The Cloud NAS race is on.
Network Attached Storage (NAS) refers to enterprise data storage that can be accessed from different devices over a network. NAS environments have gained prominence for file-based workloads because they provide a hierarchical structure of directories and folders, making it easier to organize and find files. Many enterprise applications today are file-based and use files stored in a NAS as their data repositories. This data can be everything from user-generated data to home directories and file shares, but increasingly file data comes from applications such as genomics, PACS imaging, media audio and video files, self-driving car data, IoT sensors and edge devices. File data can be seismic data, electronic design data, and IoT data. As a result, file data volumes are enormous. But, Gartner forecasts worldwide IT spending to grow by only 6.2% in 2021. Nevertheless, as I noted in my last post, at least 70% of enterprise data is cold data, sitting on expensive storage, consuming the same backup resources as hot data.
Now that CEOs are intimately involved in the cloud journey, core enterprise applications are moving to the cloud faster than ever – and these enterprise workloads are primarily file-based. Cloud data migration without rewriting the application means file-based workloads must be able to run in the cloud cost effectively and without user, application, and customer disruption.
Cloud NAS to the Rescue?
Cloud NAS refers to a cloud-based storage solution to store and manage files. Cloud NAS, or cloud file storage, is gaining prominence as many vendors have introduced cloud NAS offerings, including AWS, Azure, NetApp, and Qumulo. A few things to know:
- Cloud NAS storage is accessed via the Server Message Block (SMB) and Network File System (NFS) protocols. On-premises NAS environments are also accessed via SMB and NFS.
- Cloud NAS is often designed for high-performance file workloads. Its high-performance Flash tier can be very expensive.
- Many cloud NAS offerings offer less-expensive file tiers. Putting data in these lower tiers requires the right approach to hybrid and multi-cloud data management.
- When considering cloud NAS file tiering ensure you have visibility across storage silos and ensure data does not get locked into a proprietary solution that will disrupt your users. The need for cloud native data access and data mobility should not be underestimated. (Read the white paper Why Standards-Based File Tiering Matters.)
Is a Cloud Storage Gateway good for File Data Migration to a Cloud NAS?
Short answer? No. A cloud storage gateway is an on-premises appliance, typically hardware based, that provides a file gateway to data in the cloud. Since cloud storage gateways put data in the cloud in a proprietary format, they are not a good choice for file data migrations to a cloud NAS. Read more about the pros and cons of using cloud storage gateways for data migrations.
Compare Cloud Data Migration and Unstructured Data Management Options and Choices.
The Roadblocks of Cloud Data Migration for Files
The goal of a cloud data migration is to move large production data sets quickly, with data integrity intact, without errors, and without disruption to users. But, the path to the cloud for file data migrations is paved with unstructured data migration challenges. Here are some of the file data migration challenges we often see:
- Sunk Costs: Free tools are labor intensive. Tools like robocopy and rsync are error-prone, they do not handle failures well, and they require a lot of human effort and babysitting. There are some point data migration solutions and cloud storage gateways, but these do not typically scale. Cloud gateways hold the data in the cloud, ransom to a proprietary format, and do not put you on the right path to cloud data management.
- Data Integrity: There are always source and storage incompatibilities and challenges keeping access controls and metadata intact.
- Time Consuming: Whether it’s WAN latencies, a mix of small and large files, or the fact there are billions of files in a large data migration project, these can all result in a massive time commitment if not properly managed.
- Downtime Impact: This is always a big one – the impact on users and application access to data. The length of the cutover is also always a roadblock.
- Complex Cloud Storage Factors: There’s a lot to consider, including file vs. object data migration, performance vs. pricing, and the need to ensure you have the right option at the right time.
- Insufficient Planning: It’s shocking how often enterprise IT organizations are flying blind, trying to plan and manage file data migrations without data analytics and insight. This is why, at Komprise, we say Know First and Move Smart.
- Ad-Hoc Approach: No continuity, no learnings from each migration, no real program management, instead a one-and-done cloud data migration mindset. Sound familiar?
Closer Look: Komprise Elastic Data Migration for Unstructured Data
Why Cloud Data Migrations Fail
We put together a cloud unstructured data migration infographic to summarize the common cloud data migration roadblocks.
Avoiding Unstructured Data Migration Pitfalls
With an analytics-driven approach to cloud data migration and unstructured data management, you can avoid the common data migration challenges and:
- Know before you migrate – analytics drive the most cost-effective plans
- Preserve data integrity – maintain metadata, run MD5 checksums
- Save time and costs – multi-level parallelism provides elastic scaling
- Be worry-free – built for petabyte-scale that ensures reliability
- Migrate NFS 27X faster and Migrate SMB data 25X faster – forget slow, free tools that need babysitting
Learn more about Komprise Elastic Data Migration and read our white paper on accelerating NAS and cloud data migrations.
Cloud NAS Migration?
At Komprise, we working closely with our partners to ensure our customers have the best cloud NAS data migration experience, while ensuring data is delivered in native format for cloud native data access, which means no lock-in and maximum enterprise data storage savings. Here some examples: