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TECH WORKSHOP
 Johannes Borch – Solutions Architect




Author: Carlos Conde – Solutions Architect
#1 AWS Technical Review
#2 Cloud-Powered CI
#4 Q&A Session
Core Principles
« Everything fails
  all the time »
Werner Vogels – CTO of Amazon
When you turn off your cloud
resources, you actually stop
     paying for them
Technical Review
Amazon EC2
On-demand instances with admin access
Amazon Machine
    Images
 Pre-configured server Image
YOUR CODE



3rd PARTY
LIBRARIES


  CORE
SERVICES


OPERATING
 SYSTEM


 AMI
YOUR CODE   YOUR CODE



3rd PARTY   3rd PARTY
LIBRARIES   LIBRARIES


  CORE        CORE
SERVICES    SERVICES


OPERATING   OPERATING
 SYSTEM      SYSTEM


 AMI         AMI
YOUR CODE   YOUR CODE   YOUR CODE



3rd PARTY   3rd PARTY   3rd PARTY
LIBRARIES   LIBRARIES   LIBRARIES


  CORE        CORE        CORE
SERVICES    SERVICES    SERVICES


OPERATING   OPERATING   OPERATING
 SYSTEM      SYSTEM      SYSTEM


 AMI         AMI         AMI
VM Import
Easily import virtual machine images from your existing
         environment to Amazon EC2 instances



 • VMware ESX VMDK images
 • Citrix Xen VHD images
 • Microsoft Hyper-V VHD images for Microsoft Windows
   Server 2003 (R2) and 2008 (R1 & R2)
Instance-Store
     vs.
  EBS-Store
32bits




64bits
US East Region (N. VA)              EU West Region (IRE)                    Japan Region (Tokyo)


Availability        Availability   Availability              Availability
  Zone A              Zone B         Zone A                    Zone B       Availability      Availability
                                                                              Zone A            Zone B

Availability        Availability
                                                  Availability
  Zone C             Zone D
                                                    Zone C




  US West 1 Region (N. CA)           APAC Region (Singapore)                US West 2 Region (Oregon)




Availability      Availability     Availability             Availability    Availability      Availability
  Zone A            Zone B           Zone A                   Zone B          Zone A            Zone B
Amazon Route 53
       On-demand DNS service

                 +
          Elastic IP
Dynamic IP addresses for EC2 instances
Horizontal Scaling
Amazon CloudWatch
  Monitoring for AWS resources
Auto Scaling
Automatically scale up/down EC2 capacity
Elastic Load Balancing
Distributes incoming traffic to EC2 instances
6 am
10 am
10 am
10 am
7 pm
7 pm
7 pm
without elasticity you can't accelerate
High Availability
Media Storage &
 Distribution
Amazon S3
Simple Storage Service
1b   Tb
99.999999999%
   durability
Amazon S3 Growth
Total Number of Objects Stored in Amazon S3                                566
                                                                           Billion




                                                             262 Billion




                                               102 Billion

                                  40 Billion
       2.9 Billion   14 Billion
Tip: MFA Delete
Amazon CloudFront
 Flexible content delivery network
US West 1         US West 2       US East        Europe West   Asia Pacific   Asia Pacific
(N. California)     (Oregon)     (N. Virginia)     (Dublin)     (Singapore)      (Tokyo)




      AWS Regions
      AWS Edge Locations (CloudFront & Route 53)
DEMO
Data Storage
Data Storage
Relational Databases
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
RDS Read-Replicas
 For read-heavy applications
RDS Multi-AZ
Secondary replica in another Availability Zone
RDBMS on EC2
  Special use cases
[[ console screenshot ]]
restore EBS from snapshot
Amazon ElastiCache
Memcached compatible in-memory cache
Data Storage
"NoSQL" Databases
Amazon SimpleDB
NoSQL database, key-value model
Domain
ID       Category    Name        Color     Size    Make   Model Year
item01   Clothes     Shirt       Siamese small,
                                         medium,
                                         large
item02   Clothes     Sweater     Blue,     large                2006,
                                 Yellow,                        2007
                                 Pink
item03   Car parts   Emissions   O2                Audi   S4    2000,
                                 sensor                         2001,
                                                                2002
Item
ID       Category    Name        Color     Size    Make   Model Year
item01   Clothes     Shirt       Siamese small,
                                         medium,
                                         large
item02   Clothes     Sweater     Blue,     large                2006,
                                 Yellow,                        2007
                                 Pink
item03   Car parts   Emissions   O2                Audi   S4    2000,
                                 sensor                         2001,
                                                                2002
Attributes
ID       Category    Name        Color     Size    Make   Model Year
item01   Clothes     Shirt       Siamese small,
                                         medium,
                                         large
item02   Clothes     Sweater     Blue,     large                2006,
                                 Yellow,                        2007
                                 Pink
item03   Car parts   Emissions   O2                Audi   S4    2000,
                                 sensor                         2001,
                                                                2002
Values
ID       Category    Name        Color     Size    Make   Model Year
item01   Clothes     Shirt       Siamese small,
                                         medium,
                                         large
item02   Clothes     Sweater     Blue,     large                2006,
                                 Yellow,                        2007
                                 Pink
item03   Car parts   Emissions   O2                Audi   S4    2000,
                                 sensor                         2001,
                                                                2002
Amazon DynamoDB
 Fully managed NoSQL database
Low Latency
                          ADMIN
 Massive and Seamless
      Scalability

