Amazon web services in the cloud computing landscape

AS&T - Cloud Computing

Amazon Web Services
In the Cloud Computing Landscape
6177

© 2011 Accenture. All rights reserved. Accenture, its logo, and Accenture “High performance. Delivered.” are trademarks of Accenture.

Who am I ?

Lode Blomme

Work
• Accenture since August 2011
• Technology Architecture Consultant

Social Media
• Twitter : @lodeblomme
• LinkedIn : http://linkedin.com/in/lodeblomme

Keywords
• architecture – cloud computing – photography – PHP – web 2.0 – web services

Copyright © 2011 Accenture All Rights Reserved 2

Project Context

Company Overview
• Small startup company
• Community website about outdoor navigation
• Web services for other outdoor navigation websites
• Active in Western Europe
Attention Points
• Agility is important
• No large capital for investments
Scalability
• Alot of traffic in summer (avg 25k visits / day)
• Alot less traffic in winter (avg 5k visits / day)
• Alot of traffic during the day
• Alot less traffic during the night


Mirror mirror on the wall, what is the best technology of them all ?

TECHNOLOGY
FOCUS

Cloud File Storage Comparison

• name: S3 • name: Cloud Files
• technology: proprietary • technology: OpenStack
• physical locations: US East, US • physical locations: US & UK
West, Ireland, Singapore, Tokyo


Cloud File Storage Pricing

Storage ($ / TB) Data Transfer ($ / TB)

0.16 0.2
0.14 0.18
0.16
0.12
0.14
0.1 0.12
0.08 0.1
0.06 0.08
0.06
0.04
0.04
0.02 0.02
0 0
0 2000 4000 6000 0 200 400
AWS S3 Rackspace AWS S3 Rackspace


Cloud Servers Comparison

• name: EC2 • name: Cloud Servers
• billing: hourly • billing: hourly
• stop server: yes (thx to EBS) • stop server: no
• storage size: independent of • storage size: linked to machine
machine power (thx to EBS) power
• technology: Xen • technology: Xen
• interface: UI or API • interface: UI or API
• physical locations: US East, US • Physical locations: US & UK
West, Ireland, Singapore, Tokyo


Technologies Used

Amazon S3 (Cloud File Storage)

Amazon EC2 (Cloud Servers) + EBS + Elastic IP
• Ubuntu Linux 8.04 – 11.04
• Apache Web Server 2.2
• NginX 0.5 – 0.8
• PHP 5.2 – 5.3
• PostgreSQL 8.2 – 8.4

Amazon RDS
• MySQL 5.1 – 5.5

Dedicated Servers
• Same as Amazon EC2

Amazon EC2 Machine Image (AMI)

Virtual Host
VM

AMI
virtual

HD
disk
S3


Amazon EC2 Ephemeral Storage

Root disk +
• Micro Instance : none
• Small Instance : 160 GB
• Large Instance : 850 GB
• Extra Large Instance : 1,690 GB
• High-Memory Extra Large Instance : 420 GB
• High-Memory Double Extra Large Instance : 850 GB
• High-Memory Quadruple Extra Large Instance : 1690 GB
• High-CPU Medium Instance : 350 GB
• High-CPU Extra Large Instance : 1690 GB
• Cluster Compute Quadruple Extra Large Instance : 1690 GB
• Cluster Compute Eight Extra Large Instance : 3370 GB
• Cluster GPU Quadruple Extra Large Instance : 1690 GB


Height Information Web Service

VM

Virtual HD S3


Scalable Height Information Web Service

VM

VM

VM

VM

VM
S3
VM


EC2 Elastic Block Store (EBS)

= Virtual disk
~ SAN

• Persistant
• Variable size
• Attach to VM
• Improve performance with RAID
• No super performance


