AEM and Amazon EFS for a Shared Content Store in the Cloud
Adobe Experience Manager deployments increasingly run on cloud infrastructure, where content authors, publishers, asset processors, and integration services may operate across multiple availability zones. That flexibility introduces an architectural question: how should repository data and binary assets be shared reliably between application nodes?
Amazon Elastic File System (EFS) can provide a managed, elastic NFS file system for selected AEM storage requirements. Used carefully, it can simplify access to shared binaries, logs, packages, and operational files. It is not, however, a universal replacement for AEM’s repository architecture or a shortcut to making every node fully active and writable.
A sound design begins by separating AEM’s content repository, binary data, indexes, dispatcher cache, and deployment artifacts. Each category has different performance, consistency, and recovery requirements. Treating them as one undifferentiated file share can create latency, locking, and availability problems that are difficult to diagnose later.
Where EFS fits in an AEM architecture
EFS is a regional file service that exposes storage through NFS. Multiple EC2 instances, containers, or other compatible compute resources can mount the same file system, making it useful when several AEM-related processes need access to common files. Capacity grows automatically, so teams do not need to provision a fixed disk volume for an unpredictable media library.
For AEM, the strongest use cases usually involve shared binaries and supporting application data. An EFS-backed data store can allow instances in a farm to reference the same large assets instead of maintaining separate copies. It may also support shared package repositories, workflow exchange directories, or operational files when the application and deployment model require them.
The repository’s mutable segment store deserves more caution. Traditional AEM TarMK deployments are designed around a primary node and a separate standby or cold-backup strategy, rather than several independently writable nodes sharing the same segment files. Mounting a common EFS path does not change those repository semantics. A shared file system must be compatible with the exact AEM storage mode and Adobe support guidance used by the project.
Separating repository data from binary content
AEM stores structured content in the Java Content Repository while large files, such as images, videos, and documents, can be handled through a binary data store. This distinction is central to a cloud design. Structured repository data often benefits from low-latency local storage, while binaries demand scalable capacity and efficient sharing.
An architecture may therefore keep the AEM segment store and indexes on high-performance attached storage, while placing the binary data store on EFS. The result is a hybrid storage model: local or block storage handles latency-sensitive repository operations, and elastic file storage handles large, shared objects. The exact arrangement depends on the AEM version, topology, licensing, and validated deployment pattern.
AEM’s datastore configuration must be consistent across every node that accesses it. Repository paths, mount points, permissions, and service users should be identical from the application’s perspective. If one node sees a different directory, stale mount, or incomplete binary path, requests can fail intermittently and produce misleading repository or asset errors.
Performance, consistency, and network design
EFS performance depends on throughput mode, performance mode, file size, access patterns, and the network path between the application and storage. General Purpose performance mode is commonly selected when low operation latency matters, while Elastic Throughput can suit workloads with variable demand. A high-volume asset ingestion pipeline may need a different profile from an authoring environment with modest traffic.
Every AEM node should use an EFS mount target in its own Availability Zone where possible. This keeps traffic within the regional network design and avoids unnecessary cross-zone paths. Security groups must permit NFS traffic on port 2049, while network ACLs, route tables, and DNS resolution need to support the mount consistently during startup and failover.
NFS latency is different from local NVMe or EBS latency. Repository commits, index updates, workflow steps, and package operations can become slower when many small file operations traverse the network. Performance testing should reproduce realistic authoring activity, asset uploads, replication, indexing, and cache warm-up instead of relying on a simple file-copy benchmark.
The following comparison helps clarify where each storage option may fit:
| AEM workload | Common storage choice | Why it may fit | Main concern |
|---|---|---|---|
| Segment store | Fast EBS or validated local storage | Predictable repository latency | Must follow AEM topology rules |
| Oak indexes | Fast EBS or local storage | Supports frequent reads and updates | Network file latency can reduce responsiveness |
| Shared binary data store | EFS | Elastic capacity and multi-node access | Mount consistency and throughput |
| Dispatcher cache | Local disk or instance storage | Fast, disposable cache operations | It should not be treated as the source of truth |
| Backups and exports | S3, backup service, or archive storage | Durable and cost-effective retention | Restore procedures must be tested |
| Deployment packages | EFS, artifact repository, or pipeline storage | Makes packages available to several nodes | Avoid uncontrolled manual changes |
Availability and recovery planning
A shared content store improves access, but it does not automatically create a complete disaster recovery strategy. EFS is regional and can be highly available across Availability Zones, yet accidental deletion, application corruption, or an invalid deployment can still affect shared files. Recovery requires independent protection and clear restoration procedures.
