High performance and cost optimised need not be an oxymoron in AWS. In this session we will focus on practical ways to build efficient, high performance architectures. We will focus on how to pick the most appropriate service and resources, understand trade-offs, and reduce costs over time.

1. S U M M I T
SYDNEY

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Running lean: Performant yet
cost optimised
Louay Shaat
Solutions Architect
Amazon Web Services

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Meet the “Unicorn Company”
A mission for a better experience

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The strategy
A new digital experience
• Small innovation budget

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Meet the team
Better user
experience
Increase
deployments
Budget
constraint
Time
constraint
Resource
constraint
Utilise cloud
performance
CxO
Leadership Team
Architect
DevOps Lead

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Two fundamental areas of focus
Architect the
traditional way
Architect cloud
native apps
Proprietary/
COTS
Tightly coupled
Complex to
scale
Open source
Loosely coupled
Cloud native

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Why cloud native?
Users: Unknown
Data volume: TB–PB–EB
Locality: Global
Performance: Milliseconds–microseconds
Access: Web, mobile, IoT, devices
Social mediaRide hailing Media streaming Dating

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Phase 1 – Proof of value
Amazon EC2
Instance
MSSQL
Amazon
ElastiCache
(Redis)
DB
Instance

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Phase 2 – Live system
Microsoft SQL RDS
EC2 Auto
Scaling
Amazon EC2
Instance 1
Amazon
ElastiCache
Redis
Amazon
ElastiCache
Redis
Redis
Cluster
Amazon EC2
Instance 1
Primary
Slave

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What is the right compute option?
Amazon EC2
Virtual server in the cloud
Amazon ECS,
EKS, and Fargate
Container in the cloud
AWS Lambda
Serverless compute

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Phase 2 – Live system – Compute optimised
Microsoft SQL RDS
ECS Auto
Scaling
Amazon
ElastiCache
Redis
Amazon
ElastiCache
Redis
Redis
Cluster
Amazon ECS
container 1
Amazon ECS
Container 2
Primary
Slave

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What is the right Database option?
Relational Key-value Document In-memory Graph Time-series Ledger
Amazon
DynamoDB
Amazon
Neptune
Amazon RDS
Aurora CommercialCommunity
Amazon
Timestream
Amazon
QLDB
Amazon
ElastiCache
Amazon
DocumentDB

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Database use cases
Relational
Referential
integrity
Key-value
High
throughput and
low-latency
Document
Store
documents
In-memory
Query by key
Graph
Navigate
relationships
between
data
Time-series
Collect, store,
and process
data sequenced
by time
Ledger
immutable, and
verifiable
application data
Lift and shift, ERP,
CRM, finance
Shopping cart,
Social and Product
catalog
Content mgmt
and mobile
Leaderboards,
and real-time
analytics
Fraud detection
and
recommendation
engine
IoT applications,
event tracking
supply chain and
health care

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Phase 2 – Live system – Backend optimised
Amazon Aurora RDS Serverless
Amazon ECS
Auto Scaling
Amazon
ElastiCache
Redis
Amazon
ElastiCache
Redis
Redis
Cluster
Amazon ECS
container 1
Amazon ECS
container

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Optimise your compute purchase
Spot
On-Demand

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Multiple instance types and purchase options
Use all three purchase options to
optimise costs
Automatic optimisation behind the
scenes with machine learning

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What does it mean?
Availability
Zone 1
Availability
Zone 2
Availability
Zone 3
m4.large Spot
Instances
m5.large Spot
Instances
c4.xlarge On-
Demand instances
m4.large Spot
Instances
m5.large Spot
Instances
c4.xlarge On-
Demand instances
m4.large Spot
Instances
m5.large Spot
Instances
c4.xlarge On-
Demand instances
Single
ASG

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Phase 2 – Live System – Purchase optimised
Amazon Aurora RDS Serverless
Amazon ECS
Auto Scaling
Amazon
ElastiCache
Redis
Amazon
ElastiCache
Redis
Redis
Cluster
Amazon ECS
container 1
Amaozn ECS
container 1

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Predictive scaling in EC2 Auto Scaling
Provisioned Capacity
Actual Capacity Demand
Machine
learning model
Billions of data points
from Amazon.com
Capacity provisioning with Dynamic Scaling
Time
Load/Capacity
Capacity provisioning with Predictive Scaling and Dynamic Scaling
Time
Load/Capacity

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Phase 2 – Live System – Pattern optimised
Amazon Aurora RDS Serverless
Predictive
auto scaling
Amazon
ElastiCache
Redis
Amazon
ElastiCache
Redis
Redis
Cluster
Amazon ECS
container 1
Amazon ECS
container 1

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Summary of architectural transformations
Start with the basics (design for cloud native)
Compute optimisation
Footprint
optimisation
Better
Scalability
Backend optimisation
Cost/licensing
Optimisation
Better
Scalability
TCO
Reduced
operational
costs
No licensing
costs
Architected for
microservices
Scale as we
grow

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How to run leaner

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Tagging strategy
• Application ID
• Environment
• Opt In/Out
• Owner
• Business Unit

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Some tips
and

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Related breakouts
Understanding complexity and how it impacts innovation
Tyson Nutt
Right tool for the right job: the journey beyond relational databases
Syed Jaffry
The art of successful failure
Becky Weiss

33. Thank you!
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Louay Shaat
lshaat
lshaat