EC2 EBS AMI

Virtual Host
virtual
VM disk

AMI

HD EBS


Static IP

client server 1

DNS server 2


EC2 Elastic IP

client Elastic IP server 1

DNS server 2


Amazon Relational Database Service

AMAZON RDS

Easily Launch MySQL & Oracle Databases


Easy Multi-AZ Deployment


Easy Read Replica Creation


Why Amazon RDS

Pros :
• Automatic software upgrades
• Automatic backups
• Create new RDS instance from any point in time backup
• Multi-AZ deployment
• Easy read replica creation

Cons :
• More expensive than running MySQL on EC2 yourself


Lessons Learned

Pro
• No traffic cost between S3 and EC2 when in same region
• High speed Amazon network when in same region
• No time to wait for hardware
• Easy to clone an existing running server
• Easy to add/remove storage
• Easy to replace a server without downtime

Con
• Pay extra for support
• Disk I/O is not top (Ephemeral Storage is faster than EBS)


Project Numbers

Peak number of instances :
• 2 RDS MySQL databases
• 3 EC2 instances running Memcached
• 3 EC2 instances running PostgreSQL database
• 10 EC2 instances running Apache & PHP
Storage requirements :
• +/- 75GB on S3
• +/- 1TB on EBS


Your own Amazon EC2 and S3

PRIVATE CLOUD

Private Cloud Amazon EC2

Nimbula Director (http://nimbula.com/)
• From the people behind Amazon EC2
• Uses KVM as hypervisor
• Runs on CentOS
Eucalyptus (http://www.eucalyptus.com/)
• Open Source Software
• AWS Interface Compatibility
• Xen and KVM Hypervisor Support
OpenStack Compute (http://www.openstack.org/projects/compute/)


Private Cloud Amazon S3

AmpliStor (http://www.amplidata.com/)
• Belgian Company
Gluster (http://www.gluster.org/)
• Acquired by Red Hat
• Runs on CentOS
OpenStack Object Storage
(http://www.openstack.org/projects/storage/)


Or we can go and have a drink …

Q&A

Amazon CloudWatch

• Monitoring for AWS cloud resources like :
• EC2 instances
• EBS volumes
• Elastic Load Balancers
• RDS DB instances
• SQS queues
• SNS topics
• Custom metrics generated by a customer’s applications and services.
• Programmatically retrieve your monitoring data
• View graphs
• Set alarms


Auto Scaling

• Allows you to scale capacity up or down automatically according to conditions
you define.
• Particularly well suited for applications that experience hourly, daily, or weekly
variability in usage.
• Enabled by Amazon CloudWatch.
• No additional charge beyond Amazon CloudWatch fees.


Application Deployment

• How to get your application running on newly started VMs?
• Number of servers changes constantly which makes deploying new versions
hard.
• Create a Gold Image with OS and application if your application doesn’t change
often.
• Create a system that bootstraps your VM when started. Use the same system
for application updates :
• CloudInit package from Canonical
• Chef from Opscode
• Puppet from Puppet Labs


AWS BEYOND IAAS

Non-relational data store

SIMPLEDB

What is SimpleDB

• Highly available, flexible, and scalable non-relational data store
• Automatically multiple geographically distributed copies of each data item
• Change data model on the fly
• Data is automatically indexed
• The Data Model: Domains, Items, Attributes and Values
• Consistency Options: Eventually Consistent Reads or Consistent Reads


When to use SimpleDB

• Utilize index and query functions rather than more complex relational database
functions
• Don’t want any administrative burden at all in managing their structured data
• Want a service that scales automatically up or down in response to
demand, without user intervention
• Require the highest availability and can’t tolerate downtime for data backup or
software maintenance


Amazon Relational Database Service

AMZON RDS

When to use RDS

• Have existing or new applications, code, or tools that require a relational
database
• Want native access to a MySQL or Oracle relational database, but prefer to
offload the infrastructure management and database administration to AWS
• Like the flexibility of being able to scale their database compute and storage
resources with an API call, and only pay for the infrastructure resources they
actually consume


What if SimpleDB and RDS don’t fit?

