

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Different instances cost different amounts

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Instance families: Example Instance vCPU Mem

(GiB) Monthly price (3-yr AURI )

Ideal use case

c4.2xlarge 8 15 $125.44 Best price-compute performance

m4.2xlarge 8 32 $137.25 Balanced

r3.2xlarge 8 61 $179.25 Lowest cost per GiB RAM

r3.xlarge 4 30.5 $89.61 Lowest cost per GiB RAM

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Do you need continuous compute

or does bursting work for you?

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t2.medium •  4 GiB RAM •  Baseline performance: 40% •  Bursts beyond this based on CPU

credits •  Less than $17 per month •  Details: http://amzn.to/1sl2bKa •  Web servers, dev, small databases

t2

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m3.medium

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t2.medium (bursting)

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Cloudwatch: CPU Utilization

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t2 vs m3.medium or c4.large Instance vCPU Mem

(GiB) Monthly price (3-yr AURI )

Ideal use case

m3.medium 1 3.75 $19.08 Always available, balanced

c4.large 2 3.75 $31.36 Always available, compute

t2.medium 2 4 $16.86 Bursty workloads

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Consider switching to a t2?

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Guidance •  Inspect your workloads (use CloudWatch!) •  Can your workload run on a t2? •  If not, is it memory intensive? àr3 •  Is it compute intensive? à c4

•  Others to consider: –  i2 for storage-optimized –  g2 for GPU

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Savings potential If t2 works for you •  11%: Switch from m3.medium to t2.medium •  46%: Switch from c3.large to t2.medium Instance optimization •  9%: Switch to c4 for compute-intensive apps

(m4.2xl -> c4.2xl) •  35%: Switch to r3 for memory-intensive apps

(m4.2xl -> r3.xlarge)

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Best practices: 1. Monitor instances with CloudWatch 2. Switch to t2 as possible 3. Use compute- and memory-focused instances as needed

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Do you need long-term storage?

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Amazon Glacier Extremely low-cost cloud

storage service

Amazon Glacier

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Are you purchasing in the most cost-

effective way?

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Commitment and spot save $

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Use Reserved Instances if possible:

Up to 60% savings + capacity reservation

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AWS Trusted Advisor identifies savings

attainable via Reserved Instancess

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Reserved Instance Marketplace

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Use Spot Instances for non-stateful workloads

Pricing starts

at 90% off

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Novartis, Cycle Computing & AWS Spot Instances

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Goal: Screen 10 million compounds

against a common cancer target in < 1 week

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10,600 AWS instances

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39 drug design years in 11 hours

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3 promising compounds identified

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Cost of $4,232

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Savings potential • ~40%: 1-Year Reserved

Instances • ~60%: 3-Year Reserved

Instances • Up to 90%: Spot Instances

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Could you save by letting AWS do more

work for you?

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Focus on what you do best

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Let AWS solve other problems for you

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AWS’s higher-level services automate your work and save

you money CloudFront

DynamoDB

Amazon RDS

ElastiCache

Amazon Redshift

Amazon EMR

Amazon Kinesis

Amazon WorkSpaces

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Are you modeling and monitoring your

spend?

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https://calculator.s3.amazonaws.com/index.html

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Detailed billing reports and

cost insights

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Detailed Billing Reports http://amzn.to/1swNwLV

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Cost Explorer http://amzn.to/1zHE2Fj

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Cost Explorer Demo

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Forecasting Demo

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Budgeting Demo

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Demo

CloudWatch

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•  Control and verify •  Design for elasticity •  Match resources and

workload •  Purchase for savings •  Use application

services •  Model and track

Frameworks to remember

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Tools to use •  IAM, AWS console •  Auto Scaling,

Amazon SQS •  Amazon CloudWatch •  AWS Trusted Advisor •  Detailed billing reports

and Cost Explorer •  Partners

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•  Turn off untagged resources •  Stop idle instances •  Use instances matched to task

and less expensive ones •  Baseload with RIs •  Use Spot Instances for non-

stateful workloads •  Model and track spending

Best practices

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Chicago

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

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