Multi-Cloud Strategy and How to Implement It | Parallels RAS
Last updated on December 1, 2021
A multi-cloud strategy is a process where an organization uses multiple cloud services for its computing needs. Generally, companies that have different requirements for varied data sets adopt this model. For example, if Amazon Web Services (AWS) works well for big data analytics projects or if Microsoft Azure is the ideal solution for transactional workloads, companies must choose a cloud vendor that works best for their specific use-case. Similarly, if you want to implement an enhanced security layer for your IT infrastructure, adopt a private cloud model. There is no single solution that addresses all companies.
If an organization utilizes cloud services from various locations, it might be hard to find a public cloud provider that works across all regions. An organization might use a premium cloud service for their high-value data while using comparatively cheaper cloud infrastructure to maintain admin-related details, allowing a company to limit the IT infrastructure cost. Another significant advantage of this model is the granular pricing model. Pay-as-you-go pricing ensures that instead of paying a fixed price, your fee is determined by actual service usage.
There is also a large number of companies that adopt this model for data autonomy. As laws and policies mandate, particular data types reside in a specific location, this model ensures that companies do not break such laws. The flexibility to decide where specific data resides enables companies to optimize performance and reduce latency by placing the computing resources as close to the end-users as possible.
Is There a Downside to a Multi-Cloud Strategy?
Although companies adopt a multi-cloud strategy for enhanced performance, security, compliance, and resource availability, this model is not perfect. To deploy a multi-cloud solution, the IT team needs to have thorough knowledge about the possible cloud vendors and the pricing models of the market, making it a possibly costly and lengthy process. Also, application management can become a concern as data moves from one cloud provider to another.
You can’t deploy a multi-cloud model in an instant. Before doing so, the organization must check the necessary Service Level Agreements (SLAs) and Terms and Conditions (T&Cs) thoroughly with the cloud vendors to ensure that data privacy and security are always maintained.
Use Parallels RAS to Implement a Multi-Cloud Solution
While adopting a multi-cloud strategy, organizations usually utilize a mix of public cloud vendors, such as AWS, Azure, and Google. However, creating such a pipeline across multiple vendors is a cumbersome process. You can overcome such challenges by embracing Parallels Remote Application Server (RAS): A unified virtual desktop and application delivery solution that supports multi-cloud deployments.
Parallels RAS is a virtualization solution that delivers Windows applications, desktops, and data to any device and platform, such as Windows, Mac, Android, iOS, Chromebooks, and more. One significant advantage of Parallels RAS is that it supports all deployment models, such as on-premises, public, and hybrid, enabling organizations to utilize all types of clouds.
In addition, Parallels RAS supports various security features, such as multi-factor authentication, client policies, granular filtering, and RBAC (Role-Based Access Control). Therefore, any risk of a data breach is significantly lower, and IT admins have full control over the company’s VDI applications from a single view, from anywhere.
Implementing a multi-cloud model by using Parallels RAS mitigates the concerns of deploying a multi-cloud model by removing the operational complexity.
