Learn how to optimise your AWS bill by using Amazon EC2 Spot instances, AWS Savings plans and blended on-demand/spot pools for your AWS Autoscaling groups. Also includes some easy wins to help you get started.

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Cost optimisation onAWS
O n l i n e W e b i n a r – 2 0 2 0 / 0 4 / 0 9
Cobus Bernard
Sr Developer Advocate
Amazon Web Services
@cobusbernard
cobusbernard
cobusbernard

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Amazon EC2 instance characteristics
M5d.xlarge
Instance family
Instance
generation
Instance size
Instance type
CPU
Memory
Storage
Network performance
Additional
capabilities

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Broadest and deepestplatformchoice
Workloads Capabilities Options
(AWS, Intel, AMD)
(up to 4.0 GHz)
(up to 24 TiB)
(HDD and NVMe)
(up to 100 Gbps)
(GPUs and FPGA)
(Nano to 32xlarge)
+ + =
270+instance types

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Amazon EC2 general-purpose instances
M5
instances
Balance of compute, memory, and network
resources
4:1 memory-to-vCPU ratio
A1
instances
Workloads that can scale out across multiple cores,
fit within memory, and run on ARM instructions
T3
instances
Baseline level of CPU performance with the ability to
burst above the baseline for workloads that don’t
require sustained performance

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Amazon EC2 memory-optimized instances
R5
instances
Accelerate performance for workloads
that process large datasets in memory
8:1 memory-to-vCPU ratio
High-memory
instances
Extreme memory needs
Certified to run SAP HANA
From 6 to 24 TB of memory
X1 and
X1e
instances
For memory-intensive workloads and
very large in-memory workloads
16:1 and 32:1 memory-to-vCPU ratios

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Amazon EC2storage-optimized instances
I3/I3en
instances
I/O optimized for high-transaction workloads,
low-latency workloads
H1
instances
Designed for applications that require low cost,
high-disk throughput and high-sequential-disk I/O
access to very large datasets
More vCPUs and memory per TB of disk than D2
D2
instances
Lowest cost per storage ($/GB)
Supports high-sequential-disk throughput
D2

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Amazon EC2acceleratedcomputing instances
GPU compute instances for use cases including deep learning training,
HPC simulations, financial computing, and batch rendering
Feature latest NVIDIA high-end GPUs including Volta V100
Customer programmable FPGAs that provide dramatic
performance improvements for applications such as financial
computing, genomics, accelerated search, and image processing
Feature Xilinx Virtex UltraScale+ VU9P FPGAs in a single instance
Programmable via VHDL, Verilog, or OpenCL
GPU graphics instances designed for workloads such as 3D rendering,
remote graphics workstations, video encoding, and AR/VR
Feature NVIDIA midrange GPUs such as Turing T4 GPUs, with GRID
Virtual Workstation features and license
P series
P2/P3 instances
G series
G3/G4 instances
FPGA
instances
F1 instances

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Instance Discovery
New search and discovery experience
to easily find EC2 instance types
Quicker and easier for you to find and compare
different instance types and project costs
Announcing

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13. Amazon EC2CostOptimisation non-prod
100.0
71.4
35.7
29.8
0
20
40
60
80
100
24 x 7 24 x 5 12 x 5 10 x 5
% RunningTime
Up to 70%
savings for non-
production
workloads

14. AWS InstanceScheduler
• AWS-provided solution
• Custom start & stop schedules
• Works with EC2 & RDS instances
• Deploy using CloudFormation
• Selectively tag instances to schedule
• Multiple schedules per instance
• 5-minute granularity
https://aws.amazon.com/answers/infrastructure-
management/instance-scheduler/

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16. VPC Endpoints
• Egress traffic incurs a cost
• UseVPC Enpoints for:
• S3
• DynamoDB
https://docs.aws.amazon.com/vpc/latest/userguide/v
pc-endpoints.html

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SavingsPlans
Easy to use
Receive discounted rates
automatically in exchange
for a monetary commitment
Flexible
Make a single commitment that
applies across multiple AWS compute
services, even as
your requirements change
Significant discounts
Select from two types of Savings Plans to
receive discounts of up
to 72% on EC2 Instance Savings Plans and
66% on Compute Savings Plans
Flexible purchase option that offers up to 72% discounts
on Amazon EC2 and AWS Fargate usage

