Amazon EFS Deep Dive: Practical Shared File Storage Design Through Comparison with Google Cloud Filestore and Azure Files

Introduction

Amazon EFS (Amazon Elastic File System) is AWS’s fully managed shared file storage service. AWS officially explains that EFS can be mounted simultaneously from multiple EC2 instances, containers, and serverless compute platforms, and can scale to petabyte levels according to demand. AWS also states that EFS is designed for parallel access and provides the throughput, IOPS, and low latency required by a wide range of workloads. :contentReference[oaicite:0]{index=0}

This topic is useful for several types of readers. First, infrastructure engineers who want to share the same file set across multiple servers. Second, platform engineers who need to safely handle ReadWriteMany shared storage in Kubernetes or container platforms. It is also useful for architects who want to compare AWS, GCP, and Azure and understand how to choose shared file storage. Google Cloud Filestore is provided as persistent file storage that can be accessed simultaneously from multiple instances, and its documentation explains that GKE PersistentVolumes can be used as read-write-many volumes from multiple nodes. Azure Files also provides both SMB and NFS protocols, and its AKS documentation states that file shares can be mounted from multiple pods. :contentReference[oaicite:1]{index=1}

The main conclusion is that Amazon EFS is a very natural choice when you want to use a shared file system straightforwardly on AWS. Meanwhile, GCP Filestore is easy to understand in terms of tier design and regional configuration, while Azure Files offers flexible design through combinations of SMB/NFS and redundancy options. In other words, rather than asking which one is best, it is safer to choose based on which cloud you use, what shared file requirements you have, and what operational responsibilities you want to take on. :contentReference[oaicite:2]{index=2}

1. What Is Amazon EFS?

Amazon EFS is AWS’s shared file storage service, allowing multiple compute resources, including EC2, to access the same file system at the same time. AWS officially explains that EFS scales serverlessly, can grow to petabyte scale, and provides low latency and high throughput for a broad range of workloads. :contentReference[oaicite:3]{index=3}

The important point is not to think of EFS as “shared EBS.” EBS is basically block storage for a single instance, while EFS is designed from the beginning as a shared file system. That makes it suitable for workloads requiring parallel access from multiple nodes, such as shared WordPress content, common application assets, ML training data, shared container workspaces, and intermediate files for rendering or analysis. AWS documentation also explains EFS on the assumption that it is mounted from Amazon EC2 within a VPC. :contentReference[oaicite:4]{index=4}

EFS also has two file system types: Regional and One Zone. AWS explains that Regional stores data redundantly across multiple Availability Zones and supports continued access to data even if one or more AZs become unavailable. One Zone, on the other hand, stores data in a single AZ and is suited to cases where cost optimization is more important than availability requirements. AWS itself generally recommends Regional. :contentReference[oaicite:5]{index=5}

2. The Core Value of EFS: Sharing, Automatic Scaling, and Managed Operations

The biggest appeal of Amazon EFS is that it makes it easy to handle shared file systems without detailed manual capacity planning. AWS explains that EFS scales serverlessly and provides multiple throughput modes, including Elastic Throughput. With Elastic Throughput, throughput changes automatically according to read and write demand, making it easier to start without precisely setting performance values in advance. :contentReference[oaicite:6]{index=6}

From a practical perspective, three points are especially valuable.

First, multiple nodes can access the same file system at the same time. Even as web servers scale up or down, they can refer to the same files, and EFS is also easy to use as shared storage in Kubernetes. Google Filestore and Azure Files provide similar value, but EFS is especially natural when working on AWS. :contentReference[oaicite:7]{index=7}

Second, it is easy to scale automatically. You can avoid operations where storage has to be expanded every time capacity runs short, and applications do not need to worry too much about how much they will use. Cost design is still necessary, of course, but it moves you far away from physical disk-style operations. :contentReference[oaicite:8]{index=8}

Third, you do not have to operate the shared file server itself. Avoiding the need to build your own NFS server, design HA, handle failover and rollback, monitor capacity, and apply patches is a major advantage. EFS greatly reduces this “file server maintenance burden.” :contentReference[oaicite:9]{index=9}

3. Throughput Modes and Performance Design

EFS provides Elastic, Provisioned, and Bursting throughput modes. AWS performance documentation explains that each mode is used differently: Elastic Throughput adjusts automatically according to demand, while Provisioned Throughput lets you reserve the throughput you need in advance. :contentReference[oaicite:10]{index=10}

In practice, the following way of thinking is easy to use.