 Durable and Available


Predictable Performance


  Zero Administration
Average reads<5ms, writes<10ms
DEMO
Best Practices
Design for Failure

 •   Elastic IP addresses
 •   Multiple Azs
 •   Snapshot EBS volumes
Multiple AWS accounts

    •   Production
    •   Development
AWS IAM
Identity and Access Management
145
Identity & Access Management (IAM)

IAM offers greater security, flexibility,
and control when using AWS, including:
• Integration with your corporate directory
• Create and manage user groups
• Assign Permissions to Users and Groups
• Manage Passwords
Use multi-factor
authentication
for admins
Loose Coupling
 Adopt SOA principles
Create Independent components
  Design everything as a Black Box
  Think in terms of services
  Load-balance clusters




Amazon SQS as Buffers
 Tight Coupling       Controller A           Controller B        Controller C


                     Q                   Q                   Q
 Loose Coupling
 using Queues             Controller A        Controller B        Controller C
Amazon SQS
Simple Queue Service
Use notifications
You need to know when something's wrong
Amazon CloudWatch
  Monitoring for AWS resources

               +
    Amazon SNS
   Simple Notification Service
Tip – Instance Optimizer

             Free Memory
               Free CPU       PUT                       2 weeks
               Free HDD
               At 1-min
               intervals            Amazon CloudWatch
                                                                  Alarm

  Instance

             Custom Metrics




              “You could save a bunch of money by switching
              to a small instance, Click on CloudFormation Script to
              Save”
Implement Elasticity
   … In all your components
Automate
AWS is a programmable datacenter
App Vending
   Machine
Pre-configured
IT security-blessed
auto-scalable
auto-backup
multi-AZ
full-control
one-click deployable
enterprise apps
APIs / CLI
Script your IT infrastructure
Java, Ruby, Python, PHP, .Net


…
res = ec2.runInstances new RunInstancesRequest([
         imageId: "ami-00754474",
         keyName: "aws-sa-ww-key",
         instanceType: "m1.small",
         securityGroups: ["httpssh"],
         minCount: 1,
         maxCount: 1,
         userData: "AWSWeb.war".bytes.encodeBase64().toString()
         ])
…
CLI




PROMPT> ec2-run-instances ami-b232d0db -n 3 --availability-zone us-east-1a
HTTP


https://ec2.amazonaws.com/?Action=RunInstances
&ImageId=ami-60a54009
&MaxCount=3
&MinCount=1
&Placement.AvailabilityZone=us-east-1b
&Monitoring.Enabled=true
&AUTHPARAMS
AWS CloudFormation
 Template-based provisioning service
Test & Prototype
On-demand, pay as you go testing and
           prototyping
Data-based decision
        making
Drive your development by user's feedback
"Hadoop is a reliable storage and data analysis system"




               HDFS                 MapReduce
MapReduce
(map    ‘(   ))


          (    )


(reduce   ‘(   ))
Each input to a map is a list of <key, value> pairs
(<a, > , <o, > , <p, > , …)

Each output of a map is a list of <key, value> pairs
(<a’,   >, <o’, >, <p’,     >, …)


Each input to a reduce is a <key, value-list>
(<a’,            >, …)



Reduced into a list of values
Deploying a Hadoop cluster is hard




http://eddie.niese.net/20090313/dont-pity-incompetence/
Amazon Elastic
 MapReduce
Hadoop + The AWS Cloud
Data Warehouse
                                 (Batch Processing)
Data Warehouse                                                      Data Warehouse
 (Steady State)                                                      (Steady State)

                                                       Shrink to
                   Expand to                          9 instances
                  25 instances
Reducing Costs with Spot Instances
            Scenario #1                             Scenario #2
                                                        Job Flow
             Job Flow




                                                          Duration:
              Duration:
                                                           7 Hours
              14 Hours

   Cost :                                     #2: Cost with Spot
   4 instances *14 hrs * $0.50 = $28          4 instances *7 hrs * $0.50 = $13 +
                                              5 instances * 7 hrs * $0.25 = $8.75
                                              Total = $21.75



                   Time Savings: 50% Cost Savings: ~22%
AWS is a set of infrastructure building blocks
Amazon Web Services is all about


 FLEXIBILITY
« Want to increase innovation?
  Lower the cost of failure »

                             Joi Ito
AWS lowers the cost of
     innovation
 Testing a new idea is cheap
Resources
Architecture Center
aws.amazon.com/architecture
Articles & Tutorials
aws.amazon.com/articles
Videos & Webinars
aws.amazon.com/resources/webinars
FREE TIER!
aws.amazon.com/free
Plat_forms web development contest

Ulrich Stärk, Freie Universität Berlin – Plat_forms web development contest:
Der Wettbewerb wird am 03. und 04.04.2012 in den Räumen des Henry-Ford-
Baus der Freien Universität Berlin stattfinden;
der 02.04. wird als Anreise- und Aufbautag genutzt: https://www.plat-
forms.org/
Plat_Forms ist ein Experiment um die Eigenschaften verschiedener
Webentwicklungsplattformen (Java, .NET, PHP, Ruby, Perl, usw.)
wissenschaftlich zu untersuchen, bei dem Teams professioneller
Softwareentwickler gegeneinander antreten
Q &A
THANK YOU
aws.amazon.com
Amazon Web Services, Technical Workshop, Berlin, January 2012

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Amazon Web Services, Technical Workshop, Berlin, January 2012