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Clifford Duke, Solutions Architect
2019-04-29
AWS Quick Start
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AWS Purpose-Built Database Strategy:
The Right Tool for the Right Job
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The Database Market is Changing
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Traditional Database Architecture
App/Web Tier
Client Tier
RDBMS
one database for
all workloads
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• key-value access
• complex queries
• transactions
• analytics
Traditional Database Architecture
App/Web Tier
Client Tier
RDBMS
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Data categories and common use cases
Relational Key-value Document In-memory Graph
Referential
integrity, ACID
transactions,
schema-
on-write
Low-latency,
key lookups
with high
throughput and fast
ingestion
of data
Indexing and
storing
documents with
support for
query on any
attribute
Microseconds
latency, key-based
queries, and
specialized data
structures
Creating and
navigating
data relations
easily and quickly
Lift and shift, EMR,
CRM, finance
Real-time bidding,
shopping cart, social
Content
management,
personalization,
mobile
Leaderboards,
real-time analytics,
caching
Fraud detection,
social networking,
recommendation
engine
Search
Indexing and
searching semi-
structured logs and
data
Product catalog,
help and FAQs,
full text
Time-series Ledger
Collect, store, and
process data
sequenced by time
IoT applications,
event tracking
Complete,
immutable, and
verifiable history of
all changes to
application data
Systems
of record, supply
chain, health
care,
registrations,
financial
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Application Architecture is Changing
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Microservices at Amazon
Service-Oriented Architecture
(SOA)
Single-purpose
Connect only through APIs
Connect over HTTPS
“Microservices”
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Monolithic vs. SOA vs. Microservices
SOA
Coarse-grained
Microservices
Fine-grained
Monolithic
Single Unit
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Microservices…
Eliminates any long-term commitment to a technology stack
Polyglot ecosystem
Polyglot persistence
• Decompose Databases
• Database per microservice pattern
Allows easy use of Canary and Blue-Green deployments
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Purpose-Built Databases
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Redshift
Data warehousing
EMR
Hadoop + Spark
Athena
Interactive analytics
Kinesis Data Analytics Real
time
Elasticsearch Service
Operational Analytics
RDS
MySQL, PostgreSQL, MariaDB,
Oracle, SQL Server
Aurora
MySQL, PostgreSQL
QuickSight SageMaker
DynamoDB
Key value, Document
ElastiCache
Redis, Memcached
Neptune
Graph
Timestream
Time Series
QLDB
Ledger Database
S3/Glacier
Glue
ETL & Data Catalog
Lake Formation
Data Lakes
Database Migration Service | Snowball | Snowmobile | Kinesis Data Firehose | Kinesis Data Streams
Data Movement
Analytics Databases
Business Intelligence & Machine Learning
Data Lake
Managed
Blockchain
Blockchain
Templates
Blockchain
RDS on VMware
DocumentDB
Document
Our portfolio
Broad and deep portfolio, purpose-built for builders
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AWS: Purpose-built databases
Relational Key-value Document In-memory Graph Search
Amazon
DynamoDB
Amazon
Neptune
Amazon RDS
Aurora CommercialCommunity
Amazon
ElastiCache
Amazon
Elasticsearch
Service
Amazon
DocumentDB
Time-series Ledger
Amazon
Timestream
Amazon
Quantum
Ledger
Database
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Relational Databases
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Amazon RDS
Managed relational database service with a choice of popular database engines
Easy to administer
No need to provision
infrastructure, install, and
maintain DB software
Highly scalable
Scale DB compute and storage
with a few clicks; minimal
downtime for your application
Available & durable
Automatic Multi-AZ
data replication;
automated backup, snapshots,
and failover
Fast & secure
SSD storage and
guaranteed provisioned
I/O; data encryption at rest and
in transit
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Amazon Aurora
MySQL and PostgreSQL compatible relational database built for the cloud
Performance and availability of commercial-grade databases at 1/10th the cost
Performance
& scalability
5x throughput of standard
MySQL and 3x of standard
PostgreSQL; scale-out up to
15 read replicas
Availability
& durability
Fault-tolerant, self-healing
storage; six copies of data
across three AZs; continuous
backup to S3
Highly secure
Network isolation,
encryption at
rest/transit
Fully managed
Managed by RDS: no
hardware provisioning,
software patching, setup,
configuration, or backups
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Aurora: Fastest Growing Service in AWS History
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Aurora Serverless
On-demand, auto-scaling database for applications with variable workloads
Warm
Capacity Pool
Application
Database Endpoint
Scalable Database Capacity
(Compute + Memory)
Shared Distributed Storage
Starts up on demand, shuts down when not in use
Automatically scales with no instances to manage
Pay per second for the database capacity you use
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Non-Relational Databases