Cases suited to Elastic Throughput

• Access patterns are hard to predict
• You are in the early build stage and are not confident in performance estimates
• You are a small team and want to reduce operational burden first

Cases suited to Provisioned Throughput

• High throughput is consistently required
• You want to specify performance requirements clearly
• You prioritize performance certainty over cost

Cases where Bursting Throughput matters

• You are inheriting older design assets or existing configurations
• You can operate while understanding burst behavior

AWS states that for most workloads, it recommends General Purpose and Elastic Throughput. That means for new builds, General Purpose + Elastic Throughput can be treated as the first candidate. :contentReference[oaicite:11]{index=11}

Quota information also shows default read throughput of 3 GiBps and write throughput of 1 GiBps for One Zone with Elastic / Provisioned, while limits may vary by region and configuration. In addition, the 2025 update history records that maximum Elastic Throughput read performance was raised to 60 GiBps in some regions and 20 GiBps in others. Performance limits can change relatively easily, so checking the latest quotas is important during design. :contentReference[oaicite:12]{index=12}

4. Comparison with GCP Filestore

Google Cloud Filestore is Google’s shared file storage service. The official overview explains that Filestore is persistent file storage that can be accessed simultaneously from multiple application instances, and that it can be used especially with GKE as a read-write-many shared volume. :contentReference[oaicite:13]{index=13}

Filestore is easy to understand through its service tiers. Google documentation lists tiers such as Basic HDD, Basic SSD, Zonal, Regional, and Enterprise, allowing you to choose performance and availability based on requirements. In particular, the Regional tier replicates data across multiple zones and can tolerate zone failures, which is close to the idea of EFS Regional. :contentReference[oaicite:14]{index=14}

A practical comparison looks like this:

• Amazon EFS: stronger emphasis on automatic scaling and ease of sharing
• Google Filestore: easier to explicitly choose performance and availability through tier selection

Filestore pricing can be expressed through combinations such as instance fees, GiB-hours, and IOPS, depending on the tier, on/off settings, and configuration. Compared with AWS EFS, which is closer to a model based on stored data plus throughput/access, Filestore retains a somewhat stronger “instance-like” feel. :contentReference[oaicite:15]{index=15}

In practical terms, AWS makes it easy to use EFS with the feeling of “placing a shared file system first,” while GCP makes it easy to use Filestore with the feeling of “choosing the required service tier and designing file storage accordingly.” :contentReference[oaicite:16]{index=16}

5. Comparison with Azure Files

Azure Files is Azure’s shared file storage service, supporting both SMB and NFS. Official documentation explains that Azure Files provides two standard protocols, SMB and NFS, and that a single file share cannot be used with both SMB and NFS at the same time, though separate shares using each protocol can be created within the same storage account. :contentReference[oaicite:17]{index=17}

Azure Files also puts redundancy choices relatively front and center. Japanese documentation organizes redundancy options such as LRS, ZRS, and GRS, making it easier to design according to availability and disaster recovery requirements. :contentReference[oaicite:18]{index=18}

On pricing, Azure Files has multiple billing models. Azure’s pricing pages and billing model explanations state that there are models such as pay-as-you-go and provisioned v2 for HDD, and that cost is determined by four factors: billing model, media tier, redundancy, and resource model. :contentReference[oaicite:19]{index=19}

A rough comparison between EFS and Azure Files is as follows:

• EFS: natural on AWS as an NFS-style shared file system
• Azure Files: supports both SMB and NFS, making it suitable for Windows-based and SMB-oriented workloads

If your workload is Linux-centered and you want AWS-native shared file storage, EFS is very straightforward. On the other hand, if SMB compatibility or affinity with Microsoft environments is important, Azure Files is highly understandable as a design choice. :contentReference[oaicite:20]{index=20}

