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Amazon web services in the cloud computing landscape
1.
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.
2.
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
3.
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 Copyright © 2011 Accenture All Rights Reserved 3
4.
Mirror mirror on
the wall, what is the best technology of them all ? TECHNOLOGY FOCUS Copyright © 2011 Accenture All Rights Reserved 4
5.
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 Copyright © 2011 Accenture All Rights Reserved 5
6.
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 Copyright © 2011 Accenture All Rights Reserved 6
7.
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 Copyright © 2011 Accenture All Rights Reserved 7
8.
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 Copyright © 2011 Accenture All Rights Reserved 8
9.
Amazon EC2 Machine
Image (AMI) Virtual Host VM AMI virtual HD disk S3 Copyright © 2011 Accenture All Rights Reserved 9
10.
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 Copyright © 2011 Accenture All Rights Reserved 10
11.
Height Information Web
Service VM Virtual HD S3 Copyright © 2011 Accenture All Rights Reserved 11
12.
Scalable Height Information
Web Service VM VM VM VM VM S3 VM Copyright © 2011 Accenture All Rights Reserved 12
13.
EC2 Elastic Block
Store (EBS) = Virtual disk ~ SAN • Persistant • Variable size • Attach to VM • Improve performance with RAID • No super performance Copyright © 2011 Accenture All Rights Reserved 13
14.
EC2 EBS AMI
Virtual Host virtual VM disk AMI HD EBS Copyright © 2011 Accenture All Rights Reserved 14
15.
Static IP
client server 1 DNS server 2 Copyright © 2011 Accenture All Rights Reserved 15
16.
EC2 Elastic IP
client Elastic IP server 1 DNS server 2 Copyright © 2011 Accenture All Rights Reserved 16
17.
Amazon Relational Database
Service AMAZON RDS Copyright © 2011 Accenture All Rights Reserved 17
18.
Easily Launch MySQL
& Oracle Databases Copyright © 2011 Accenture All Rights Reserved 18
19.
Easy Multi-AZ Deployment Copyright
© 2011 Accenture All Rights Reserved 19
20.
Easy Read Replica
Creation Copyright © 2011 Accenture All Rights Reserved 20
21.
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 Copyright © 2011 Accenture All Rights Reserved 21
22.
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) Copyright © 2011 Accenture All Rights Reserved 22
23.
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 Copyright © 2011 Accenture All Rights Reserved 23
24.
Your own Amazon
EC2 and S3 PRIVATE CLOUD Copyright © 2011 Accenture All Rights Reserved 24
25.
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/) • Open Source Software Copyright © 2011 Accenture All Rights Reserved 25
26.
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/) • Open Source Software Copyright © 2011 Accenture All Rights Reserved 26
27.
Or we can
go and have a drink … Q&A Copyright © 2011 Accenture All Rights Reserved 27
28.
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 Copyright © 2011 Accenture All Rights Reserved 28
29.
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. Copyright © 2011 Accenture All Rights Reserved 29
30.
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 Copyright © 2011 Accenture All Rights Reserved 30
31.
AWS BEYOND IAAS Copyright
© 2011 Accenture All Rights Reserved 31
32.
Non-relational data store
SIMPLEDB Copyright © 2011 Accenture All Rights Reserved 32
33.
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 Copyright © 2011 Accenture All Rights Reserved 33
34.
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 Copyright © 2011 Accenture All Rights Reserved 34
35.
Amazon Relational Database
Service AMZON RDS Copyright © 2011 Accenture All Rights Reserved 35
36.
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 Copyright © 2011 Accenture All Rights Reserved 36
37.
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. Copyright © 2011 Accenture All Rights Reserved 37
38.
in-memory cache in
the cloud ELASTICACHE Copyright © 2011 Accenture All Rights Reserved 38
39.
What is ElastiCache •
In-memory cache in the cloud • Memcache on EC2 Memcached compatible • Uses Amazon CloudWatch for monitoring Copyright © 2011 Accenture All Rights Reserved 39
40.
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 Copyright © 2011 Accenture All Rights Reserved 40
41.
Process vast amounts
of data ELASTIC MAPREDUCE Copyright © 2011 Accenture All Rights Reserved 41
42.
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. Copyright © 2011 Accenture All Rights Reserved 42
43.
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)); Copyright © 2011 Accenture All Rights Reserved 43
44.
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. Copyright © 2011 Accenture All Rights Reserved 44
45.
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. Copyright © 2011 Accenture All Rights Reserved 45
46.
Amazon Simple Queue
Service AMAZON SQS Copyright © 2011 Accenture All Rights Reserved 46
47.
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/ Copyright © 2011 Accenture All Rights Reserved 47
48.
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. Copyright © 2011 Accenture All Rights Reserved 48
49.
Amazon Simple Notification
Service AMAZON SNS Copyright © 2011 Accenture All Rights Reserved 49
50.
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 Copyright © 2011 Accenture All Rights Reserved 50
51.
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. Copyright © 2011 Accenture All Rights Reserved 51
52.
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. Copyright © 2011 Accenture All Rights Reserved 52
53.
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. Copyright © 2011 Accenture All Rights Reserved 53
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