How to use a Data Fabric to Power Your Cloud Workloads

More workloads are moving to the cloud every day, and those workloads require data. As mentioned in previous blogs, a data fabric is one way to ensure that all of your data is available everywhere you need it. It ensures seamless data movement between clouds and between the cloud and the data center. Some of the use cases for this technology apply to “cloud only” workloads, and are the subject of this blog.

Certain types of workloads simply lend themselves to the public cloud. One of those is data analytics. It requires large amounts of computer power to “crunch” large segments of data culled from a variety of sources. Analytics projects may also run in short bursts requiring large amounts of compute resources that then go relatively unused in between projects. This need for elastic infrastructure is what makes the cloud such a perfect environment for such projects.

This affinity between the public cloud and data analytics is one of the reasons that NoSQL databases like Cassandra and MongoDB are built around the idea of using many smaller servers rather than a smaller number of large servers. Yes, one could argue this is simply following the scale out wave that allows companies to leverage off-the-shelf, commodity hardware. But it’s also true these distributed architectures are perfect for the cloud, as it enables fast and easy deployment of any application, at any scale.

But NoSQL databases aren’t the only applications that can benefit from in-cloud deployment. Traditional, relational databases (RDBMSs) can also leverage the elastically scalable compute and storage resources available in cloud environments. These RDMBSs can support a variety of workloads ranging from analytics to order processing.

While on-premises RDBMS deployments typically require stressful CapEx-centric infrastructure forecasting, cloud-based deployments allow for less rigid, OpEx-centric, pay-as-you go consumption models. This can dramatically reduce IT forecasting anxiety and eliminate the need for costly over-provisioned database infrastructure, while simultaneously delivering a near-infinite pool of resources to critical RDBMS applications.

To fully exploit the possibilities of both NoSQL and traditional databases, a file-based data fabric is required. Only a file-based data fabric can seamlessly support both modern and legacy applications, while also delivering the requisite data shareability and scalability.

One of the most common ways to efficiently use cloud computing infrastructure is to have data that is always in-cloud, but leverage in-cloud compute only when it’s needed. You can define the compute nodes required for a data analytics project and then leave those nodes powered off until the project goes live. Those compute nodes would point to the in-cloud data fabric where your source data is located. The data fabric will make sure all of the files stored by your data sources are accessible to your compute nodes as soon as you power them on. Turn them on, perform your analytics, and turn them off again. If you need to update your data, you can do so while the compute is offline, making changes directly within the file-based data fabric. When the data updates are complete, the compute nodes can then be turned on again for additional analysis, with no need to alter the mapping between compute and data location. From a cloud cost and operational efficiency perspective, it doesn’t get any better than that.

StorageSwiss Take

Some workloads were designed for the cloud. Some weren’t. With a file-based data fabric you can seamlessly support both and leverage the power and economics of the cloud across a wide range of applications.

Sponsored by Elastifile

About Elastifile

Elastifile is redefining the way data is stored and managed, enabling seamless deployment of private and hybrid cloud solutions. With enterprises and service providers increasingly seeking to support both on-premises and cloud workflows, Elastifile delivers a cross-cloud data fabric that unifies the data across these environments within the single global namespace of a global file/object system. The easy-to-manage, easy-to-deploy, elastic, scale-out architecture intelligently shares the resources across all environments, providing the optimal solution for enterprise data and related application services. For more information visit

W. Curtis Preston (aka Mr. Backup) is an expert in backup & recovery systems; a space he has been working in since 1993. He has written three books on the subject, Backup & Recovery, Using SANs and NAS, and Unix Backup & Recovery. Mr. Preston is a writer and has spoken at hundreds of seminars and conferences around the world. Preston’s mission is to arm today’s IT managers with truly unbiased information about today’s storage industry and its products.

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