6. How to Think About Pricing

Amazon EFS pricing documentation explains that billing elements include read/write access under Elastic Throughput, Provisioned Throughput, and read and tiering activity associated with moving data to Infrequent Access or Archive. In other words, EFS cost is affected not only by stored capacity, but also by access patterns and tiering strategy. :contentReference[oaicite:21]{index=21}

Common causes of rising costs in the field include:

• Putting everything in shared storage “just in case”
• Treating frequently accessed data and rarely accessed data the same way
• Using Regional even for workloads where One Zone is sufficient
• Overprovisioning throughput

For EFS cost design, it is useful to separate at least the following three categories:

1. Hot data used constantly
2. Data that is referenced occasionally but still needs to be shared
3. Data kept mostly for storage or archival purposes

Google Filestore also has time-based and capacity-based pricing by tier, while Azure Files costs vary by billing model and media tier. What all clouds have in common is that shared file storage can become expensive if you put everything there simply because it is convenient. The basic rule everywhere is to place only what truly needs sharing. :contentReference[oaicite:22]{index=22}

7. Workloads Especially Suited to EFS

Amazon EFS is especially suited to the following cases.

First, architectures where multiple EC2 instances, containers, or Kubernetes nodes read and write the same files. It works very naturally for shared application content, uploaded files, intermediate data for ML processing, and shared CI/CD workspaces. AWS also describes EFS as a file system designed for parallel access. :contentReference[oaicite:23]{index=23}

Second, it is suited to cases where you want to make NFS-based shared storage managed. Operating your own NFS server brings heavy responsibilities around redundancy, patching, disk expansion, and incident response, so EFS is a natural option when you want to reduce that burden.

Third, it is suited to cases where data volume grows, but you do not want to perform detailed capacity planning every time. EFS’s scalability is a key strength, so it is easy to handle in early-stage growth or environments with large access fluctuations. :contentReference[oaicite:24]{index=24}

On the other hand, for high-performance storage used by only a single instance, or workloads where ultra-low latency is the top priority, another type of storage may be more appropriate. The trick is to choose EFS for its value as a “shared file system.”

8. Common Mistakes and How to Avoid Them

8-1. Putting everything in EFS

If you gather data in EFS even when sharing is not required, both costs and responsibility boundaries expand. EFS is convenient, but the design becomes much cleaner when you limit it to “things that need sharing.”

8-2. Choosing Regional or One Zone vaguely

If availability requirements are strong, choose Regional. If a single AZ is acceptable, choose One Zone. It is important to decide this upfront. AWS itself generally recommends Regional. :contentReference[oaicite:25]{index=25}

8-3. Fixing throughput without performance testing

If you lock in Provisioned Throughput from the start, you may overprovision or fall short. It is safer to start with Elastic Throughput and observe actual trends. :contentReference[oaicite:26]{index=26}

8-4. Comparing it with Azure Files or Filestore as if they work the same way

Filestore strongly emphasizes tier selection, Azure Files emphasizes SMB/NFS and redundancy options, and EFS is especially natural as an automatically scaling shared NFS-style service. Even if they all sound like “shared file storage,” the comparison axes are quite different. :contentReference[oaicite:27]{index=27}

Summary

Amazon EFS is AWS’s fully managed shared file storage service. It allows multiple compute resources to access the same file system in parallel and can scale to petabyte scale according to demand. It supports Regional and One Zone file system types and provides Elastic / Provisioned / Bursting throughput modes, allowing flexible shared file storage design. :contentReference[oaicite:28]{index=28}

Google Cloud Filestore makes it easy to choose performance and availability by tier and is especially straightforward for shared storage use with GKE. Azure Files supports both SMB and NFS, offers rich redundancy and billing model choices, and works well with Microsoft environments. :contentReference[oaicite:29]{index=29}

A practical summary is:

• Use Amazon EFS when you want to naturally use a shared file system on AWS
• Use Filestore when you want to design shared storage on GKE or Google Cloud by selecting service tiers
• Use Azure Files when you value SMB/NFS flexibility and affinity with Microsoft environments

As a first step, even if you choose EFS, it is best not to move every file into the shared platform at once. Start by placing only the data that truly requires simultaneous access from multiple nodes into EFS. Then observe performance trends and cost behavior, and optimize One Zone / Regional choices and throughput modes as needed. That approach is much gentler operationally.