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Effectively Scale and Operate AEM with MongoDB
Agenda
MongoDB Introduction
MongoMK
Sizing
Deployment
Operational Best Practices
Ola!
Norberto Leite
Technical Evangelist
Madrid, Spain
http://www.mongodb.com/norberto
@nleite
norberto@mongodb.com
introduction
MongoDB
GENERAL PURPOSE DOCUMENT DATABASE OPEN-SOURCE
MongoDB is Fully Featured
Query Operators
Conditional Operators
$all, $exists, $mod, $ne, $in, $nin, $nor, $or, $size, $type
$lt, $lte, $gt, $gte
// find customers with any claims
> db.customers.find( {claims: {$exists: true }} )
// find customers matching a regular expression
> db.customers.find( {last: /^rog*/i } )
// count customers by city
> db.customers.find( {city: ‘Philadelphia’} ).count()
Indexes
// Index nested documents
> db.customers.ensureIndex( “policies.agent”:1 )
> db.customers.find({‘policies.agent’:’Fred’})
// geospatial index
> db.customers.ensureIndex( “property.location”: “2d” )
> db.customers.find( “property.location” : { $near : [22,42] } )
// text index
> db.customers.ensureIndex( “policies.notes”: “text” )
Documents are Rich Data Structures
{
first_name: ‘Paul’,
surname: ‘Miller’,
cell: 447557505611,
city: ‘London’,
location: [45.123,47.232],
Profession: [banking, finance, trader],
cars: [
{ model: ‘Bentley’,
year: 1973,
value: 100000, … },
{ model: ‘Rolls Royce’,
year: 1965,
value: 330000, … }
]
}
Fields can contain an array of sub-documents
Fields
Fields can contain
arrays
Typed field values
Over
10,000,000
downloads
300,000 Students
for MongoDB
University
35,000
attendees to
MongoDB
events annually
Over 1,000
Partners
Over 2,000
Paying
Customers
http://graphics8.nytimes.com/images/2013/04/21/blogs/dotgenesis/dotgenesis-superJumbo.jpg
MongoMK
MongoDB MicroKernel
• AEM 6 Scalable Storage Solution
• Flexible
• Multi-Datacenter Deployments
• Geo Distributed Content
• Auto-Failover
MongoMK
Nodes Blobs
Settings
Changes
ClusterNodes
Metadata collection
Content node structure
Internal AEM indexes
Multi version structures
Blobs collection
Binary file chunks
Enforces data de-duplicationSettings, Changes, ClusterNodes
Internal AEM collections
Configuration and settings data
MongoMK - Content
Metadata
Binary / Blobs
Binary / Blobs
MongoMK – Metadata
Metadata
MongoMK – Data Model
MongoMK – Version Control
Revisions of content are maintained as separate
trees
MongoMK – Data Model
MongoMK – Versioning & Concurrency
System provides version and concurrency control of
content revisions.
MongoMK – Versioning & Concurrency
Binary / Blobs
MongoMK – Binary Data
Metadata
AEM Blob Storage
TAR MONGODB S3
MongoMK - Blobs
MongoMK - Blobs
Blobs on MongoMK
Positive Penalty
Unified Storage Layer More Storage Requirements
Reduced Operational Overhead More I/O Intensive
Binary De-duplication Higher Bandwidth Requirements
http://centralskateco.com/wp/wp-content/uploads/2014/12/sebasti_o_salgado_church_gate_station_1995.jpg
Sizing
MONGODB SIZING
Availability Volume
Expected Latency Working Data Set
http://i.ytimg.com/vi/urAmQRc6Ios/maxresdefault.jpg
Availability
Sizing - Availability
AEM
Editing
Curating
Validating
Primary
Secondary
Secondary
Sizing - Availability
AEM
Editing
Curating
Validating
Primary
Secondary
Primary
Sizing - Availability
AEM - author
AEM - author
AEM - author
Primary
Secondary Secondary
Datacenter West Datacenter EastDatacenter Center
AEM - authorAEM - author
Sizing - Availability
AEM - author
AEM - author
AEM - author
Primary
Secondary Secondary
Backups (hidden) Hot Backups (delayed)
http://cdn.papermag.com/uploaded_images/salgado_genesis.jpg
Volume
Sizing - Volume
Indexes Properties Multi Version
Nodes
Blobs
Full Text Search
Indexes
Binary Chunks
Sizing - Volume
• Space required by
– Data
– Indexes
• Read / Write Ratio
• Computational Unit Capacity
– RAM
– Disk
• Types of Disks!
