Jeremy Martin | November 19, 2018

Top Trends in Cloud Data Storage

Over the last several years, the growth of data storage has been explosive. In 2018, average data center storage capacity was 1,450 exabytes. By 2021, that number is expected to climb to 2,300 exabytes.

Meanwhile, IT budgets have remained relatively constant, creating a delta between the storage capacity organizations desire and how much those businesses can invest in storage. 

To keep up with the costs of data growth, businesses have begun to invest differently in their storage systems. Rather than pay for disk space on premise, they’re opting for cloud storage from major providers such as Google Cloud, Amazon Web Services, and Microsoft Azure.

But just what is cloud computing exactly? How does data storage work? In this article, we’ll discuss these topics, along with the important trends you should know during your search for viable solutions.

 

 

Public, Private, VPC, & Hybrid 

Cloud storage can be divided into three types: public, private, and hybrid.

As the name implies, public cloud vendors offer their services to the general public. They maintain large data centers full of computing hardware, and their customers share access to that hardware.

In contrast, private cloud is an exclusive service, hosted either in an organization’s own data centers or the vendor’s, so as to address security concerns or compliance with regulations.

VPC is a special kind of cloud computing which lets you configure resources. If you were using AWS, for example, you would automatically get a VPC, a private sub-section of AWS that you control, in which you can place AWS resources (such as EC2 instances or RDS databases). Moreover, you would have full control over who has access to the AWS resources that you place inside your VPC. In this sense, VPCs partition compute environments from physical infrastructures, so you can run multiple operating systems and applications simultaneously on the same machine.

Hybrid blends both use cases. An organization with hybrid solutions, for example, may run web servers in its own private cloud then using a public cloud service for additional capacity during peak hours.

Whether you use public, private, or hybrid cloud services, odds are you store data in different ways. At a macro level, there are three storage types: block storage, object storage, and file storage.

 

 

Block, Object, and File Storage

Block storage is a type of data storage that stores data in volumes, or blocks, which act as individual hard disk drives (HDD). Blocks are used to store data, software, code, dependencies, configurations and other files. Each storage block has its own file system and stores different information types between partitions. Logical unit numbers (LUNs) separate blocks, allowing each HDD to add or resize files. Block storage is often used for enterprise-level storage area networks (SANs) and is controlled by one operating system (OS).

On the cloud, block storage manifests as products such as AWS Elastic Block Store, which provides a virtualized SAN with logical volume management provisioning via a web services interface. Using the APIs, you can write data into a block storage instance or pull information off of a block storage instance at will. 

More popular and flexible than block storage, object storage manages unstructured data such as music, images, video files, backup files, database dumps, log files, and large data sets like pharmaceutical or financial data. In this paradigm, each object is given a unique identifier, allowing it to exist across multiple storage devices and locations. The main benefit of Object Stores is scale, both in terms of number of objects and geographic distribution. A good example of block storage would be a service like AWS Glacier. 

File systems are different. Products like Google Drive and Dropbox store their data as a hierarchy of files and folders so the user may retrieve files in the same format. While block-level storage systems write and retrieve data to and from certain blocks, file-level storage requests data through user-level data representation interfaces. This client-server method of communication occurs when the client uses the data’s file name, directory location, URL and other information.

 

 

Load Balancing & Clustering

Load balancing refers to efficiently distributing network traffic across a group of backend servers. Spreading work evenly ensures that no single server bears too much demand and thus improves application responsiveness. It also increases availability of applications and websites for users. Modern applications cannot run without load balancers.

Clustered storage is the use of two or more storage servers working together to increase performance, capacity, or reliability. Clustering distributes work loads to each server, manages the transfer of workloads between servers, and provides access to all files from any server regardless of the physical location of the file.

Failover clusters are a load balancing method with multiple servers managing the workload. The advantage is that you can eliminate the threat of a single point of failure for a server, application or service. Normally, if a server with a particular application or service crashes, the application or service is unavailable until an administrator manually rectifies the problem. But if a clustered server crashes, another server within the cluster will automatically take over the failed server's application and service responsibilities without intervention from an administrator or impact on operations.

 

 

Pay-as-You-Go & Elastic Storage

Cloud providers also offer a pay-as-you-go model, reducing hardware and software costs once reserved for on-premise infrastructure — a far cry from self-hosted servers and networks that need constant maintenance, hardware upgrades, and updates. In addition to being more affordable, these solutions are also considerably more secure than their self-hosted counterparts.

Why is the pay-as-you-go model so revolutionary? Well when it comes to setting up storage systems on-premise, you would have to buy ahead of the demand. With cloud computing, however, you can use resources as needed. This elasticity saves you from burning capital and lets you meet demand by paying for more storage when you need it. When you want to warehouse data, storage can increase or decrease independently. 

In addition to cost, you also get the ability to expand and contract your business however you want. If you want to launch a new product, you can get more storage — and fast — since IT no longer needs to provision storage systems or manage a major project.

 

 

Understanding your Storage Requirements

As your business grows, so will the volume, variety, and velocity of the data you store. For this reason, you should select a storage provider that accommodates your needs, both in terms of affordability and type of storage.

If you’re using data for analysis, for example, you’ll want to centralize that data in a data warehouses so that all your teams can work off the same dataset.

But to centralize your data means having to maintain, store, organize, back up, and manage all different kinds of data, structured and unstructured. Hence, you want a solution that lets your capacity flex over time and frees you from having to plan the next several years of storage requirements. With cloud computing, you get both, paying only for the capacity you use and choosing the type of storage that meets your usage needs. 

Want to store your customer data on a cloud data warehouse, eliminate data prep, and accelerate your time to analytics? Try Fusion for free.

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