New Repository in AEM 6 by Michael Marth

New Repository in AEM 6
and other goodies for developers
Michael Marth, Adobe

About @michaelmarth
Senior Engineering Manager at Adobe
Responsible for Granite platform

© 2013 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
Before we start
3
Certifications

Scalability Oak
4
AEM 6.0 Content Repository

AEM 6.0 Content Repository
Goals
 Scalability
 Big repositories
 Distributed, many cluster nodes
 Write throughput
 Parallel writes
 Write performance
 Many child nodes
 Many ACLs
5
Project “Oak”
 aka Jackrabbit 3, all open source
 Apache Software Foundation
http://jackrabbit.apache.org/oak/
 Implementation of the JCR spec, JSR-283
Your apps run unchanged

Architecture
6
JCR
oak-core
Micro kernel
Oak API
Micro kernel API

Microkernel choose according to your scalability and
performance requirements
7
jjjJCR Content Repository
Persistence
AEM
Performance Optimized and Made for Scale

Node Store Where nodes get stored
8
Nodes Binaries
• Tar MK
Tar files, locally
• MongoMK
MongoDB
• …
(other are WIP)
oak-core
JCR

Data Stores Where the binary data gets stored
9
• File System (local, NAS,
SAN)
shareable
• S3
for AWS deployments
• In Tar files
easier backup and ops
• In MongoDB
easier backup and ops
oak-core
JCR
Nodes Binaries

TarMK Memory-mapped files
10
92 GB
unused
CQ5.x Tar PM 100GB RAM in Server
8GB
JVM
AEM6 Tar MK: 100GB RAM in Server
8GB
JVM
92 GB off-heap
used for running the repo from RAM

MongoMK Cluster Deployment Topologies
11
MongoS
AEM with
Oak
MongoD Primary MongoD Secondary MongoD Secondary
MongoDB replication
r/w r r
MongoS
AEM with
Oak
MongoS
AEM with
Oak
ShareNothing
ShareNothing

Micro Kernels Which one shall I use?
12
AEM6 Author
default: TarMK
local, fast, easy to operate
“I need reliability”: TarMK + Failover instance
HTTP-transported copy of instance, failover switch e.g. Nagios
“I need scalability”: MongoMK Cluster
Scale CPU (many AEM instances)
Scale read throughput (many Mongo replicas)
Scale globally (distribute replicas globally)
“I cannot change the repository”: Remain on CRX2 Cluster
Supported, but deprecated

Micro Kernels Which one shall I use?
13
AEM6 Publish
Primary use case is Publishing: TarMK as a “Farm” (independent
instances)
fast, independent, easy to operate
Primary use case is User Generated Content: MongoMK in a Publish
Cluster
all Publish instances running on same MongoDB

Search Pluggable Index Providers
14
• Property Index Provider
stored in repo, backup’ed
sync/async
re-indexable asynchronously
ordered indexes
• Lucene
full-text extraction
stored in data store
• Solr
in JVM (OSGi runtime) or remote (for
production)
native queries language exposed
oak-core
JCR
MK

Search Configurable Indexes
15
• Index Definition via nodes
not everything indexed by default anymore
allows smaller, specialized, faster indexes
no need to index nodes you do not search for
• In AEM: pre-configured
indexes for AEM itself
• Define custom indexes for your
application’s needs
without an index the repo will be traversed on a
query
oak-core
JCR
MK

Numbers Performance & Scalability
16
TarMK running on my MacBook (i.e. totally unscientific)
• add nodes, session.save() for each node: xxx nodes added / sec
• add nodes, batch save(): xxx nodes added / sec
• add property, catch save(): xxx properties added / sec
• import files from Wikipedia, flat hierarchy:
MongoMK running on our Jenkins server
• 1 Oak instance on MongoMK: nodes added / sec…
• 3 Oak instances on MongoMK: nodes added / sec… (factor yyy)
• 5 Oak instances on MongoMK: nodes added / sec…(factor yyy)

Performance & Scalability Some Hints
17
Observations in a Cluster
• Many Oak instances, high write throughput needed
• Be mindful of observation listeners
• Only listen to local events
• Restrict paths you listen on
Many child nodes
• Many child nodes, high write throughput
• Be mindful of sorted node types
• nt:unstructured is sorted
• oak:unstructured is not

Efficiency We ♡ Sys Admins
18
Operations Dashboard

Project Efficiency Granite Operations Dashboard
provides control over system health, diagnosis and
maintenance automation, efficiently and extensible.
19
Main features:
• System health overview at a glance
• Reducing time to find, analyze and fix issues
• One-Click System Status to help file AEM Support tickets
• Maintenance automation to reduce project operations

DEMO

Efficiency We ♡ Sys Admins
24
One-Click Setup

Project Efficiency One-Click Setup instantly fires up
AEM instances in the cloud right
25
Main features:
• Ready-made AEM configurations
• Spins up machines in AWS – you maintain full control of the
machines

DEMO

Efficiency We ♡ Developers
31
Developer Mode

Project Efficiency Developer Mode
32
Main features:
• Inspect component performance right in the page
• Run automated tests
• Inspect component errors right in the context of the page

DEMO

Efficiency We ♡ Developers
38
Eclipse Tooling

DEMO

Sightly
Beautiful Markup

Mobile
PhoneGap Enterprise

one more
thing™

Sneak Peak
44
Granite.JS
aka AEM Micro Engine

Granite.JS Granite Javascript Platform
45
Main features:
• Lightweight, scripting server stack
• REST based content-driven web framework for server-side
JavaScript development
• Runs Sightly
• Based on Node.js

Granite.JS Architecture
46
jjj
Coral UI / Sightly
Sling
AEM
Granite/AEM - Java
Oak
REST
Microkernel (Java)
OSGi
jjj
Coral UI / Sightly
Sling.JS
Granite.JS – Node.JS
Repository
REST
Microkernel (C)
NPM

Granite.JS Use Case (I) – Web Developer in AEM
Projects
47
UI Dev
codes
Sightly,
CSS, etc
Brackets Grunt Granite.JS
Java Dev
codes
Java,
OSGi services
Eclipse Maven Granite/AEM
gitpush
Maven
AEM Production Pkg

DEMO

New Repository in AEM 6 by Michael Marth

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