Design an optimal storage strategy for your cloud workload

Last reviewed 2024-03-14 UTC

This guide helps you assess the storage requirements of your cloud workload, understand the available storage options in Google Cloud, and design a storage strategy that provides optimal business value.

For a visual summary of the main design recommendations, see the decision tree diagram.

If you've read this document previously and need a summary of the changes, see the change log.

Overview of the design process

As a cloud architect, when you plan storage for a cloud workload, you need to first consider the functional characteristics of the workload, security constraints, resilience requirements, performance expectations, and cost goals. Next, you need to review the available storage services and features in Google Cloud. Then, based on your requirements and the available options, you select the storage services and features that you need.

The following diagram shows this 3-phase design process:

Phased approach to designing storage for cloud workloads.

Define your requirements

Use the questionnaires in this section to define the key storage requirements of the workload that you want to deploy in Google Cloud.

Guidelines for defining storage requirements

When answering the questionnaires, consider the following guidelines:

  • Define requirements granularly

    For example, if your application needs Network File System (NFS)-based file storage, identify the required NFS version.

  • Consider future requirements

    For example, your current deployment might serve users in countries within Asia, but you might plan to expand the business to other continents. In this case, consider any storage-related regulatory requirements of the new business territories.

  • Consider cloud-specific opportunities and requirements

    • Take advantage of cloud-specific opportunities.

      For example, to optimize the storage cost for data stored in Cloud Storage, you can control the storage duration by using data retention policies and lifecycle configurations.

    • Consider cloud-specific requirements.

      For example, the on-premises data might exist in a single data center, and you might need to replicate the migrated data across two Google Cloud locations for redundancy.


The questionnaires that follow are not exhaustive checklists for planning. Use them as a starting point to systematically analyze all the storage requirements of the workload that you want to deploy to Google Cloud.

Assess your workload's characteristics

  • What kind of data do you need to store?


    • Static website content
    • Backups and archives for disaster recovery
    • Audit logs for compliance
    • Large data objects that users download directly
    • Transactional data
    • Unstructured, and heterogeneous data

  • How much capacity do you need? Consider your current and future requirements.

  • Should capacity scale automatically with usage?

  • What are the access requirements? For example, should the data be accessible from outside Google Cloud?

  • What are the expected read-write patterns?


    • Frequent writes and reads
    • Frequent writes, but occasional reads
    • Occasional writes and reads
    • Occasional writes, but frequent reads

  • Does the workload need file-based access, using NFS for example?

  • Should multiple clients be able to read or write data simultaneously?

Identify security constraints

  • What are your data-encryption requirements? For example, do you need to use keys that you control?

  • Are there any data-residency requirements?

Define data-resilience requirements

  • Does your workload need low-latency caching or scratch space?
  • Do you need to replicate the data in the cloud for redundancy?
  • Do you need strict read-write consistency for replicated datasets?

Set performance expectations

  • What is the required I/O rate?

  • What levels of read and write throughput does your application need?

  • What environments do you need storage for? For a given workload, you might need high-performance storage for the production environment, but could choose a lower-performance option for the non-production environments.

Review the storage options

Google Cloud offers storage services for all the key storage formats: block, file, and object. Review and evaluate the features, design options, and relative advantages of the services available for each storage format.


Block storage

The data that you store in block storage is divided into chunks, each stored as a separate block with a unique address. Applications access data by referencing the appropriate block addresses. Block storage is optimized for high-IOPS workloads, such as transaction processing. It's similar to on-premises storage area network (SAN) and directly attached storage (DAS) systems.

The block storage options in Google Cloud are a part of the Compute Engine service.

Option Overview
Persistent Disk Dedicated hard-disk drives (HDD) and solid-state drives (SSD) for enterprise and database applications deployed to Compute Engine VMs and Google Kubernetes Engine (GKE) clusters.
Google Cloud Hyperdisk Fast and redundant network storage for Compute Engine VMs, with configurable performance and volumes that can be dynamically resized.
Local SSD Ephemeral, locally attached block storage for high-performance applications.

File storage

Data is organized and represented in a hierarchy of files that are stored in folders, similar to on-premises network-attached storage (NAS). File systems can be mounted on clients using protocols such as NFS and Server Message Block (SMB). Applications access data using the relevant filename and directory path.

Google Cloud provides a range of fully managed and third-party solutions for file storage.

Solution Overview
Google Cloud Filestore

NFSv3 file servers for Compute Engine VMs and Google Kubernetes Engine clusters.

You can choose a service tier (Basic, High Scale, or Enterprise) that suits your use case.

