EFS File System: A Deep Dive in AWS Resources & Best Practices to Adopt

In the rapidly evolving landscape of cloud computing, organizations are increasingly adopting microservices architectures, containerized applications, and distributed systems that require shared, scalable storage solutions. Amazon Elastic File System (EFS) has emerged as a cornerstone technology for teams building modern cloud-native applications that need persistent, shared storage across multiple compute instances and services.

While traditional block storage solutions like EBS volumes excel at providing dedicated storage for individual instances, they fall short when applications need to share data across multiple systems. Network-attached storage (NAS) solutions in on-premises environments have long filled this gap, but they come with significant operational overhead and limited scalability. EFS bridges this divide by providing a fully managed, elastic, and highly available NFS file system that can be simultaneously accessed by thousands of EC2 instances, containers, and serverless functions.

The growing complexity of modern applications has made shared storage a critical component of cloud infrastructure. According to recent industry analysis, over 60% of enterprise applications now require some form of shared storage for configuration files, application data, or content distribution. This shift has driven significant adoption of EFS across various industries, with usage growing by over 150% year-over-year as organizations migrate from traditional shared storage solutions to cloud-native alternatives.

In this blog post we will learn about what EFS File System is, how you can configure and work with it using Terraform, and learn about the best practices for this service.

What is EFS File System?

EFS File System is a fully managed, elastic Network File System (NFS) that provides scalable file storage for use with AWS compute services including EC2, ECS, EKS, and Lambda. Unlike traditional block storage, EFS offers concurrent access to file data across multiple instances, making it the go-to solution for applications that require shared storage capabilities.

At its core, EFS abstracts away the complexity of traditional NFS deployments while providing the familiar POSIX-compliant file system interface that applications expect. This means developers can work with files and directories using standard file system operations without worrying about provisioning, scaling, or managing the underlying infrastructure. The service automatically scales from gigabytes to petabytes of storage capacity, growing and shrinking based on actual usage patterns.

The architecture of EFS is built around high availability and durability. Files are automatically replicated across multiple Availability Zones within a region, providing 99.999999999% (11 9's) of durability. This replication happens transparently to applications, ensuring that data remains accessible even if individual components fail. The service integrates seamlessly with other AWS services, including VPC networking, IAM for access control, and CloudWatch for monitoring.

Storage Classes and Performance Modes

EFS offers multiple storage classes optimized for different access patterns and cost requirements. The Standard storage class provides the lowest latency per operation and can achieve up to 7,000 file operations per second. For workloads with infrequent access patterns, the Infrequent Access (IA) storage class offers significant cost savings by storing files at a lower cost while charging a small fee per access.

The One Zone storage class provides an even more cost-effective option by storing files in a single Availability Zone, reducing costs by up to 47% compared to Standard storage. This option works well for development environments or workloads that don't require the cross-AZ redundancy of regional storage classes. The One Zone-IA storage class combines single-AZ storage with infrequent access pricing for maximum cost optimization.

Performance modes in EFS cater to different workload requirements. General Purpose mode provides the lowest latency per operation and can achieve up to 7,000 file operations per second. Max I/O mode can scale to higher levels of aggregate throughput and operations per second, making it suitable for applications with thousands of concurrent clients. The choice between these modes depends on your specific latency and throughput requirements.

EFS also supports two throughput modes: Provisioned and Bursting. Bursting throughput scales with the size of your file system, providing baseline performance that can burst to higher levels when needed. Provisioned throughput allows you to specify the throughput your application requires, independent of the amount of data stored, which is particularly useful for workloads with high throughput requirements relative to their storage size.

Security and Access Control

Security in EFS operates at multiple layers to provide comprehensive protection for your data. At the network level, VPC integration ensures that file system access is isolated within your virtual private cloud. Security groups act as virtual firewalls, controlling which EC2 instances can access your file system through NFS mount operations.

Access control can be configured using traditional POSIX permissions or through AWS Identity and Access Management (IAM) policies. POSIX permissions work at the file and directory level, allowing granular control over who can read, write, or execute specific files. IAM policies provide AWS-level access control, enabling you to define which users or roles can perform specific EFS operations like creating file systems or managing access points.

EFS Access Points provide a more granular way to control access to your file system. Each access point can enforce a specific user identity, enforce a root directory, and apply creation permissions for new files and directories. This feature is particularly useful in multi-tenant environments where different applications or users need access to specific portions of the file system while maintaining isolation from other parts.

Strategic Importance for Modern Infrastructure

The strategic importance of EFS File System extends far beyond simple storage needs, representing a fundamental shift in how organizations approach shared data management in cloud environments. As companies migrate from monolithic applications to microservices architectures, the need for storage solutions that can be accessed concurrently by multiple services becomes critical for maintaining data consistency and reducing operational complexity.

Recent surveys indicate that over 75% of organizations running containerized workloads require persistent shared storage for configuration management, application state, and data sharing between services. EFS addresses this need by providing a storage solution that scales with demand while maintaining the performance characteristics required by modern applications.

Cost Optimization and Operational Efficiency

EFS delivers significant cost optimization opportunities through its intelligent tiering and lifecycle management capabilities. Organizations can reduce storage costs by up to 85% by automatically moving infrequently accessed data to lower-cost storage classes. This automatic optimization happens without application changes or manual intervention, making it a transparent way to optimize infrastructure spending.

The pay-as-you-use pricing model eliminates the need for capacity planning and over-provisioning that characterizes traditional storage solutions. Unlike block storage where you must provision specific amounts of storage upfront, EFS scales automatically based on actual usage, ensuring you only pay for what you consume. This elastic scaling has helped organizations reduce storage costs by 30-60% compared to traditional approaches.

Real-world implementations demonstrate substantial operational benefits. A leading media company reduced their storage management overhead by 70% after migrating from self-managed NFS servers to EFS, while simultaneously improving availability and reducing the time required for storage scaling operations from hours to minutes. The elimination of storage server maintenance, backup management, and capacity planning freed up engineering resources to focus on application development rather than infrastructure management.

Scalability and High Availability

EFS provides virtually unlimited scalability, automatically growing and shrinking based on file system usage without disrupting applications. This elastic nature means applications can scale from handling gigabytes to petabytes of data without requiring architectural changes or manual intervention. The ability to scale throughput independently of storage capacity allows applications to maintain consistent performance regardless of data volume.

The high availability architecture of EFS, with automatic replication across multiple Availability Zones, provides 99.999999999% durability without requiring additional configuration or management. This level of reliability eliminates single points of failure that often plague traditional shared storage solutions and reduces the risk of data loss that can impact business operations.

For organizations running mission-critical applications, EFS provides the reliability and availability characteristics needed to support always-on services. The service's ability to handle thousands of concurrent connections while maintaining consistent performance makes it suitable for applications ranging from content management systems to high-performance computing workloads.

Integration with Modern Application Patterns

EFS seamlessly integrates with containerized applications running on Amazon ECS and Amazon EKS, providing persistent storage that can be shared across multiple containers and pods. This integration supports modern application patterns like microservices architectures where multiple services need access to shared configuration files, application data, or content repositories.

The service's compatibility with serverless computing through AWS Lambda enables new architectural patterns where functions can access shared file systems for processing large datasets or managing shared state. This capability bridges the gap between traditional server-based applications and serverless architectures, allowing organizations to adopt serverless patterns while maintaining access to persistent shared storage.

Key Features and Capabilities

Elastic Scaling and Performance

EFS automatically scales storage capacity up and down based on actual usage, eliminating the need for manual capacity planning or storage provisioning. This elastic scaling happens transparently to applications, ensuring that storage never becomes a bottleneck for application growth. The service can scale from a few gigabytes to petabytes of storage while maintaining consistent performance characteristics.

Performance scaling in EFS is designed to match the needs of modern applications. The service can deliver up to 10 GB/s of throughput and more than 500,000 IOPS for workloads that require high-performance file access. This level of performance makes EFS suitable for workloads ranging from simple file sharing to high-performance computing applications that require intensive file I/O operations.

Multi-AZ Durability and Availability

Data stored in EFS is automatically replicated across multiple Availability Zones within a region, providing protection against component failures and ensuring high availability. This replication happens synchronously, meaning that data is written to multiple locations before the write operation is acknowledged to the application, ensuring consistency and durability.

The multi-AZ architecture also provides automatic failover capabilities. If a particular Availability Zone becomes unavailable, applications can continue accessing their data through mount targets in other zones without manual intervention. This level of availability is crucial for production applications that require continuous access to shared data.

POSIX Compliance and NFS Compatibility

EFS provides full POSIX compliance, supporting standard file system operations including hierarchical directories, file locking, and symbolic links. This compatibility ensures that existing applications designed for traditional file systems can use EFS without modification, reducing migration complexity and development effort.

The NFS v4.1 protocol support enables EFS to work with a wide range of operating systems and applications. This standards-based approach ensures compatibility with existing tools and workflows while providing the performance and reliability benefits of a managed service.

Flexible Access Control

EFS supports multiple access control mechanisms to meet different security requirements. Traditional POSIX permissions provide file-level access control, while AWS IAM integration enables policy-based access management at the API level. This dual approach allows organizations to implement security policies that align with their existing access control frameworks.

Access Points provide an additional layer of access control, enabling fine-grained control over how different applications or users access the file system. Each access point can enforce specific user and group identities, restrict access to specific directories, and apply creation permissions for new files and directories.

Integration Ecosystem

EFS integrates seamlessly with a comprehensive ecosystem of AWS services, enabling organizations to build sophisticated architectures that leverage shared storage across multiple compute platforms. The service's native integration with AWS networking, security, and monitoring services provides a foundation for building secure, scalable, and observable applications.

At the time of writing there are 25+ AWS services that integrate with EFS File System in some capacity. EC2 instances, ECS tasks, EKS pods, and Lambda functions can all access EFS file systems, providing flexibility in how applications consume shared storage.

The compute integration extends beyond simple file access to include advanced features like persistent storage for containers, shared configuration management, and distributed data processing. ECS services can mount EFS file systems as volumes, enabling stateful containerized applications that maintain data persistence across container restarts and deployments.

Container orchestration platforms like Amazon EKS benefit from EFS integration through the EFS CSI driver, which provides dynamic volume provisioning and persistent volume claims that Kubernetes applications can use to access shared storage. This integration enables cloud-native applications to leverage persistent shared storage while maintaining the portability and scalability characteristics of containerized deployments.

Lambda functions can mount EFS file systems to access shared libraries, configuration files, or large datasets that exceed the temporary storage limits of the Lambda execution environment. This capability enables new architectural patterns where serverless functions can process large amounts of data stored in shared file systems while maintaining the cost and operational benefits of serverless computing.

Pricing and Scale Considerations

EFS pricing follows a pay-as-you-use model with several dimensions that affect total cost. Storage pricing varies by storage class, with Standard storage offering the highest performance at a premium price, while Infrequent Access and One Zone storage classes provide significant cost savings for data accessed less frequently.

The pricing structure includes charges for storage capacity, data transfer, and in some cases, provisioned throughput. Standard storage costs approximately $0.30 per GB per month, while Infrequent Access storage reduces costs to around $0.025 per GB per month. One Zone storage classes offer additional savings by storing data in a single Availability Zone, reducing costs by up to 47% compared to regional storage options.

Request pricing applies to Infrequent Access storage classes, with charges for read and write operations. This pricing model encourages the use of lifecycle policies to automatically move infrequently accessed data to lower-cost storage classes, optimizing costs without requiring manual intervention.

Scale Characteristics

EFS scales automatically from gigabytes to petabytes of storage capacity without requiring manual intervention or application changes. The service can support thousands of concurrent connections, making it suitable for applications ranging from small development environments to large-scale production workloads.

Performance scaling in EFS is designed to grow with storage utilization in Bursting mode, or can be independently configured in Provisioned mode. Bursting mode provides baseline performance that scales with the size of your file system, with the ability to burst to higher performance levels when needed. Provisioned mode allows you to specify exact throughput requirements independent of storage size, which is particularly useful for applications with high performance requirements relative to their data volume.

Throughput limits vary by mode and configuration, with General Purpose mode supporting up to 7,000 operations per second and Max I/O mode supporting higher aggregate throughput and operations per second. These limits are designed to accommodate the vast majority of application workloads while providing predictable performance characteristics.