– CPU
http://barrydequanne.com/wp-content/uploads/2014/09/Sebasti%C3%A3o-Salgado-3.jpg
Working Set
Sizing – Working Set
Working Set
Rest of your Database
Sizing – Working Set
• Percentage of data that is constantly request by the application
– Indexes
– Recent Used Data
• Read / Write
– Impacts the calculation of the RAM requirement
• Working Set Should Fit In RAM
Working Set Not in RAM
Sizing – Working Set
• AEM Calculation of Working Set
–Internal MongoDB Indexes
–Constantly accessed Assets
• % of data access
–AEM Indexes
• Multi-version Indexes
• Lucene Indexes
MongoDB 3.0
• Document Level Locking
• Compression
• Tunable Memory Cache
• Index Prefix
Compression
Adobe Recommended
Engine for AEM 6.1!!!
Working Set Can Be Distributed Across Shards
Sizing - Latency
Primary
Secondary
Secondary
AEM
AEM
AEM
ONLY
SECONDARY
READS!
Deploy
Rules for a Good Deployment
Prototype
Test
MonitorScale
Automate
AEM + Ops Manager
Scale EasilyMeet SLAs
Best Practices,
Automated
Cut Management
Overhead
https://acebourke.files.wordpress.com/2015/04/photo-by-saldago-three-miners.jpg
Operational Best Practices
Node Documents
{
"_id": "1:/norberto",
"_deleted": {
"r14e211fe903-0-1": "false"
},
"jcr:created": {
"r14e211fe903-0-1": ""dat:2015-06-23T17:53:36.257+02:00""
},
"jcr:createdBy": {
"r14e211fe903-0-1": ""admin""
},
"_commitRoot": {
"r14e211fe903-0-1": "0"
},
"jcr:primaryType": {
"r14e211fe903-0-1": ""nam:nt:folder""
},
"_modified": NumberLong("1435074815"),
"_modCount": NumberLong("1")
}
{
"_id": "1:/norberto",
…
"_commitRoot": {
"r14e211fe903-0-1": "0",
"r14e2122a4bb-0-1": "0"
},
…
"_modified": NumberLong("1435074995"),
"_modCount": NumberLong("3"),
"_children": true,
"_lastRev": {
"r0-0-1": "r14e2122a4bb-0-1"
}
}
Document Moves
2015-05-18T17:07:10.264+0200 [conn1298] command aem.$cmd command: findAndModify { findandmodify: "nodes",
query: { _id: "10:/content/www/...", _modCount: 3 }, fields: { _id: 1 }, update: { $set: { ... }, $max: {
_modified: 1431961630 }, $inc: { _modCount: 1 } } } update: { $set: { ... }, $max: { _modified:
1431961630 }, $inc: { _modCount: 1 } } nscanned:1 nscannedObjects:1 nmoved:1 nMatched:1 nModified:1
keyUpdates:0 numYields:0 locks(micros) w:116270 reslen:203 116ms
nscanned:1464 nscannedObjects:1044 nmoved:288 nMatched:1044 nModified:1044 keyUpdates:1 numYields:11
locks(micros) w:242369 169ms
nscanned:10829 nscannedObjects:10000 nmoved:1316 nMatched:10000 nModified:10000 keyUpdates:1 numYields:89
l
ocks(micros) w:2372208 1234ms
Fragmentation
AEM will be constantly growing the documents
generating document moves and subsequently
producing fragmentation
db.adminCommand( { repairDatabase: 1 } )
http://docs.mongodb.org/manual/reference/command/repairDatabase/
I/O
MongoDB will use your servers IO resources heavily
iostat | iftop | iperf | vmstat
http://docs.mongodb.org/manual/administration/production-notes
Monitoring Performance Indicators
Memory, Background Flushing Avg and
Opcounters: make sure you understand these
metrics
https://docs.mms.mongodb.com/
Working Set Measurement
https://docs.mms.mongodb.com/
Page Faults and Memory aligned with Db
Storage will give you and good indication of how
well provision is your machine and if you need to
scale out
Take Aways
Takeway
AEM + MongoDB is a Scalable Solution
Provisioning is Key
Monitor, monitor, monitor
Working closely with Adobe
We are ready to help you!
MongoMK Deployment for AEM
https://info-mongodb-com.s3.amazonaws.com/MongoDB_AEM6_Consulting_Datasheet.pdf
MongoDB + AEM White Paper
https://www.mongodb.com/collateral/connecting-global-
audiences-adobe-experience-manager-mongodb
MongoDB Days 2015
5 November, 2015 London
https://www.mongodb.com/events/mongodb-days-uk
Obrigado!
Norberto Leite
Technical Evangelist
norberto@mongodb.com
@nleite
Effectively Scale and Operate AEM with MongoDB by Norberto Leite

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