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�۶���Ƶ Experience Manager Assets performance tuning guide assets-performance-tuning-guide

An Experience Manager Assets setup contains several hardware, software, and network components. Depending upon your deployment scenario, you may require specific configuration changes to hardware, software, and network components to remove performance bottlenecks.

In addition, identifying and adhering to certain hardware and software optimization guidelines helps build a sound foundation that enables your Experience Manager Assets deployment to meet expectations around performance, scalability, and reliability.

Poor performance in Experience Manager Assets can impact user experience around interactive performance, asset processing, download speed, and other areas.

In fact, performance optimization is a fundamental task that you perform before you establish target metrics for any project.

Here are certain key focus areas around which you discover and fix performance issues before they have an impact on users.

Platform platform

While Experience Manager is supported on several platforms, �۶���Ƶ has found the greatest support for native tools on Linux and Windows, which contributes to optimum performance and ease of implementation. Ideally, you should deploy a 64-bit operating system to meet the high memory requirements of an Experience Manager Assets deployment. As with any Experience Manager deployment, you should implement TarMK wherever possible. While TarMK cannot scale beyond a single author instance, it is found to perform better than MongoMK. You can add TarMK offload instances to increase the workflow processing power of your Experience Manager Assets deployment.

Temporary folder temp-folder

To improve asset upload times, use high performance storage for the Java temporary directory. On Linux and Windows, a RAM drive or SSD could be used. In cloud-based environments, an equivalent high speed storage type could be used. For example, in Amazon EC2, an drive can be used for the temporary folder.

Assuming the server has ample memory, configure a RAM drive. On Linux, run these commands to create an 8 GB RAM drive:

mkfs -q /dev/ram1 800000
 mkdir -p /mnt/aem-tmp
 mount /dev/ram1 /mnt/aem-tmp
 df -H | grep aem-tmp

On Windows OS, use a third-party driver to create a RAM drive or just use high performance storage such as SSD.

Once the high performance temporary volume is ready, set the JVM parameter -Djava.io.tmpdir. For example, you could add the JVM parameter below to the CQ_JVM_OPTS variable in the bin/start script of Experience Manager:

-Djava.io.tmpdir=/mnt/aem-tmp

Java configuration java-configuration

Java version java-version

�۶���Ƶ recommends deploying Experience Manager Assets on Java 8 for optimum performance.

JVM parameters jvm-parameters

Set the following JVM parameters:

Data store and memory configuration data-store-and-memory-configuration

File data store configuration file-data-store-configuration

Separating the data store from the segment store is recommended for all Experience Manager Assets users. In addition, configuring the maxCachedBinarySize and cacheSizeInMB parameters can help maximize performance. Set maxCachedBinarySize to the smallest file size that can be held in the cache. Specify the size of the in-memory cache to use for the datastore within cacheSizeInMB. �۶���Ƶ recommends you set this value between 2-10 percent of the total heap size. However, load/performance testing can help determine the ideal setting.

Configure the maximum size of the buffered image cache configure-the-maximum-size-of-the-buffered-image-cache

When uploading large amounts of assets to �۶���Ƶ Experience Manager, to allow for unexpected spikes in memory consumption and to prevent JVM fails with OutOfMemoryErrors, reduce the configured maximum size of the buffered image cache. Consider an example that you have a system with a maximum heap (- Xmxparam) of 5 GB, an Oak BlobCache set at 1 GB, and document cache set at 2 GB. In this case, the buffered cache would take maximum 1.25 GB and memory, that would leave only 0.75 GB memory for unexpected spikes.

Configure the buffered cache size in the OSGi Web Console. At https://host:port/system/console/configMgr/com.day.cq.dam.core.impl.cache.CQBufferedImageCache, set the property cq.dam.image.cache.max.memory in bytes. For example, 1073741824 is 1 GB (1024 x 1024 x 1024 = 1 GB).

From Experience Manager 6.1 SP1, if you’re using a sling:osgiConfig node for configuring this property, make sure to set the data type to Long. For more details, see .

Shared data stores shared-data-stores

Implementing an S3 or Shared File Datastore can help to save disk space and increase network throughput in large-scale implementations. For more information on the pros and cons of using a shared datastore, see Assets sizing guide.

