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What is a Cloud Data Server?

A cloud data server provides computer processing and data storage capacity in a virtual environment. Unlike a local or on-premises server, which can only be accessed through a closed network, a cloud data server is accessed via the Internet. A cloud data server is also called a virtual server.

The physical infrastructure associated with the cloud data server is typically managed by a third-party cloud service provider such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure. The cloud service provider maintains the cloud data center that supports the cloud data server. This includes hardware, temperature control, and routine maintenance. In this way, companies do not have the added complexity of operating and maintaining a physical server and can instead focus on growing their business.

You typically gain access to a cloud data server via the Internet. There are varying levels of access to the cloud data server, namely, IaaS, PaaS and SaaS. With all three cloud service models, you do not own or manage any of the hardware components that support the cloud data server. How much of the software and applications you own and manage depends on the type of service you select as described below.

With IaaS – Infrastructure as a Service – you own and manage only the software components of the cloud infrastructure. With PaaS – Platform as a Service – you own and manage the applications that run on the software components, but not the software itself. With SaaS – Software as a Service – you access the application via the internet and do not own or manage the application itself, any software or hardware components.

Cloud Data Server FAQs

What is the difference between an on-premises server and a cloud data server?

In the past, companies typically provided computing resources to their employees and end users via a local server. This local server is also known as an on-premises server and can only be accessed via a closed network. With the advance of cloud computing, companies have harnessed the power of the cloud to meet their evolving computing needs. A cloud data server provides the same computing power and storage capacity as an on-premises server, but without the headache of owning, operating, and maintaining physical components and support systems. Unlike an on-premises server, a cloud data server can be accessed with ease over the Internet.

What are the types of cloud data servers?

You can access the cloud data server depending on the cloud deployment model of your choice: public cloud, private cloud, hybrid cloud and multi cloud.

The public cloud is the most cost-effective option for many smaller businesses and startups. A public cloud is inherently shared by design so there are some performance issues and security concerns. To overcome this, a private cloud may be a more attractive option where you have access to a dedicated cloud data server that is not shared. A private cloud can provide a high performance and highly secure option for migrating to the cloud. However, this single-tenant option with the private cloud is very expensive.

To overcome these issues and still gain the most from cloud computing, organizations have turned to a hybrid cloud or multi cloud strategy to gain the best of both worlds. With the hybrid cloud, you can mix the private cloud and public cloud. For example, you can save your most data-intensive workloads and sensitive data storage for the private cloud and use the public cloud for development work and testing. With the multi cloud, you can spread your cloud computing needs across multiple public cloud service platforms, lowering your risk in the event of an interruption in cloud services.

What are the benefits of a cloud data server?

A cloud data server allows you to forego the upfront capital expense of building an onsite data center to support your server and computing needs. Instead, you can access all the computing resources and storage capacity that you need via the Internet with a cloud data server.

With an on-premises server, you are limited to the computing and storage capacity of your physical infrastructure. With a cloud data server, you get scalability unheard of with an on-premises server. Need to ramp up for seasonal customer and user upticks in traffic? You can quickly spin up as many cloud data servers as you need to handle that surge. Need to rapidly downsize once the season is over? You simply release the cloud data servers you no longer need. On the cloud, you only pay for what you need.

You gain reliability with a cloud data server. All your data will not be lost if your on-premises data center was to sustain weather-related damage, power loss or disruption to other support systems. With a cloud data server, you can rest easy that the cloud infrastructure for your applications and data are being expertly managed.

What are the cons of a cloud data server?

Although using a cloud data server is typically a huge cost savings for companies, your cloud bill can quickly spiral out of control if you don’t manage your cloud resources well. On the cloud, every byte of data counts, including each backup that you make onto your cloud data server.

Silk optimizes your cloud data server experience

Silk helps you to effectively manage your cloud data server across a public, hybrid or multi cloud environment. Silk is a virtualized layer that sits between your data and the cloud data center and helps keep your cloud resources to a minimum. This translates to a lower cloud bill.

Silk also offers up to 10x faster performance compared to native public cloud alone. This makes it ideal for companies who are looking to migrate data-intensive and mission-critical workloads to the cloud – making the public cloud a viable option without the hefty cost of private cloud.

Silk offers a range of enterprise data services including zero-footprint snapshots, deduplication, and thin provisioning. This reduces the amount of cloud resources that you need to a minimum. In turn, this helps to minimize your cloud services bill since you no longer need to worry about too many snapshots ballooning through your allocated resources.