new repository in aem 6 by michael marth

New Repository in AEM 6and other goodies for developers

Michael Marth, Adobe

About @michaelmarth

Senior Engineering Manager at AdobeResponsible for Granite platform

© 2013 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

Before we start

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Certifications


Scalability Oak

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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

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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

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JCR

oak-core

Micro kernel

Oak API

Micro kernel API

1 per language

1 in Java

Many


Microkernel choose according to your scalability and performance requirements

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jjjJCR Content Repository

Persistence

AEM

TAR

Performance Optimized and Made for Scale


Node Store Where nodes get stored

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Nodes Binaries

• Tar MKTar files, locally

• MongoMKMongoDB

• …(other are WIP)

oak-core

JCR


Data Stores Where the binary data gets stored

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• File System (local, NAS, SAN)shareable

• S3for AWS deployments

• In Tar fileseasier backup and ops

• In MongoDBeasier backup and ops

oak-core

JCR

Nodes Binaries


TarMK Memory-mapped files

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92 GBunused

CQ5.x Tar PM 100GB RAM in Server

8GB JVM

AEM6 Tar MK: 100GB RAM in Server

8GB JVM

92 GB off-heapused for running the repo from RAM


MongoMK Cluster Deployment Topologies

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MongoS

AEM with Oak

MongoD PrimaryMongoD

SecondaryMongoD

Secondary

MongoDB replication

r/w r r

MongoS

AEM with Oak

MongoS

AEM with Oak

Share

Noth

ing

Share

Noth

ing


Micro Kernels Which one shall I use?

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AEM6 Author

default: TarMKlocal, fast, easy to operate

“I need reliability”: TarMK + Failover instanceHTTP-transported copy of instance, failover switch e.g. Nagios

“I need scalability”: MongoMK ClusterScale CPU (many AEM instances)Scale read throughput (many Mongo replicas)Scale globally (distribute replicas globally)

“I cannot change the repository”: Remain on CRX2 ClusterSupported, but deprecated


Micro Kernels Which one shall I use?

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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 Clusterall Publish instances running on same MongoDB


Search Pluggable Index Providers

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• Property Index Providerstored in repo, backup’edsync/asyncre-indexable asynchronouslyordered indexes

• Lucenefull-text extractionstored in data store

• Solrin JVM (OSGi runtime) or remote (for production)native queries language exposed

oak-core

JCR

MK


Search Configurable Indexes

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• Index Definition via nodesnot everything indexed by default anymoreallows smaller, specialized, faster indexesno need to index nodes you do not search for

• In AEM: pre-configured indexes for AEM itself

• Define custom indexes for your application’s needswithout an index the repo will be traversed on a query

oak-core

JCR

MK


Numbers Performance & Scalability

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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

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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

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Operations Dashboard


Project Efficiency Granite Operations Dashboard provides control over system health, diagnosis and maintenance automation, efficiently and extensible.

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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

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One-Click Setup


Project Efficiency One-Click Setup instantly fires up AEM instances in the cloud right

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Main features:• Ready-made AEM configurations• Spins up machines in AWS – you maintain full control of the

machines


DEMO


Efficiency We ♡ Developers

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Developer Mode


Project Efficiency Developer Mode

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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

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Eclipse Tooling


DEMO

What else is coming up


SightlyBeautiful Markup


MobilePhoneGap Enterprise


one more thing™


Sneak Peak

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Granite.JSaka AEM Micro Engine


Granite.JS Granite Javascript Platform

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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

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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

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UI Dev

codes

Sightly,CSS, etc

Brackets Grunt Granite.JS

Java Dev

codes

Java,OSGi services

Eclipse Maven Granite/AEM

gitpushMaven AEM Production

Pkg


DEMO

Thank for your attention

new repository in aem 6 by michael marth

Technology