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Amazon DynamoDB
We needed to adapt to power Amazon.com
Needed to power
Amazon.com
Required massive scalability
and reliability
DynamoDB designed to meet
this need
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Many Applications Require Millisecond Latency at Any Scale
Example: Amazon Prime Day 2017
Biggest shopping event in
Amazon history
Peaked at 12.9 million
requests per second
Thousands of Amazon
teams using DynamoDB
3.34 trillion requests
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Amazon DynamoDB
Fully-managed nonrelational database for any scale
High performance
Fast, consistent performance
Virtually unlimited throughput
Virtually unlimited storage
Secure
Encryption at rest and transit
Fine-grained access control
PCI, HIPAA, FIPS140-2 eligible
Fully managed
Maintenance-free
Serverless
Auto scaling
Backup and restore
Global tables
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DynamoDB Global Tables
Build high-performance,
globally distributed
applications
Low latency reads and writes
to locally available tables
Multi-region redundancy
and resiliency
Easy to set up and
no application
rewrites required
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Amazon ElastiCache
Fully-managed, Redis or Memcached compatible, low-latency, in-memory data
store
Fully managed
AWS manages all hardware
and software setup,
configuration, monitoring
Extreme performance
In-memory data store and cache
for sub-millisecond response times
Easily scalable
Read scaling with replicas
Write and memory scaling
with sharding
Non-disruptive scaling
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Graph Use Cases
Social news feed Recommendations Retail fraud detection
Friends
Use
Play
Like
Check in
Like
Connect
Read
Credit
card
Product
Email
address
Credit
card
Known
fraud
Uses
Paid
with
Uses
Paid
with
Paid with
Purchased
Approve
purchase?
Sport
Product
Purchased
Purchased
People
who also
follow sports
purchased…
Purchased
Knows
Knows
Do you
know…
Follows
Follows
Follows
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Challenges Building Apps with Highly-Connected Data
Existing graph databasesRelational databases
Too expensiveDifficult to
maintain high
availability
Difficult to scale Limited support
for open
standards
Inefficient graph
processing
Unnatural for
querying graph
Rigid schema
inflexible for
changing graphs
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Amazon Neptune
Fully managed graph database
Fast & scalable
Store billions of relationships;
query with millisecond latency
Reliable
Six replicas of your data across
three AZs with full backup and
restore
Easy
Build powerful queries
easily with Gremlin and SPARQL
Open
Supports Apache TinkerPop and
W3C RDF graph models
Gremlin
SPARQL
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Amazon DocumentDB
Fast, scalable, and fully managed MongoDB-compatible database service
Fast Scalable Fully managed MongoDB compatible
Millions of requests per second
with millisecond latency; twice the
throughput of MongoDB
Separation of compute and
storage enables both layers to
scale independently; scale out
to 15 read replicas in minutes
Managed by AWS:
no hardware provisioning; auto
patching, quick setup, secure,
and automatic backups
Compatible with MongoDB 3.6; use
the same SDKs, tools, and
applications with Amazon
DocumentDB
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Database Migration Service
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AWS Database Migration Service
Migrating
Databases to AWS
100,000+
Databases migrated
Migrate between on-premises and AWS
Migrate between databases
Data replication for zero-downtime migration
Automated schema conversion
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100,000+ Databases Migrated with DMS
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Got Files? Deploy Your File Workloads Quickly &
Easily with AWS
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Considerations when moving file data
1. Why are you moving data storage to AWS?
2. What is the data you’re moving?
3. Where is the data going – to which service/for what application & use
case?
4. When do you need the data off your array/out of the DC/in AWS?
5. How much data? How much usable network capacity?
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Time Cost Complexity
Why move? The pain of managing on-premises
storage
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Time
• Long 3-6-month acquisition
• 30-90 day implementation
Why move? The pain of managing on-premises storage
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Cost – hidden expenses
• Capex – high up-front capital investment
• Guesswork on how much storage you will need
• Guesswork on types of drives, mix of SSD/HDD
• Expensive add-on software for tiering, snapshotting, HA, DR
• Warranty renewals, EOL, migrations
Why move? The pain of managing on-premises storage
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Complexity
• Specialized expertise
• Availability – need a second array and datacenter for HA
• Backup – dedicated backup arrays plus offsite copy
• Scalability – difficult to scale: time/cost to order more
drives, upgrade controllers, EOL of array – all additional
hidden costs
Why move? The pain of managing on-premises storage
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What? Files.