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TypesofSavings Plans
Provide the lowest prices, up to 72% off (same
as Standard RIs) on the selected instance family (e.g., C5
or M5), in a specific AWS Region
Offer the greatest flexibility, up to 66% off
(same prices as Convertible RIs)
Flexible
across
 Instance family: e.g., Move from C5 to M5
 Region: e.g., Change from EU (Ireland) to EU
(London)
 OS: e.g.,Windows to Linux
 Tenancy: e.g., Switch Dedicated tenancy to Default
tenancy
 Compute options: e.g., Move from EC2 to Fargate
Flexible
across
 Size: e.g., Move from m5.xl to m5.4xl
 OS: e.g., Change from m5.xlWindows to
m5.xl Linux
 Tenancy: e.g., Modify m5.xl Dedicated to
m5.xl Default tenancy
Compute
Savings Plans
EC2 Instance
Savings Plans

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Getting startedwithSavingsPlans
Review your Savings Plans
recommendations in AWS
Cost Explorer
Customize
recommendations based
on your needs (type of
Savings Plan, payment
option,
term length)
Review hourly commitment
(e.g., $10/hr) and add to cart
Eligible Amazon EC2 and
AWS Fargate usage is
charged at a discounted
Savings Plans rate up to
your commitment level
AWS Cost Explorer guides you through the purchasing process
Just like RIs, you can purchase Savings Plans via the RI operations team

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Low utilization
High utilization
Opportunity: Mostinstancesaren’tverybusy

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AWSComputeOptimizer
Recommends optimal instances for Amazon EC2 and Amazon EC2 Auto Scaling
groups from 140+ instances from M, C, R,T, and X families
Applies insights Saves timeLower costs
performance

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Simplifyingcompute optimization
AWS Compute
Optimizer
Identify optimal
AWS compute resources
for your workloads
Mettle scans yourAWS
infrastructure and uses
machine learning to
automatically identify
optimalAWS resources
for your workloads
Identifies workload
characteristics and profile
based on the data
gathered
Matches the resource
requirements of your
workloads to optimalAWS
resources with
recommendations
Amazon
CloudWatch
metrics
EC2 Instance
EC2 Auto Scaling
groups
Helps you visualize
what-if scenarios based
on the recommended
resources
AWS resources
metadata

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Easytochoose withAWSComputeOptimizer
New services that recommend optimal AWS compute resources to reduce costs up to 25%
Recommends optimal EC2 instances
Optimizes performance and reduces costs by
making recommendations to help you right-
size compute to your workloads
Analyzes Amazon CloudWatch metrics and
considers Auto Scaling group configuration for
intuitive and actionable recommendations
Up to three recommendations per workload
Available at no additional charge

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OptimizingAmazon EC2costand capacity
Pricing Capacity
Capacity management
made easy on the broadest
and deepest compute
platform

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the second
Amazon EC2purchaseoptions
savings of up to 90%a significant discount more
flexibility

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TooptimizeAmazon EC2,combine purchaseoptions
RIs or a Savings Plan
Spot for fault-tolerant,
flexible, stateless workloads
On-Demand

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Capacity
Interruptions only
happen if OD
needs capacity
Pricing
Smooth, infrequent changes,
more predictable
Instances
Same infrastructure as
On-Demand and RIs
Usage
Choose different instance
types, sizes, and AZs in
a single fleet or EC2 Auto
Scaling group
Pricing is based on long-term supply and demand trends; no bidding!
Saveup to 90%using EC2Spot Instances

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Low, predictable prices
Up to 90% discount over On-Demand prices
Faster results
Increase throughput up to 10x while staying in budget
Easy to use
Launch through AWS services (e.g.,Amazon ECS,Amazon EKS,AWS
Batch,Amazon SageMaker,Amazon EMR) or integrated third parties
WhySpot Instances?

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FlexibilityiskeytosuccessfulSpotusage
Instance flexible Time flexible Region flexible

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Minimal interruptions
Check for 2-minute interruption notification via instance
metadata orAmazonCloudWatch events, and automate by
 Checkpointing
 Draining from ELB
 Using stop-start and hibernate to restart faster
InterruptionhandlersforAmazonECSandAmazonEKS
Amazon Elastic
Kubernetes Service
(Amazon EKS)
 Connection between termination requests from AWS infrastructure to nodes
 Tasks running on Spot Instances will automatically be triggered for shutdown before
the instance terminates, and replacement tasks will be scheduled elsewhere on the
cluster
Amazon Elastic
Container Service
(Amazon ECS)
HandlingSpot interruptions
Less than 5% of Spot Instances were interrupted in the last 3 months

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OptimizingAmazon EC2costand capacity
Pricing
Achieve optimal
price/performance
with different
purchase models
Capacity

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UsingAmazon EC2AutoScaling
Automatically scale instances across instance families
and purchase options in a single ASG to optimize cost
Capacity-optimized
Prioritize deploying Spot Instances into greater Spot pool capacity
order to lower the chance of interruptions
Lowest cost
Prioritize cost by selecting a mix of On-Demand and Spot Instances
to launch based on the lowest available price
Prioritized list
Use a prioritized list for On-Demand instance types to scale capacity
during an urgent, unpredictable event to optimize performance
Amazon EC2
Auto Scaling
AZ1 and AZ2
https://ec2spotworkshops.com/running-amazon-ec2-workloads-at-scale.html

