This document discusses different architectures for implementing Adobe Experience Manager (AEM): - A development setup that is easy to setup but not fault tolerant or scalable. - A highly available architecture that scales AEM runtime via auto scaling groups but the author server cannot scale. - A digital assets heavy architecture best for large datastores, with failover and replication between regions. - A distributed author architecture that offers resilience and scalability through author clustering and MongoDB replica sets. - A user generated content architecture able to handle UGC on runtime via horizontal scaling and moderation on publish servers.

1. © 2013 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Amazon Web Services & Adobe Experience Manager
Kam Radhakrishnan | Senior Consultant | Adobe

2. © 2013 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
jjj
Sling
AEM UI
Oak & Plugins
REST
Microkernel (Java)
OSGi
AEM Internal Architecture
3
Presentation Tier
Middle Tier
Data Tier
Traditional Web Application

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How does it work?
5
A
P P P
D D D
Cache
Invalidation
Cache
Invalidation
Author Server
Dispatcher Servers
Publish Servers
Elastic Load Balancer
Internet Users
Marketing Users

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Development Setup
6
Advantages Disadvantages
• Easy to setup • Not fault tolerant.
• Built and re-built in minutes • Cannot scale on Author and runtime.
• Best for learning & practice and ideal developer setup. • Not suitable for production.
AZ#1
A P D
Sydney

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Highly Available Architecture
7
Advantages Disadvantages
• Highly scalable runtime with Auto Scaling Group based on
CloudWatch stats.
• Author cannot scale.
• TarMK offers optimal performance. • Manual failover on Author
• Author Servers are fault tolerant • At any given point in time we have few servers that are idle.
AZ#1
AZ#2
A P
P
D
DAc
PG
Auto Scaling
Group
Auto Scaling
Group
Sydney
PG

6. © 2013 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Digital Assets(DAM) Heavy Architecture
8
Ac
PG
PG
A
AZ#2
AZ#1
Sydney
Advantages Disadvantages
• Best for customer who have a large datastore that runs in
terabytes.
• Cannot scale on Author.
• Offers failover and DR in a different region. • At any given point in time we have few servers that are idle.
• Supports binary-less replication for storage efficiencies, all
author and Publish point to one copy in S3.
P D
P D
Auto Scaling Group
Auto Scaling Group

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Distributed Author Architecture
9
A
PG
A
AZ#1
AZ#1
Sydney
M
M
P D
P D
Auto Scaling
Group
Auto Scaling
Group
Advantages Disadvantages
• Best when there are large numbers of authors that need to be
supported across geographies.
• Required skillset in MongoDB to optimize and administer the
servers.
• Architecture offers resilience and scalability and automatic
failover with Author clustering and mongo dB replica sets.
• Performance is not as great as Tar Micro Kernel.
• Runtime still runs on Tar Micro Kernel which gives good
performance for customers accessing the website.
• More servers to monitor and manage.
MA
PG
Singapore

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D
D
User Generated Content Architecture
10
Ac
P
P
A
AZ#2
AZ#1
Sydney
P D
P D
Auto Scaling Group
Auto Scaling Group
M
M
Advantages Disadvantages
• Ability to handle UGC content on Runtime. • MongoDB skill set required for ongoing maintenance.
• Horizontal scalability on Runtime • Performance is not as good as Tar Micro Kernel.
• Moderation on Publish servers. • More servers to monitor and manage.
MA

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Q & A

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