Google Cloud NetApp Volumes File-based storage using NFSv3, NFSv4.1, or SMB.
More options See Summary of file server options.

Object storage

Data is stored as objects in a flat hierarchy of buckets. Each object is assigned a globally unique ID. Objects can have system-assigned and user-defined metadata, to help you organize and manage the data. Applications access data by referencing the object IDs, using REST APIs or client libraries. Object storage is similar to on-premises SAN in terms of the ability to scale, but is easier to manage and less expensive.

Cloud Storage provides low-cost, highly durable, no-limit object storage for diverse data types. The data you store in Cloud Storage can be accessed from anywhere, within and outside Google Cloud. Optional redundancy across regions provides maximum reliability. You can select a storage class that suits your data-retention and access-frequency requirements.

Comparative analysis

The following table provides a comparative analysis of the key capabilities of the storage services in Google Cloud.

Persistent Disk Hyperdisk Local SSD Filestore Google Cloud NetApp Volumes Cloud Storage

10 GiB to 64 TiB per disk

257 TiB per VM

4 GiB to 64 TiB per disk

512 TiB per VM

375 GiB per disk

12 TiB per VM

1-100 TiB per Filestore instance (the minimum and maximum capacity and the scaling increments vary by service tier)

2-500 TiB per storage pool

100 GiB to 100 TiB per volume

No lower or upper limit
  • Scale up
  • Add and remove disks
  • Autoscale using managed instance groups
Scale performance and capacity dynamically Not scalable
  • Basic tier: scale up
  • Enterprise and Zonal tiers: scale up and down
Scale up and down Scales automatically based on usage
Limited sharing
  • Read-only: multiple VMs
  • Multi-writer: 2 VMs
Not shareable Not shareable Mountable on multiple Compute Engine VMs, remote clients, and GKE clusters Mountable on multiple Compute Engine VMs and GKE clusters
  • Read/write from anywhere
  • Integrates with Cloud CDN and third-party CDNs
Encryption keys
Google-managed, customer-managed, or customer-supplied keys Google-managed, customer-managed, or customer-supplied keys Google-managed keys
  • Google-managed keys (all service tiers)
  • Customer-managed keys (Enterprise and Zonal tiers)
Google-managed or customer-managed keys Google-managed, customer-managed, or customer-supplied keys
Lifetime of the disk Lifetime of the disk Ephemeral (data lives until the VM is stopped or deleted) Lifetime of the Filestore instance Lifetime of the volume Lifetime of the bucket
Zonal Zonal
  • Regional availability for Enterprise instances, zonal availability for Basic and Zonal instances
  • Snapshots for Enterprise and Zonal instances
  • Backups
Linearly scaling high performance, based on disk size and CPU count Dynamically scalable, high-performance persistent storage High-performance scratch storage

Scalable performance

Expectations depend on the service level

Autoscaling read-write rates, and dynamic load redistribution
Manually format and mount Manually format and mount Manually format, stripe, and mount Fully managed Fully managed Fully managed
  • IOPS-intensive or latency-sensitive applications
  • Databases
  • Shared read-only storage
  • Rapid, durable VM backups
  • Performance-intensive workloads
  • Scale-out analytics
  • Flash-optimized databases
  • Hot-caching for analytics
  • Scratch disk
  • Lift-and-shift on-premises file systems
  • Shared configuration files
  • Common tooling and utilities
  • Centralized logs
  • Lift-and-shift on-premises file systems
  • Shared configuration files
  • Common tooling and utilities
  • Centralized logs
  • Windows workloads
  • Streaming videos
  • Media asset libraries
  • High-throughput data lakes
  • Backups and archives
  • Long-tail content

Choose a storage option

There are two parts to selecting a storage option:

  • Deciding which storage services you need.
  • Choosing the required features and design options in a given service.

    Examples of service-specific features and design options

    Persistent Disk

    • Deployment region and zone
    • Regional replication
    • Disk type, size, and IOPS (for Extreme Persistent Disk)
    • Encryption keys: Google-managed, customer-managed, or customer-supplied
    • Snapshot schedule


    • Deployment zone
    • Disk type, size, and IOPS
    • Encryption keys: Google-managed, customer-managed, or customer-supplied
    • Snapshot schedule


    • Deployment region and zone
    • Instance tier
    • Capacity
    • IP range: auto-allocated or custom
    • Access control

    NetApp Volumes

    • Deployment region
    • Service level for the storage pool
    • Pool and volume capacity
    • Volume protocol
    • Volume export rules

    Cloud Storage

    • Location: multi-region, dual-region, single region
    • Storage class: Standard, Nearline, Coldline, Archive
    • Access control: uniform or fine-grained
    • Encryption keys: Google-managed, customer-managed, or customer-supplied
    • Retention policy

Storage recommendations

Use the following recommendations as a starting point to choose the storage services and features that meet your requirements. These recommendations are also presented as a decision tree later in this document.