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Amazon EC2Spot Instancepools explained
$0.27 $0.29$0.50
1b 1c1a
8XL
$0.30 $0.16$0.214XL
$0.07 $0.08$0.082XL
$0.05 $0.04$0.04XL
$0.01 $0.04$0.01L
C4
$1.76
On
demand
$0.88
$0.44
$0.22
$0.11
Each instance family
Each instance size
Each availability zone
In every Region
Is a separate Spot pool
R5
M4
M5
I3 C5R4
i3en R5a
R5d

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ASG capacity-optimizedallocation strategy
us-east-1a
Desired capacity: 12
SpotAllocationStrategy: capacity-optimized
OnDemandBaseCapacity: 0 OnDemandPercentageAboveCapacity: 0
r5.large
m4.large
m5.large
R5 R5
R5 R5
us-east-1b us-east-1c
Overrides: [“r5.large”, “m4.large”, ”m5.large”]
$$
$
$$$
r5.large
m4.large
m5.large
$$$
$$
$
r5.large
m4.large
m5.large
$
$$$
$$

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ASG lowest-priceallocationstrategy
us-east-1a
Desired capacity: 12
SpotAllocationStrategy: lowest-price
OnDemandBaseCapacity: 0 OnDemandPercentageAboveCapacity: 0
r5.large
m4.large
m5.large
R5 R5
R5 R5
us-east-1b us-east-1c
Overrides: [“r5.large”, “m4.large”, ”m5.large”]
$$
$
$$$
r5.large
m4.large
m5.large
$$$
$$
$
r5.large
m4.large
m5.large
$
$$$
$$

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TooptimizeAmazon EC2,combine purchaseoptions
RIs or a Savings Plan
Spot for fault-tolerant,
flexible, stateless workloads
On-Demand

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Before:MultipleASGstouseSpot,On-Demand,andRIstogether
m4.large SpotASG Min: 1 Max: 10
m5.large Spot ASG Min: 1 Max: 10
c4.xlarge O-D ASG Min: 1 Max: 10
Availability
Zone 1
Availability
Zone 2
Availability
Zone 3
Before, with three
ASGs
—one for each
instance type/
purchase option

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Then:Spot,On-Demand,andRIsinasingleASG
m4.large Spot Instances
m5.large Spot Instances
c4.xlarge On-Demand instances
The new way
combines purchase
options, instance
types, and AZs in
a singleASG
SingleASGAvailability
Zone 1
Availability
Zone 2
Availability
Zone 3

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m4.xlarge Spot
Weight of 1
m4.2xlarge Spot
Weight of 2
m4.4xlarge On-Demand
Weight of 4
Availability
Zone 1
Availability
Zone 2
Availability
Zone 3
Different
instance types
contribute
differently to
total capacity
Now:Spot,On-Demand,andRIsinasingleASGwithweights

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Amazon EC2Spot Instancepools explained
$0.27 $0.29$0.50
1b 1c1a
8XL
$0.30 $0.16$0.214XL
$0.07 $0.08$0.082XL
$0.05 $0.04$0.04XL
$0.01 $0.04$0.01L
C4
$1.76
On
demand
$0.88
$0.44
$0.22
$0.11
16
Weight
8
4
2
1
$0.11
Weighted
price
$0.11
$0.11
$0.11
$0.11
$0.017 $0.018$0.032
1b 1c1a
$0.038 $0.02$0.032
$0.016 $0.02$0.021
$0.025 $0.04$0.02
$0.01 $0.04$0.01

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APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

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APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

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APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

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APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

48. © 2020, Amazon Web Services, Inc. or its affiliates. All rights reserved.
APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

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APIparameters
"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": "MyLaunchTemplate"
},
"Overrides": [
{
"InstanceType": "m4.xLarge",
"WeightedCapacity": "1"
},
{
"InstanceType": "m4.2xLarge",
"WeightedCapacity": "2"
},
{
"InstanceType": "m4.4xLarge",
"WeightedCapacity": "4"
}
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 10,
"OnDemandPercentageAboveBaseCapacity": 50,
"SpotAllocationStrategy": “capacity-optimized",
"SpotInstancePools": 2
}
}
AZ1 and AZ2
Desired
Min
Max
On-Demand base
50% On-Demand
50% Spot
Minimum On-Demand (10)

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Worker fleetreference architecture
Producer node (OD or RI) Producer node (Spot)
Producer fleet
Amazon EC2 Auto
Scaling
Consumer node
(OD or RI)
Consumer node (Spot)
Consumer fleet
Amazon EC2 Auto
Scaling
Amazon Simple
Queue Service

