Documentation & best practices
- Minimal TarMK architecture guidelines
- Single TarMK instance
- TarMK cold standby
- TarMK farm (for Publish tier)
Requirements for using MongoMK
TarMK vs MongoMK
- TarMK vs MongoMK guidelines
- Exceptions for choosing MongoMK over TarMK for AEM Author
- Exceptions for choosing MongoMK over TarMK for AEM Publish
- AEM architecture scaling guidelines
The data store is the part of the repository that stores large binary files, where as the nodestore stores small data like node definitions and properties. It is recommended the nodestore is persisted by the mechanism aligned with the selection microkernel (TarMK stores the nodestore in tar files, MongoMK stores the nodestore in MongoDB) however the data store should always be stored in the file system or an Amazon S3 bucket(s).
File Data Store (FDS)
- The File Data Store (FDS) is the default data store type for TarMK and MongoMK in AEM.
- FDS can be persisted on local disk, NAS or SAN.
- FDS is also sharable via the Shared Data Store configuration (see Shared Data Store section below).
- Any production deployment should have at a minimum a File Data Store configured for all AEM instances (Author and Publish).
Amazon S3 Data Store (S3DS)
- The Amazon S3 Data Store (S3DS) stores files in Amazon S3 buckets.
- S3DS is "infinitely scalable" and recommended for Data Stores over 5TB in size.
- S3DS is sharable via the Shared Data Store confguration (see below).
- Disk space
- Parallelization of AEM instances
- AEM Author sizing calculations
- AEM Publish sizing calculations
- AEM scalability guidelines
- Disk sizing for AEM Assets (Excel-based Disk Sizing tool)
Set up & configuration
- OS optimizations and NUMA
- Linux configurations and requirements
- Using virtualised environments (VMWare ESX and Amazon Web Services)
- MongoMK deployments require special Dispatcher configurations
Maintenance & operations
- Running online revision clean-up
- Monitoring online revision clean-up
- Troubleshooting online revision clean-up
- Online revision clean-up and backups
Offline revision clean-up
- When to use offline revision clean-up
- Running offline revision clean-up
- Increasing performance of offline revision clean-up
- Offline revision clean-up FAQ
- TarMK offline clean-up - Increase performance, avoid memory issues and track progress
Revision clean-up and TarMK cold standby
Garbage collection is the process of re-claiming disk space form the repositories Data Store. Garbage collection must be run frequently, during off-hours.
- Running garbage collection via the Operations console
- Running garbage collection via JMX MBean
- Scheduling the execution of garbage collection
- Garbage collection and backups
Garbage collection on a Shared Data Store
Gargbage collection and TarMK cold standby
Backup & restore
- Backup frequency considerations
- Avoid running concurrently with Data Store garbage collection or Nodestore revision clean-up
- Configuring AEM online backup
- AEM online backup Operations console
- AEM online backup JMX MBean
- AEM online backup HTTP API (for automation)
- AEM online backup performance benchmarks
- Filesystem snapshot backups
- Package-based backups
Restoring from backup
MongoDB backup and restore
Why upgrading to AEM 6.4 is important
Key repository features
AEM upgrades can be broken out into phases, each phase with a set of preparatory and execution steps. Upgrades to AEM 6.4 require in-place upgrades, rather than side-grades if backward compatibility is required.
Planning the upgrade
- Planning the upgrade to AEM 6.4
- Assessing upgrade complexity with the Pattern Detector
- Understanding backwards compatability options
Understanding the upgrade procedure
- Upgrading TarMK AEM Author
- Upgrading MongoMK Author cluster
- Upgrading TarMK Publish farm
- Final upgrade steps
Performing the upgrade
AEM 6.4 upgrade considerations
AEM feature considerations
Custom application considerations
Indexes & queries
Oak provides two main types of indexes: Lucene Property Indexes and Property Indexes.
- Lucene Property Index vs. Property Index
- AEM provides a Lucene Fulltext index and a Counter index, however these are used as-is.
SOLR server integration
Lucene property indexes
Tools and approaches
- oak-run.jar can be used to re/index with reduced impact on AEM performance.
- In AEM 6.4, using oak-run.jar is the ONLY supported method for re/indexing MongoMK and RDBMK repositories.
- Text pre-extraction for re/indexing of Lucene indexes with binary text extraction
- reindex=true to re-index any index
- refresh=true to refresh
- Abort re-indexing
- The Index Manager can no longer be used to re-index in AEM 6.4
Understanding and troubleshooting queries
- Troubleshooting slow queries guide
- Explain Query tool
- Query Builder debugger
- Query logging
- AEM Chrome Plug-in† with Sling Log Tracer v1.0.2+
† denotes community supported tooling.