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Running
Databases on AWS
Michael Hanisch – Solutions Architect
#1 Introduction
#2 Relational Databases
#3 NoSQL Databases
#4 What’s New?
#   1
Introduction
You created a fantastic webapp
http://www.flickr.com/photos/scobleizer/3985020876/
People love it
http://www.flickr.com/photos/grantrobertson/448648883
And everyone wants to use it
The scalability challenge

                                      Requirement: predictable,
                                       consistent performance
 Performance




                                                      Hardware provisioning
                                                      Data sharding
                                                      Data caching
                                                      Cluster management
               Reality: performance
               degrades with scale                    Fault management




                       Scalability
#   2
Relational Databases
Any Database on EC2
MySQL, Oracle, PostgreSQL, MS SQL Server…
Backups
[[ console screenshot ]]
restore EBS from snapshot
Increase IOPS
Amazon RDS
Relational Database Service
Backups
[[ console screenshot ]]
RDS automated backups
[[ console screenshot ]]
RDS DB snapshots
Restore
[[ console screenshot ]]
RDS DB snapshots
[[ console screenshot ]]
RDS snapshot restore

Vertical Scaling
[[ console screenshot +
diagram ]]
Scale verticaly
rds-modify-db-instance mydbinstance
--db-instance-class db.m2.2xlarge
db.m1.large

Leverage Multiple
Availability Zones
AWS Regions and Availability Zones




   Customer Decides Where Applications and Data Reside
RDS Multi-AZ
Synchronous standby replica in another Availability Zone

Isolate read and write traffic
RDS Read-Replicas
   For read-heavy applications

Cache as much as possible
Amazon ElastiCache
  Memcached compatible in-memory cache
In-Memory Cache in the
       Cloud
Protocol-compliant with
     Memcached

Functional Partitioning

Horizontal Scaling
 (aka sharding)
 for write-heavy

Chose the right Database
      Technology
Do I really need a
relational database?
#   3
NoSQL Databases
Amazon DynamoDB
Fully managed NoSQL database service
Low Latency
    SSD-based storage nodes
Average reads <5ms, writes <10ms
Massive and Seamless
     Scalability
       No table size or throughput limits
Live repartitioning for changes to storage and
                   throughput
Flexible data model
Key/attribute store for evolving models
Predictable Performance
   Provisioned throughput model
Durable and Available
 Consistent, disk-only writes (SSD)
Zero Administration
Add Dynamo to RDS, don’t replace
Provisioned
Throughput
Reserve required IOPS
   Per table. Set at creation. Scale via API.
Scale at any time
     No downtime
Pay for throughput
Example: Short Term Event
 Massive Scale
 Short Duration
 100,000 writes/second over 4 hours
 Up to 1.4 Billion Writes


    Estimated Throughput Cost: $400
Data model
Flexible. Schema-less
Simple key/value pairs
   title => “Introduction to DynamoDB”
            date => “20120320”
Associative array,
    or Hash
 [ title => “Introduction to DynamoDB”,
            date => “20120320” ]
Attributes

[ title => “Introduction to DynamoDB”,
           date => “20120320” ]
[ title => “Disaster Recovery with AWS”,
            date => “20120320”,
         format => “online seminar”,
          presenter => “Jeff Barr” ]




       Attributes

[ title => “Introduction to DynamoDB”,
           date => “20120320” ]
[ title => “Disaster Recovery with AWS”,
            date => “20120320”,
            format => “webinar”,
         presenter => “Jeff Barr” ]




            Items

[ title => “Introduction to DynamoDB”,
           date => “20120320” ]
[ title => “Disaster Recovery with AWS”,
            date => “20120320”,
            format => “webinar”,
         presenter => “Jeff Barr” ]



      Items
Limited to 64 kB!
 [ title => “Introduction to DynamoDB”,
            date => “20120320” ]
[ title => “Disaster Recovery with AWS”,
            date => “20120328”,
            format => “webinar”,
         presenter => “Jeff Barr” ]