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"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": ”MyLaunchTemplate"
},
"Overrides": [
{ "InstanceType": "m4.4xlarge" },
{ "InstanceType": "m5.4xlarge" },
{ "InstanceType": "c5d.4xlarge" },
{ "InstanceType": "m5d.4xlarge" },
{ "InstanceType": "c4.4xlarge" }
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 0,
"OnDemandPercentageAboveBaseCapacity": 30,
"SpotAllocationStrategy": "lowest-price",
"SpotInstancePools": 2
}
}
Producer fleetconfiguration
AZ1 and AZ2
Desired – 50
Min – 20
Max – 80
30% On-Demand (15)
70% Spot (35)

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"MixedInstancesPolicy": {
"LaunchTemplate": {
"LaunchTemplateSpecification": {
"LaunchTemplateName": ”MyLaunchTemplate"
},
"Overrides": [
{ "InstanceType": "m4.4xlarge" },
{ "InstanceType": "m5.4xlarge" },
{ "InstanceType": "c5d.4xlarge" },
{ "InstanceType": "m5d.4xlarge" },
{ "InstanceType": "c4.4xlarge" }
]
},
"InstancesDistribution": {
"OnDemandAllocationStrategy": "prioritized",
"OnDemandBaseCapacity": 250,
"OnDemandPercentageAboveBaseCapacity": 0,
"SpotAllocationStrategy": "lowest-price",
"SpotInstancePools": 2
}
}
Consumer fleetconfiguration
AZ1 and AZ2
Minimum On-Demand (250)
Min – 200
Max – 350
On-Demand Base – 250
0% On-Demand (0)
100% Spot (50)
Desired – 300

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Machine learning
DevOps—CI/CD
Websites and web applications
Workloads
onAWS

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Machinelearning (ML)
Get ML solutions to market faster with access to built-in algorithms,
ML frameworks, and custom models
Save up to 90% in training costs with
managed spot training
Automatically manages Spot capacity
on your behalf
All instance types, training models,
and configurations
Amazon SageMaker
managed spot training

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Machine learning
DevOps—CI/CD
Websites and web applications
Workloads
onAWS

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DevOps—CI/CD
Or, run Jenkins build jobs inside your Kubernetes
clusters and cost-optimize with Spot node groups
https://ec2spotworkshops.com/amazon-ec2-spot-cicd-workshop.html

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CI/CDreference architecture
https://github.com/awslabs/ec2-spot-jenkins-plugin/
Users Application
Load Balancer
Jenkins master
(OD or RI)
Jenkins master
(OD or RI)
Jenkins agent
(Spot)
Jenkins agent
(Spot)
Spot fleet
Availability Zone B
Availability Zone A
VPC
Jenkins agent
(Spot)
Jenkins agent
(Spot)

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Machine learning
DevOps—CI/CD
Websites and web applications
Workloads
onAWS

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Websitesand web applications
Run web services ranging from ad servers to real-time bidding servers
Deploy web applications or services on containers and scale clusters at a fraction of the cost
Use Auto Scaling with Amazon ECS or Amazon EKS to run any containerized workload, including a web
application
Amazon EC2 Auto
Scaling
Amazon Elastic
Container Service
Amazon Elastic
Kubernetes Service
Scale in real time, pay per second, save up to 90%
AWS
Fargate

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Running webapplications withAmazon ECSon
EC2Spot
Session state data
Availability Zone A
Availability Zone B
Amazon EC2
Auto Scaling
ECS
container 1
ECS
container 2
ECS
container 1
ECS
container 2

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AWS FargatewithEC2Spot
Up to 70% off over regular Fargate
tasks
Only pay for the resources you use by
automatically scaling based on tasks,
vCPUs, and memory
VM-level isolation by design
Run containers without managing servers or clusters
AWS Fargate

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Key takeaways
Experiment and test at
a lower cost to
innovate faster
1
How to automate
cost and capacity
optimization
2
Optimize your
workloads by using best
practices
3
Spot Instances Auto Scaling and
Savings Plans
AWS Compute
Optimizer

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LearncomputewithAWSTrainingandCertification
20+ free digital courses cover topics related to cloud compute,
including introduction to the following services:
Resources created by the experts at AWS to help you build cloud compute skills
Compute is also covered in the classroom offering, Architecting on
AWS, which features AWS expert instructors and hands-on activities
• Amazon Elastic Compute Cloud
(Amazon EC2)
• Amazon EC2 Auto Scaling
• AWS Systems Manager
• AWS Inferentia and Amazon EC2 Inf1
instances
Visit the learning library at https://aws.training

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Cobus Bernard
Sr Developer Advocate
Amazon Web Services
@cobusbernard
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