If you :
• Wish to select from a wide variety of database engines
• Want to exert complete administrative control over their database server

You can always use one of the many relational database AMIs. Or
you can start your own VM on EC2 and install your choice of
database, the way you want it.


in-memory cache in the cloud

ELASTICACHE

What is ElastiCache

• In-memory cache in the cloud
• Memcache on EC2  Memcached compatible
• Uses Amazon CloudWatch for monitoring


Why ElastiCache

Pros :
• Automatic failure detection and recovery
• No change needed in your application when adding/removing caching nodes

Cons :
• More expensive than running Memcached on EC2 yourself


Process vast amounts of data

ELASTIC MAPREDUCE

What is MapReduce?

MapReduce is a software framework introduced by Google in 2004 to
support distributed computing on large data sets on clusters of
computers.


Say Again?!?

void map(String name, String document):
for each word w in document:
EmitIntermediate(w, "1");

void reduce(String word, Iterator partialCounts):
int sum = 0;
for each pc in partialCounts:
sum += ParseInt(pc);
Emit(word, AsString(sum));


What, Why and How?

Software used :

• Usage scenarios: web indexing, data mining, log file analysis, data
warehousing, machine learning, financial analysis, scientific simulation, and
bioinformatics research.
• Development :
• SQL-like languages, such as Hive and Pig
• Java, Ruby, Perl, Python, PHP, R, or C++
• Store input data and application logic in Amazon S3.
• Output data is stored in Amazon S3.


Hadoop Ecosphere

Hive
• Data warehouse system for Hadoop. Easy data summarization, ad-hoc
queries, and the analysis of large datasets stored in Hadoop compatible file
systems. Query the data using a SQL-like language called HiveQL.

Pig
• Platform for analyzing large data sets that consists of a high-level language for
expressing data analysis programs. The salient property of Pig programs is that
their structure is amenable to substantial parallelization, which in turns enables
them to handle very large data sets.

Karmasphere Studio
• Graphical environment to develop, debug, deploy and monitor MapReduce jobs
from your desktop directly to Amazon Elastic MapReduce.


Amazon Simple Queue Service

AMAZON SQS

What is Amazon SQS?

• Reliable, highly scalable, hosted queue for storing messages.
• Move data between distributed components without losing messages or
requiring each component to be always available.
• Accessible through standards-based SOAP and Query interfaces.
• More info : http://aws.amazon.com/sqs/


Amazon SQS Pro’s and Con’s

Pro Con
• All messages are stored • No guaranteed message order (no
redundantly across multiple servers FIFO, LIFO or priorities).
and data centers.
• Messages only available for max. 2
• Designed to enable an unlimited weeks.
number of computers to read and
• Messages can be delivered more
write an unlimited number of
than once.
messages at any time.
• Max. 64 KB per message.


Amazon Simple Notification Service

AMAZON SNS

What is Amazon SNS

• Publish messages from an application and immediately deliver them to
subscribers or other applications
• Delivers notifications to clients using a “push” mechanism that eliminates the
need to periodically check or “poll” for new information and updates.
• Have messages delivered over clients’ protocol of choice:
• HTTP / HTTPS
• Email
• JSON Email
• Amazon SQS


Amazon SNS Pro’s and Con’s

Pro Con
• All messages are stored • Messages can be delivered more
redundantly across multiple servers than once.
and data centers.
• Max. 8 KB per message
• Designed to meet the needs of the
• Limit of 100 topics per AWS
largest and most demanding
account.
applications, allowing applications
to publish an unlimited number of
messages at any time.


Amazon SQS vs SNS

• Both messaging services within AWS

• SQS : used by distributed applications to exchange messages
• SNS : send time-critical messages to multiple subscribers

• SQS : polling model
• SNS : push mechanism

• SQS : send and receive messages without requiring each component to be
concurrently available.


Vendor Lock-in

• No problem when using plain EC2, it’s just a virtual server.
• EC2 additions (Elastic IP, Auto scaling) get you hooked to AWS.
• Some of Amazon PAAS and SAAS offerings restrict you to using AWS.


Amazon web services in the cloud computing landscape

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