Everyone has files
Always growing…
never shrinking
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What? File data
Also referred to as unstructured data
Productivity Apps
Development Data
Media Files
Digital Security
Sensor Data
Oceanographic
Weather
Traffic
Machine Generated
Satellite images
Weather data
Seismic imagery
Atmospheric data
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What? File data sources
DAS File Server NAS
Scale-out NAS or
Parallel File systems
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Where? Storage portfolio breadth and depth
Amazon FSx for
Windows
Amazon FSx
for Lustre
Amazon
EFS
Amazon
EBS
AWS DataSync AWS Transfer
for SFTP
AWS Snow*
Family
Amazon
Glacier
Amazon
S3
AWS Backup AWS Storage
Gateway Family
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Where? Amazon Elastic File System (EFS)
Storage for Linux-based applications
Key Workloads: Enterprise applications, web serving, content management, in-cloud
database backups, container storage, test and development, media workflows
Linux
NFSv4.x
Local file system
File server
NAS filer
Clustered or Scale-out file
system
Direct Connect
VPN
Multi-VPC
Multi-account
What OS and Protocol is
being used?
Where is the data
coming from?
How can the migrated
data be accessed?
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Where? Amazon FSx for Windows File Server
Storage for Windows-based business applications
Key Workloads: Home directories, .NET applications, content management, software
development environments, media workflows
Windows Server 2008,
2012, 2016
Windows 7, 8, 10
SMB 2.0
SMB 3.x
Local Windows
file system
Windows file server
NAS filer
Direct Connect
VPN
Single-AZ
Multi-AZ via DFS-R
What OS and Protocol is
being used?
Where is the data
coming from?
How will the migrated
data be accessed?
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Where? AWS Storage Gateway
Hybrid cloud service enabling on-premises apps to seamlessly use AWS
storage
Standard storage protocols Fully managed cache
Optimized data transfer AWS integrated
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Where? Hybrid file storage: File Gateway and
Volume Gateway
File Gateway Volume Gateway + File Server
Store and access
objects in Amazon S3
Block storage and file
systems on-premises
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Where? Hybrid storage w/ Amazon S3 & File
Gateway
Store files as objects in S3 and access via standard file protocols
Key Workloads: File backup, hybrid workflows, active archive, content distribution
Windows
Linux
NFSv3, NFSv4.1
SMB2, SMB3
Local file system
File server
NAS filer
On-premises
Remote location or
branch office
In AWS
What OS and Protocol is
being used?
Where is the data
coming from?
How will the migrated
data be accessed?
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How? Options for Data Transfer
AWS
Direct Connect
Amazon
Kinesis
Firehose
AWS
Snowball
AWS
Snowmobile
AWS
Storage
Gateway
Amazon S3
Transfer
Acceleration
AWS
DataSync
AWS
Transfer
for SFTP
AWS
Snowball Edge
Storage Optimized
Amazon Kinesis
Data Streams
Amazon Kinesis
Video Streams
NEW!
AWS
Snowball Edge
Compute
Optimized
NEW! NEW!
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How? Options for File Data Transfer
AWS
Storage
Gateway
AWS
DataSync
AWS
Transfer
for SFTP
NEW!NEW!
AWS
Direct Connect
AWS
Snowball
AWS
Snowball Edge
Storage Optimized
AWS
Snowball Edge
Compute
Optimized
NEW!
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How? AWS DataSync
AWS
Online transfer service that simplifies, automates, and
accelerates moving data between on-premises storage and AWS
Combines the speed and reliability of network acceleration
software with the cost-effectiveness of open source tools
Fast data
transfer
Easy
to use
Secure and
reliable
Cloud
integrated
Cost-effective
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How? AWS Transfer for SFTP
Fully-managed service enabling transfer of data over SFTP,
and stored in Amazon S3
Fully managed
in AWS
Native integration
with AWS services
Cost-effective
Seamless migration of
existing workflows
Simple to use
Enterprise
ready
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Summary
• On-premises storage continues to grow
• AWS storage portfolio is growing
• The customer may think of storage as
• DAS, NAS, SAN
• Backup/DR, Home directories, Enterprise Apps
• Application-specific data
• There are many enterprise file-based workloads that can be migrated today
• For Linux-based applications, use EFS
• For Windows-based business applications, use FSx for Windows File Server
• To store data in S3 and access via standard file protocols, use File Gateway
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Break
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Hands-on Workshop
Building and securing a web application on AWS
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