             Table

[ title => “Introduction to DynamoDB”,
           date => “20120320” ]
Table
Item

 “UserID” = “1”


     “Date” =
   “20100915”


“Title” = “flower”


“Tags” = “flower”,
“jasmine”, “white”
“UserID” = “1”       “UserID” =”2”         “UserID” =”3”


     “Date” =            “Date” =              “Date” =
   “20100915”          “20100916”            “20100917”


“Title” = “flower”   “Title” = “ferrari”   “Title” = “coffee”


“Tags” = “flower”,   “Tags” = “car”,       “Tags” = “drink”,
“jasmine”, “white”      “italian”             “delicious”
“ImageID” = “1”      Primary or hash key

“Date” = “20100915”



  “Title” = “flower”


 “Tags” = “flower”,
 “jasmine”, “white”
“ImageID” = “1”      Primary or hash key

“Date” = “20100915”    Composite or range key


  “Title” = “flower”


 “Tags” = “flower”,
 “jasmine”, “white”
“ImageID” = “1”      Primary or hash key

“Date” = “20100915”    Composite or range key


  “Title” = “flower”


 “Tags” = “flower”,    Sets of strings
 “jasmine”, “white”    or numbers
APIs & Queries
Table APIs
1.CreateTable
 adds a new table to your account

2.UpdateTable
 updates the provisioned throughput

3.DeleteTable
 deletes a table and all of its items
4. DescribeTable
  returns table status, key schema, etc.

4. ListTables
   returns tables associated with the
   current account and endpoint
Item APIs
1. PutItem
 creates a new item, or replaces an old
 item with a new item (including all the
 attributes). Can perform conditional Put.

2. GetItem
 returns a set of Attributes for an item that
 matches the primary key. Consistent or
 eventually consistent reads.
3. UpdateItem
  PUT, ADD, DELETE attributes. Can also
  put a new item + attributes. Can
  perform conditional update.

4. DeleteItem
  deletes a single item in a table by
  primary key. Can perform conditional
  delete.
Query & Scan APIs

1. Query
  gets the values of one or more items and
  its attributes by primary key
 – Applicable only for tables with a composite
    hash range key
2. Scan
  returns one or more items and its
  attributes by performing a full scan of a
  table
Query and UPDATE
     patterns
GetItem
– Returns a set of attributes for an item that matches
  the primary key

                    Query
– Only works on a table with a composite hash, range
  key
– Hash key = ‘xxxxx’ and a range key condition (EQ,
  GT, LT, GE, LE, BEGINS_WITH, BETWEEN)
– Hash key = ‘xxxxx’ and no range key condition
– Count of items (that match a hash key value or
  hash key + range condition)
– Top N / Bottom N items ( via ScanIndexForward =
  T/F & Limit N)
– Paging via Limit N
BatchGetItem
– returns the attributes for multiple items from
  multiple tables using their primary keys



                  Scan
– Scans a table from beginning to end and
  apply filters
PutItem
– Add a new item, replace an item with a new item
– Can return all old values of an items attribute on
  update
– Conditional: Insert a new item only if the PK does
  not exist
               UpdateItem
– Add, update or delete an attribute (other than the
  PK)
– Increment an attribute (X = X + 10)
   • Atomic increment and get
– Insert a new item and attributes
– Conditional: Insert a new attribute if it does not exist
DeleteItem
– Delete an item
– Return ALL_OLD (optional)
– Conditional: Delete an item if it exists or if it
  has an expected attribute value
#   4
What’s new?
New, lower pricing for
Amazon EC2, RDS, and
    ElastiCache
      Mar 05, 2012
Amazon DynamoDB Now
  Available in Europe
      Mar 07, 2012
Amazon RDS Increases
Backup Retention Period
       Mar 19, 2012
Amazon RDS Launches
  Free Trial program
       Mar 05, 2012
aws.amazon.com/rds/free-trial
FREE TIER!
aws.amazon.com/free
THANK YOU
aws.amazon.com
Running Databases on AWS

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