S3 data store s-data-store

The following S3 Data Store configuration ( org.apache.jackrabbit.oak.plugins.blob.datastore.S3DataStore.cfg) helped �۶���Ƶ extract 12.8 TB of binary large objects (BLOBs) from an existing file data store into an S3 data store at a customer site:

accessKey=<snip>
 secretKey=<snip>
 s3Bucket=<snip>
 s3Region=us-standard
 s3EndPoint=<a href="https://s3.amazonaws.com/">s3.amazonaws.com</a>
 connectionTimeout=120000
 socketTimeout=120000
 maxConnections=80
 writeThreads=60
 concurrentUploadsThreads=30
 asyncUploadLimit=30
 maxErrorRetry=1000
 path=/opt/author/crx-quickstart/repository/datastore
 s3RenameKeys=false
 s3Encryption=SSE_S3
 proactiveCaching=true
 uploadRetries=1000
 migrateFailuresCount=400

Network optimization network-optimization

�۶���Ƶ recommends enabling HTTPS because many companies have firewalls that sniff HTTP traffic, which adversely impacts uploads and corrupts files. For large file uploads, ensure that users have wired connections to the network because a WiFi network becomes quickly saturated. For guidelines on identifying network bottlenecks, see Assets sizing guide. To assess network performance by analyzing network topology, see Assets network considerations.

Primarily, your network optimization strategy depends upon the amount of bandwidth available and the load on your Experience Manager instance. Common configuration options, including firewalls or proxies can help improve network performance. Here are some key points to bear in mind:

Workflows workflows

Transient workflows transient-workflows

Wherever possible, set the DAM Update Asset workflow to Transient. The setting significantly reduces the overheads required to process workflows because, in this case, workflows do not need to pass through the normal tracking and archival processes.

In cases where transient workflows cannot be used, run workflow purging regularly to delete archived DAM Update Asset workflows to ensure system performance does not degrade.

Typically, execute the purging workflows on a weekly basis. However, in resource-intensive scenarios, such as during wide-scale asset ingestion, you can execute it more frequently.

To configure workflow purging, add a new �۶���Ƶ Granite Workflow Purge configuration through the OSGi console. Next, configure and schedule the workflow as part of the weekly maintenance window.

If purging runs for too long, it times out. Therefore, you should ensure that your purging jobs complete to avoid situations where purging workflows fail to complete owing to the high number of workflows.

For example, after executing numerous non-transient workflows (that creates workflow instance nodes), you can execute on an ad-hoc basis. It removes redundant, completed workflow instances immediately rather than waiting for the �۶���Ƶ Granite Workflow Purge scheduler to run.

Maximum parallel jobs maximum-parallel-jobs

By default, Experience Manager runs a maximum number of parallel jobs equal to the number of processors on the server. The problem with this setting is that during periods of heavy load, all the processors are occupied by DAM Update Asset workflows, slowing down UI responsiveness and preventing Experience Manager from running other processes that safeguard server performance and stability. As a good practice, set this value to half the processors that are available on the server by performing the following steps:

Setting a queue to half of the available processors is a workable solution to start with. However, you may have to increase or decrease this number to achieve maximum throughput and tune it by environment. There are separate queues for transient and non-transient workflows and other processes, such as external workflows. If several queues set to 50% of the processors are active simultaneously, the system can get overloaded quickly. The queues that are heavily used vary greatly across user implementations. Therefore, you may have to configure them thoughtfully for maximum efficiency without sacrificing server stability.

DAM Update Asset configuration dam-update-asset-configuration

The DAM Update Asset workflow contains a full suite of steps that are configured for tasks, such as Dynamic Media PTIFF generation and �۶���Ƶ InDesign Server integration. However, most users may not require several of these steps. �۶���Ƶ recommends you create a custom copy of the DAM Update Asset workflow model, and remove any unnecessary steps. In this case, update the launchers for DAM Update Asset to point to the new model.

Running the DAM Update Asset workflow intensively can sharply increase the size of your file datatastore. Results of an experiment performed by �۶���Ƶ have shown that the datastore size can increase by approximately 400 GB if around 5500 workflows are performed within 8 hours.

It is a temporary increase, and the datastore is restored to its original size after you run the datastore garbage collection task.

Typically, the datastore garbage collection task runs weekly along with other scheduled maintenance tasks.

If you have a limited disk space and run DAM Update Asset workflows intensively, consider scheduling the garbage collection task more frequently.

Runtime rendition generation runtime-rendition-generation

Customers use images of various sizes and formats across their website or for distribution to business partners. Because each rendition adds to the footprint of the asset in the repository, �۶���Ƶ recommends using this feature judiciously. To reduce the amount of resources necessary to process and store images, you can generate these images at run time rather than as renditions during ingestion.

Many Sites customers implement an image servlet that resizes and crops images at the time they are requested, which imposes additional load on the publish instance. However, as long as these images can be cached, the challenge can be mitigated.

