This document discusses Auto Scaling in Amazon DynamoDB. It provides an overview of DynamoDB Auto Scaling, including how it removes the need to manually provision and adjust throughput capacity. It describes the console experience and API actions for Auto Scaling. It also explains how Auto Scaling works under the hood, powered by Application Auto Scaling and CloudWatch. Best practices for Auto Scaling such as optimizing for daily scale down limits are also covered.

1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Auto Scaling in Amazon
DynamoDB
Vijay Natarajan
Principal Product Manager
08/17/2017

2. Agenda
• Amazon DynamoDB Overview
• Auto Scaling
• Overview
• Console Experience & API Actions
• Under the Cover
• Best Practices

3. Amazon DynamoDB Overview

4. Amazon DynamoDB
• NoSQL Database
• Fully-managed
• Massive and seamless scalability
• Response times in microseconds
• Highly available
• Integration with AWS Services
• Pay-as-you-go model

5. DynamoDB Journey
Dec ‘04:
Suffers
outage
Oct ‘07:
Dynamo paper
published
Jan ‘12:
DynamoDB
General
Availability
Q3 ‘16:
Leader in Gartner
MQ, Forrester
Wave
Today:
• Available in 16 regions
• Millions of tables, several >100TB
• 10’s of PBs of data; Trillions of
requests/month
Tier-0 service powering most of Amazon

6. Fully Managed NoSQL Database Service
Databases hosted on premise Database hosted on Amazon EC2
Managed by You
Managed by AWS
Amazon DynamoDB

7. 1. Scalability
2. Performance
3. Security & Monitoring
4. Availability & Data Protection
5. Manageability & TCO
6. Dev Platform & Tools
DynamoDB Investment Pillars

8. • Millions of
reads/sec from
single DAX
cluster
• Unlimited items
and storage
• Auto scale
throughput based
on consumption
• Consistent, single
digit millisecond
latency
• Optimized for
analytics
workloads with
native indexing
• Microsecond
response times
with DynamoDB
Accelerator (DAX)
• Control user
access at items
and attributes
level
• SOC, PCI, ISO,
FedRAMP (Mod &
High), HIPAA
BAA, DoD IL4
• Monitor with
CloudWatch
metrics & logging
with CloudTrail
• Client-side
encryption library
• Secure, private
VPC endpoints
• Designed for
99.99% high
availability (HA)
• Built-in replication
across 3 zones
• Fully-managed
• Perpetual free tier
• Pay-as-you-grow
for capacity and
storage
independently
• Track table level
spending with
Tagging
• Purge data
automatically
(Time To Live)
• Event-driven
programming with
Triggers &
Lambda
• Advanced
analytics with
EMR & Amazon
Redshift
• Full-text query
support with
Amazon
Elasticsearch
Service
• Real-time stream
processing with
Amazon Kinesis
• DMS connector
for MongoDB to
DynamoDB
Scalability Performance Security Availability &
Data Protection
Manageability &
TCO
Dev Platform &
Tools

9. Key Customer Segments
• Ad-tech
• Gaming
• IoT
• Mobile
• Web
• Storage
• Education
• Media
• E-Commerce
• Telecom
• Financial services
• BioTech
• Healthcare
• Retail
• Networking

10. Auto Scaling

11. Overview
• Removes the guesswork out of provisioning
adequate capacity for new workloads
• Reduces operational burden of monitoring and
adjusting capacity as application demands change
• Scales up capacity as application request rates
accelerate ensuring optimal performance
• Scales down capacity as application request rates
slow down reducing costs
• No additional costs for Auto Scaling
• Fully-managed, automatic scaling of
throughput capacity for read and write of
tables and global secondary indexes
• Set only target utilization % (consumed
capacity/provisioned capacity), minimum and
maximum limits
• Configurable from management console,
CLI, and SDK
• Works with existing tables and GSI; Enabled
by default for new tables
• Full visibility into scaling activities from
console
• Powered by Application Auto Scaling which
also supports EC2, ECS, EMR, AppStream
Feature Key Benefits

12. Console Experience (contd.)

13. Console Experience (contd.)

14. Console Experience (contd.)

15. Console Experience (contd.)

16. Console Experience

17. • RegisterScalableTarget: Registers or updates a scalable target (Table or GSI)
• DeregisterScalableTarget: Deregister a scalable target and delete its scaling policies
• PutScalingPolicy: Create new or Update existing policy of scalable target
• DeleteScalingPolicy: Delete a policy
• DescribeScalingPolicies: Get policies description, filtered by table, GSI, read, write
• DescribeScalableTargets: Get information of the table or GSI being scaled
• DescribeScalingActivities: Get 6 weeks’ scaling activities history of a table or GSI
Application AutoScaling API Actions

18. How Auto Scaling Works
1. User creates Application Auto Scaling policy for a
table
2. DynamoDB publishes consumed capacity metrics to
Amazon CloudWatch.
3. If consumed capacity exceeds target utilization (or
falls below target), Amazon CloudWatch triggers an
alarm
4. The CloudWatch alarm invokes Application Auto
Scaling to evaluate your scaling policy
5. Application Auto Scaling sends UpdateTable
API request to DynamoDB to adjust table's
provisioned throughput
6. DynamoDB processes the UpdateTable request
increasing (or decreasing) table's provisioned
throughput capacity so that it approaches your
target utilization.

19. • Auto Scaling is best suited for predictable, gradually changing traffic patterns
• Start with default settings for new tables/GSI, and make adjustments over time
• Optimize for the daily scale down limits, currently, nine per day
• For known time window of traffic spikes, disable Auto Scaling and update manual
provisioning programmatically
• Apply same settings to GSI as tables, for optimal query performance
Best Practices

20. Getting Started with DynamoDB:
https://aws.amazon.com/dynamodb/
http://docs.aws.amazon.com/amazondynamodb/latest/gettingstartedguide/Welcome.html
Getting Started with DynamoDB Auto Scaling:
http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html
Additional Resources

21. Thank you!