AWS Backup or another approved backup process can protect EFS data according to retention and compliance requirements. File-system backups should be coordinated with AEM repository backups, package exports, database snapshots, and configuration management. Restoring binaries without the repository metadata that references them may leave content incomplete or unusable.
Recovery objectives should be defined before production launch. A team should know how quickly it must restore service, how much content loss is acceptable, and whether it can rebuild an environment from infrastructure code. A separate recovery environment is valuable for testing mounts, permissions, repository consistency, dispatcher behavior, and replication after restoration.
For operational guidance around event resources and related access details, the site’s frequently asked questions can provide useful context. In an implementation project, equivalent internal documentation should identify storage ownership, backup responsibility, escalation paths, and the exact sequence for bringing AEM nodes back online.
Security and operational controls
EFS supports encryption at rest through AWS Key Management Service and encryption in transit through TLS for supported mount configurations. Encryption should be combined with least-privilege IAM, tightly scoped security groups, private subnets, and controlled administrative access. The file system should not be exposed through public routes simply because application nodes need shared storage.
POSIX ownership and permissions are equally important. AEM processes must have the access required to read and write their designated paths, but broad world-writable permissions create unnecessary risk. Access points can help present specific directories with controlled identities and permissions, particularly when several services use the same file system for different purposes.
Monitoring should include EFS burst or provisioned throughput, client connections, storage bytes, mount errors, network latency, AEM repository health, indexing time, workflow queues, and failed asset operations. Logs should make it possible to correlate an AEM timeout with an NFS mount issue or a throughput limit rather than treating every failure as an application defect.
Choosing the right topology
A common production pattern uses dedicated author and publish tiers, with publishers scaled horizontally behind a load balancer and dispatchers controlling public delivery. The author tier may remain more carefully constrained because repository writes, workflows, indexing, and administrative operations are concentrated there. EFS can support shared binaries across appropriate nodes, while the repository topology remains governed by AEM’s supported clustering model.
For high-volume publishing, a shared binary store can reduce duplicate asset storage and simplify node replacement. Yet horizontal scale does not remove the need for replication queues, cache invalidation, index management, and controlled deployments. A new node must receive the correct repository state, configuration, code packages, and mount access before it accepts traffic.
Teams evaluating the design should validate it against the specific AEM release and cloud runtime. Adobe’s supported deployment documentation, release notes, and reference architectures should take precedence over generic NFS advice. A technically possible mount configuration is not automatically a supported production repository configuration.
Practical decisions before implementation
A pilot should measure authoring latency, asset upload speed, binary retrieval, workflow completion, package installation, indexing, failover, and recovery. Tests should include concurrent access from multiple nodes and realistic file counts. Small-file-heavy workloads can behave very differently from large media transfers, so both need representation.
The implementation should also document mount behavior during reboot, node replacement, scaling events, and EFS service interruptions. Infrastructure as code can standardize file systems, access points, security rules, mount targets, alarms, and backup policies. Application configuration management should keep AEM paths and service settings synchronized across environments.
Recommended safeguards include:
- Keep latency-sensitive repository files and indexes on storage validated for the chosen AEM topology.
- Use EFS selectively for shared binaries or other workloads that genuinely need elastic multi-node access.
- Test throughput, NFS latency, locking behavior, and concurrent AEM operations before production approval.
- Encrypt storage, restrict network access, enforce POSIX permissions, and monitor mount and repository health.
- Pair EFS backups with repository, configuration, package, and disaster recovery procedures.
Cloud storage decisions have a direct effect on authoring experience, deployment reliability, and incident recovery. Review the architecture against your AEM version, model realistic traffic, and document the supported storage boundaries before moving shared content into production. For attendees and developers exploring the broader AEM ecosystem, the event app download offers another route to conference resources and technical session material.