Enterprise Considerations

Enterprise deployments of EFS benefit from advanced features like backup integration with AWS Backup, encryption at rest and in transit, and integration with AWS Key Management Service for encryption key management. These features provide the security and compliance capabilities required by enterprise applications while maintaining the operational simplicity of a managed service.

Regional availability and disaster recovery capabilities make EFS suitable for enterprise workloads that require high availability and business continuity. The service's ability to replicate data across multiple Availability Zones within a region provides protection against localized failures, while backup integration enables point-in-time recovery and long-term data retention.

For organizations requiring file system access from on-premises environments, EFS can be accessed through AWS Direct Connect or VPN connections, enabling hybrid architectures that span cloud and on-premises infrastructure. This capability supports migration scenarios where applications gradually move to the cloud while maintaining access to shared data.

When compared to alternatives like Amazon FSx for NetApp ONTAP or third-party NAS solutions, EFS provides a simpler operational model with lower management overhead. However, for infrastructure running on AWS this is the most cost-effective and operationally efficient solution for NFS workloads that don't require advanced features like high-performance parallel file systems or Windows-specific file sharing protocols.

Organizations evaluating EFS should consider the total cost of ownership, including storage costs, data transfer charges, and operational overhead. While the per-GB cost of EFS may be higher than some alternatives, the elimination of management overhead, automatic scaling, and integrated backup capabilities often result in lower total costs for most workloads.

Managing EFS File System using Terraform

Terraform provides comprehensive support for managing EFS File Systems, though the complexity can vary significantly based on your specific requirements. The primary resource is aws_efs_file_system, but a production-ready implementation often requires multiple complementary resources including mount targets, access points, backup policies, and security configurations.

The main challenge when working with EFS in Terraform lies in properly configuring the networking components and access controls. Unlike simple storage resources, EFS requires careful coordination between the file system itself, mount targets in each subnet, security groups, and access points. Each mount target must be placed in a different availability zone to provide high availability, and the security groups must allow NFS traffic on port 2049 between your compute resources and the file system.

Production-Ready EFS with Multi-AZ Mount Targets

A typical production deployment requires EFS to be accessible across multiple availability zones for high availability and fault tolerance. This scenario is common when running containerized applications with ECS or EKS clusters that need shared storage for application data, configuration files, or logs.

The creation_token parameter serves as a unique identifier for the file system and helps prevent accidental duplicate creation. Setting encrypted = true enables encryption at rest, while the KMS key provides additional security control over the encryption keys. The performance_mode setting determines whether the file system is optimized for lower latency (generalPurpose) or higher levels of aggregate throughput and operations per second (maxIO).

Mount targets are required in each subnet where you want to access the file system. The security group configuration allows NFS traffic on port 2049 from your application servers while blocking unnecessary access. The lifecycle policies help manage costs by automatically transitioning infrequently accessed files to the lower-cost Infrequent Access (IA) storage class.

EFS Access Points for Application Isolation

Access points provide a way to manage access to specific directories within an EFS file system, making them ideal for multi-tenant applications or scenarios where different applications need isolated access to shared storage.

Access points provide several key benefits for application architecture. The root_directory configuration allows you to restrict access to specific paths within the file system, while posix_user settings ensure that files are created with appropriate ownership and permissions. The creation_info block automatically creates the directory structure with the specified permissions if it doesn't exist.

When integrating with ECS or EKS, access points simplify the security model by providing path-based access control without requiring complex IAM policies. The transit_encryption setting ensures that data is encrypted while moving between your applications and the EFS file system. The backup policy enables automatic point-in-time backups through AWS Backup, providing additional data protection without manual intervention.

Best practices for EFS File System

Managing EFS file systems effectively requires attention to performance, security, cost optimization, and operational considerations. These practices have been developed through real-world deployments and can help you avoid common pitfalls while maximizing the value of your EFS implementation.

Implement Proper Network Security Controls

Why it matters: EFS file systems are accessed over the network using NFS protocol, making them potential targets for unauthorized access if not properly secured. Network-level security provides your first line of defense against potential data breaches.

Implementation: Configure security groups to restrict access to only the ports and sources that need EFS access. NFS uses port 2049, so your security group rules should be specific about which subnets or security groups can access this port.