  • For applications that need file-based access, choose a suitable file storage service based on your requirements for access protocol, availability, and performance.

    Access protocol Recommendation
    • If you need regional availability, use Filestore Enterprise.
    • If zonal availability is sufficient but you need high performance, use Filestore Zonal.
    • Otherwise, use either Filestore Basic or NetApp Volumes.

    For more information about the differences between the Filestore service tiers, see Service tiers.

    SMB or NFSv4.1 Use NetApp Volumes.

  • For workloads that need primary storage with high performance, use local SSDs, Persistent Disks, or Hyperdisks depending on your requirements.

    Requirement Recommendation
    Fast scratch disk or cache

    Use local SSD disks (ephemeral).

    Sequential IOPS Use Persistent Disks with the pd-standard disk type.
    IOPS-intensive workload Use Persistent Disks with the pd-extreme or pd-ssd disk type.
    Balance between performance and cost Use Persistent Disks with the pd-balanced disk type.
    Scalable performance and capacity dynamically

    Use Hyperdisk.

    Choose a suitable Hyperdisk type:

    • Hyperdisk Throughput is recommended for scale-out analytics, data drives for cost-sensitive apps, and for cold storage.
    • Hyperdisk Extreme is recommended for workloads that need high I/O, such as high-performance databases.

    • Depending on your redundancy requirements, choose between zonal and regional disks.
      Requirement Recommendation
      Redundancy within a single zone in a region Use zonal Persistent Disks or Hyperdisks.
      Redundancy across multiple zones within a region Use regional Persistent Disks.
      For a detailed comparative analysis, see Persistent Disk options.
  • For unlimited-scale and globally available storage, use Cloud Storage.

    Depending on the data-access frequency and the storage duration, choose a suitable Cloud Storage class.

    Requirement Recommendation>
    Access frequency varies, or the data-retention period is unknown or not predictable. Use the Autoclass feature to automatically transition objects in a bucket to appropriate storage classes based on each object's access pattern.
    Storage for data that's accessed frequently, including for high-throughput analytics, data lakes, websites, streaming videos, and mobile apps.

    Use the Standard storage class.

    To cache frequently accessed data and serve it from locations that are close to the clients, use Cloud CDN.

    Low-cost storage for infrequently accessed data that can be stored for at least 30 days (for example, backups and long-tail multimedia content). Use the Nearline storage class.
    Low-cost storage for infrequently accessed data that can be stored for at least 90 days (for example, disaster recovery). Use the Coldline storage class.
    Lowest-cost storage for infrequently accessed data that can be stored for at least 365 days, including regulatory archives. Use the Archive storage class.

    For a detailed comparative analysis, see Cloud Storage classes.

Data transfer options

After you choose appropriate Google Cloud storage services, to deploy and run workloads, you need to transfer your data to Google Cloud. The data that you need to transfer might exist on-premises or on other cloud platforms.

You can use the following methods to transfer data to Google Cloud:

  • Transfer data online by using Storage Transfer Service: Automate the transfer of large amounts of data between object and file storage systems, including Cloud Storage, Amazon S3, Azure storage services, and on-premises data sources.
  • Transfer data offline by using Transfer Appliance: Transfer and load large amounts of data offline to Google Cloud in situations where network connectivity and bandwidth are unavailable, limited, or expensive.
  • Upload data to Cloud Storage: Upload data online to Cloud Storage buckets by using the Google Cloud console, gcloud CLI, Cloud Storage APIs, or client libraries.

When you choose a data transfer method, consider factors like the data size, time constraints, bandwidth availability, cost goals, and security and compliance requirements. For more information about planning and implementing data transfers to Google Cloud, see Migrate to Google Cloud: Transfer your large datasets.

Storage options decision tree

The following decision tree diagram guides you through the Google Cloud storage recommendations discussed earlier:

View a larger image

Decision tree to select a storage strategy.

What's next

Change log

This section provides a summary of the significant technical changes in this guide.

Date Description of changes
March 14, 2024 Added the Data transfer options section.
December 8, 2023 Updated the capacity numbers for Hyperdisk and Local SSD.
October 17, 2023 Updated the storage recommendations and the decision tree diagram to include Google Cloud NetApp Volumes as an option for NFSv3 file storage.
August 25, 2023
  • Added guidance