An alternative approach is to use Dynamic Media technology to hand-off image manipulation entirely. Additionally, you can deploy Brand Portal that not only takes over rendition generation responsibilities from the Experience Manager infrastructure, but also the entire publish tier.

ImageMagick imagemagick

If you customize the DAM Update Asset workflow to generate renditions using ImageMagick, �۶���Ƶ recommends you modify the policy.xml file at /etc/ImageMagick/. By default, ImageMagick uses the entire available disk space on the OS volume, and the available memory. Make the following configuration changes within the policymap section of policy.xml to limit these resources.

<policymap>
  <!-- <policy domain="system" name="precision" value="6"/> -->
  <policy domain="resource" name="temporary-path" value="/ephemeral0/imagemagick_tmp"/>
  <policy domain="resource" name="memory" value="1000MiB"/>
  <policy domain="resource" name="map" value="1000MiB"/>
  <!-- <policy domain="resource" name="area" value="1gb"/> -->
  <policy domain="resource" name="disk" value="10000MiB"/>
  <!-- <policy domain="resource" name="file" value="768"/> -->
  <policy domain="resource" name="thread" value="1"/>
  <policy domain="resource" name="throttle" value="50"/>
  <!-- <policy domain="resource" name="time" value="3600"/> -->
</policymap>

In addition, set the path of ImageMagick’s temporary folder in the configure.xml file (or by setting the environment variable MAGICK_TEMPORARY_PATH) to a disk partition that has sufficient space and IOPS.

If you are using Experience Manager on �۶���Ƶ Managed Services (AMS), reach out to �۶���Ƶ Customer Support if you plan to process lots of large PSD or PSB files. Work with �۶���Ƶ Customer Support representative to implement these best practices for your AMS deployment and to choose the best possible tools and models for �۶���Ƶ’s proprietary formats. Experience Manager may not process very high-resolution PSB files that are more than 30000 x 23000 pixels.

XMP writeback xmp-writeback

XMP writeback updates the original asset whenever metadata is modified in Experience Manager, which results in the following:

The outcomes listed consume considerable resources. Therefore, �۶���Ƶ recommends disabling XMP writeback if it is not required. For more information, see XMP writeback.

Importing a large amount of metadata can result in resource-intensive XMP writeback activity if run workflows flag is checked. Plan such an import during lean server usage so that performance for other users is not impacted.

Replication replication

When replicating assets to a large number of publish instances, for example, in a Sites implementation, �۶���Ƶ recommends you use chain replication. In this case, the author instance replicates to a single publish instance which in turn replicates to the other publish instances, freeing up the author instance.

Configure chain replication configure-chain-replication

Search indexes search-indexes

Install the latest Service Packs and performance-related hotfixes as those often include updates to system indexes. See performance tuning tips for some index optimizations.

Create custom indexes for queries that you run often. For details, see and crafting custom indexes. For additional insights around query and index best practices, see Best Practices for Queries and Indexing.

Lucene index configurations lucene-index-configurations

Some optimizations can be done on the Oak index configurations that can help improve Experience Manager Assets performance. Update the index configurations to improve the re-indexing time:

If your users do not need to do full-text search of assets, say for example, searching through text in PDF documents, then disable it. You improve index performance by disabling full-text indexing. To disable Apache Lucene text extraction, follow these steps:

Guess Total guess-total

When creating queries that generate large result sets, use the guessTotal parameter to avoid heavy memory utilization when you run them.

Known issues known-issues

Large files large-files

There are two major known issues related to large files in Experience Manager. When files reach sizes greater than 2 GB, cold standby synchronization can run into an out-of-memory situation. In some cases, it prevents standby sync from running. In other cases, it causes the primary instance to crash. This scenario applies to any file in Experience Manager that is larger than 2GB, including content packages.

Likewise, when files reach 2 GB in size while using a shared S3 data store, it may take some time for the file to be fully persisted from the cache to the filesystem. As a result, when using binary-less replication, it is possible that the binary data may not have been persisted before replication completes. This situation can lead to issues, especially if the availability of data is important.

Performance testing performance-testing

For every Experience Manager deployment, establish a performance testing regime that can identify and resolve bottlenecks quickly. Here are some key areas to focus on.

Network testing network-testing

For all network performance concerns from the customer, perform the following tasks:

Experience Manager deployment testing aem-deployment-testing

To minimize latency and achieve high throughput through efficient CPU utilization and load-sharing, monitor the performance of your Experience Manager deployment regularly. In particular:

Experience Manager Assets performance checklist and impact of asset management tasks checklist