Create dedicated security groups for EFS access rather than using overly permissive rules. Consider implementing VPC flow logs to monitor network traffic to your EFS mount targets. For highly sensitive environments, place EFS mount targets in private subnets and use VPC endpoints for AWS service communications. Network ACLs can provide an additional layer of security by controlling traffic at the subnet level.

Choose the Right Performance Mode and Throughput Configuration

Why it matters: EFS performance characteristics directly impact application responsiveness and user experience. Incorrect performance settings can lead to unnecessary costs or poor application performance, especially for latency-sensitive workloads.

Implementation: Select performance modes based on your application requirements. General Purpose mode provides the lowest latency but is limited to 7,000 file operations per second. Max I/O mode can scale to higher levels of aggregate throughput but with slightly higher latencies for file operations.

Monitor your file system's performance using CloudWatch metrics like TotalIOTime and PercentIOLimit. If your application requires consistent high throughput, consider Provisioned Throughput mode. For applications with variable workloads, Bursting Throughput mode may be more cost-effective. Test different configurations in non-production environments to find the optimal balance between performance and cost.

Enable Encryption for Data Protection

Why it matters: Data encryption protects sensitive information both at rest and in transit. Many compliance frameworks require encryption for file systems containing sensitive data, and encryption helps maintain data confidentiality even if unauthorized access occurs.

Implementation: Enable encryption at rest when creating the file system and use TLS encryption for data in transit. EFS encryption uses AWS KMS keys, giving you control over key management and access policies.

Create dedicated KMS keys for EFS encryption rather than using the default AWS managed key. This gives you better control over key rotation and access policies. Configure your mount helpers to use TLS encryption by adding the _netdev,tls options to your /etc/fstab entries. Monitor KMS key usage and set up appropriate key rotation policies to maintain security over time.

Implement Intelligent Tiering and Lifecycle Management

Why it matters: File storage costs can grow significantly over time, especially for infrequently accessed data. Intelligent tiering can reduce storage costs by up to 92% for files that aren't accessed regularly while maintaining the same level of availability.

Implementation: Configure lifecycle policies to automatically move files to Infrequent Access storage class based on access patterns. Set up policies that align with your data access requirements and compliance needs.

Monitor storage usage patterns using CloudWatch metrics to understand which lifecycle policies provide the best cost savings. Consider different transition periods for different types of data - frequently accessed application data might use a 30-day transition, while backup data might transition after 7 days. Use EFS Access Points to apply different lifecycle policies to different directories within the same file system.

Configure Proper Backup and Recovery Strategies

Why it matters: Data loss can have catastrophic business impacts, and file systems are particularly vulnerable to accidental deletion, corruption, or ransomware attacks. Automated backup policies provide point-in-time recovery capabilities for your file system data.

Implementation: Enable AWS Backup for EFS file systems to create automatic, policy-driven backups. Configure backup schedules that align with your recovery point objectives (RPO) and recovery time objectives (RTO).

Test backup and restore procedures regularly to verify that your recovery processes work correctly. Consider cross-region backup replication for disaster recovery scenarios. Set up monitoring and alerting for backup failures, and establish clear procedures for different types of data recovery scenarios. Document backup retention policies and ensure they align with your compliance requirements.

Optimize Mount Target Placement and Access Patterns

Why it matters: Mount target placement affects network performance, availability, and data transfer costs. Poor placement decisions can result in unnecessary cross-AZ traffic charges and reduced application performance.

Implementation: Place mount targets in the same availability zones as your compute resources to minimize latency and data transfer costs. Use multiple mount targets for high availability while considering the network topology of your applications.

Configure clients to use local mount targets when possible to reduce network latency and costs. Monitor mount target utilization and network performance metrics to identify potential bottlenecks. Consider using EFS Utils for improved performance and reliability when mounting file systems. Implement connection pooling and caching strategies in applications to reduce the number of file system operations.

These best practices form the foundation of a robust EFS implementation that balances performance, security, cost-effectiveness, and operational simplicity. Regular review and adjustment of these configurations based on changing application requirements and AWS service updates will help maintain optimal file system performance over time.

Product Integration

EFS File System integrates seamlessly with a wide range of AWS services, creating a comprehensive ecosystem for shared storage needs. The service works particularly well with compute services like EC2 instances, ECS containers, and Lambda functions, providing persistent storage that can be accessed concurrently across multiple workloads.

Container orchestration platforms benefit significantly from EFS integration. ECS clusters can mount EFS volumes across multiple tasks, while EKS clusters can use the EFS CSI driver to provision persistent volumes dynamically. This integration allows stateful applications to maintain data consistency across container restarts and deployments.

The service also integrates with AWS networking components through VPC endpoints for private connectivity, and works within security groups to control access at the network level. EFS mount targets are deployed across multiple subnets for high availability, and can be accessed from different availability zones within the same region.

For backup and disaster recovery, EFS integrates with AWS Backup service, allowing automated backup schedules and cross-region replication. The service also works with CloudWatch for monitoring file system performance and usage metrics, providing insights into throughput, IOPS, and client connection patterns.

Use Cases

Content Management and Media Processing

EFS File System excels in content management scenarios where multiple systems need concurrent access to shared media files, documents, or web content. News organizations and media companies often use EFS to store raw video footage, images, and audio files that need to be processed by multiple editing applications simultaneously. The file system's ability to scale automatically means that storage capacity grows with content volume without manual intervention.

This use case provides significant business value by reducing content processing times and enabling collaborative workflows. Teams can work on the same projects simultaneously without complex file synchronization processes, leading to faster time-to-market for digital content.

Application Configuration and Shared Libraries

Development teams frequently use EFS to store application configuration files, shared libraries, and deployment artifacts that need to be accessible across multiple application instances. This approach is particularly valuable in microservices architectures where multiple services need access to common configuration data or shared code libraries.

The business impact includes reduced deployment complexity, improved consistency across environments, and simplified configuration management. Teams can update shared configurations in one location and have changes propagate to all connected services automatically.

Data Analytics and Big Data Processing

EFS provides an excellent storage foundation for data analytics workloads where multiple processing nodes need access to the same datasets. Data scientists and analysts can store large datasets on EFS and process them using distributed computing frameworks like Apache Spark or Hadoop, with multiple worker nodes accessing the same data simultaneously.

This use case delivers business value through improved data processing efficiency and reduced data movement costs. Instead of copying large datasets to each processing node, teams can process data in place, significantly reducing storage costs and processing time.

Limitations

Performance Characteristics

EFS performance can be a limiting factor for certain workloads, particularly those requiring very high IOPS or low latency access patterns. While EFS offers different performance modes (General Purpose and Max I/O), the throughput is often lower than what you might achieve with dedicated EBS volumes for single-instance workloads. The network-based nature of NFS also introduces latency that may not be suitable for database applications or other latency-sensitive workloads.

Cost Considerations

EFS pricing can become expensive for large-scale storage needs compared to other AWS storage services. The cost per GB is significantly higher than S3 or EBS, making it less suitable for archival storage or scenarios where cost optimization is the primary concern. The pricing model charges for actual storage used, which can lead to unexpected costs if not properly monitored.

Regional Limitations

EFS is a regional service, meaning file systems cannot be directly accessed from other AWS regions. While AWS provides EFS-to-EFS backup for cross-region replication, this adds complexity and cost for multi-region deployments. Organizations with global applications may need to implement additional architecture patterns to work around these regional boundaries.

Conclusions

The EFS File System service is a powerful managed storage solution that fills a critical gap in AWS's storage offerings. It supports concurrent access patterns, automatic scaling, and seamless integration with various compute services. For organizations building modern distributed applications, microservices architectures, or content management systems this service offers all of what you might need.

The integration ecosystem spans compute, container, and serverless services, making EFS a versatile choice for shared storage requirements. However, you will most likely integrate your own custom applications with EFS File System as well. Changes to EFS configurations can impact multiple dependent services and applications, making proper impact assessment critical before modifications.

With Overmind's comprehensive dependency mapping and risk analysis, teams can confidently manage EFS File System changes while understanding the full scope of potential impacts across their infrastructure. This visibility helps prevent storage-related outages and ensures that shared storage modifications don't unexpectedly affect dependent applications and services.