Virtual Machines (VMs) came into existence in the late 60s and 70s. But over the past few decades or more it has become a force to reckoned with.
While VMs and Virtualization have enabled organizations to optimally utilize its software and hardware resources and drive various commercial and other benefits.
It also led to the evolution of Cloud Computing, which has drastically changed the face of IT in the form of various cloud-based services. Today’s IT is hard to imagine without virtualization and cloud as it continues to play a vital role in the democratization of technology or IT at large.
However, this doesn’t mean that VMs’ journey has sort of reached its final destination. VMs today are also empowering a new set of cognitive technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) and its further development and applications.
In this interview, Al Sene, VP – Engineering, DigitalOcean talks to TechHerald.in about the significance of VMs, its role play in cloud computing, and the overall impact of VMs on modern IT in terms of enterprise and consumer technology. He also discusses how VMs continue to enable new cognitive technologies like AI, ML, and DL, and much more.
Q1. Virtual Machines (VMs) have been around for more than a few decades now. However, in today’s time cloud has become the de-facto when it comes to all sorts of software and IT services. So what’s your take on the status of VMs in today’s cloud-driven software & technology ecosystem in terms of role, needs, and benefits?
Al Sene: The Virtual Machine or virtualization of physical resources, has enabled the cloud by allowing physical resources to be split and shared, among multiple tenants in a secure manner. The rise of cloud-based applications has led to stronger investment in virtualized environments and technologies, especially around resource optimization and security.
Providing VMs via cloud significantly reduces operational and capital costs for customers while also providing flexibility for through features such as pay-per-use and scaling based on needs. Investments in virtualized technologies will only continue as the cloud market grows both from private companies and open source communities.
Q2. As we are in 2020, how much the VMs as a technology/software piece has evolved amid the fast-moving and evolving range of technologies both in the enterprise and consumer tech space?
Al Sene: The driving principle of a shared, secure, and scalable infrastructure is what drives the cloud, and VMs are the foundation for such environments. We have seen investments in security, density, and portability. Technologies like containers and microservices also play a key role in this story but at the foundation of virtualized environments is the VM.
Q3. What’s the key trend that you observe that is redefining the significance of VMs in the present times or going ahead into the future?
Al Sene: There are several key trends we are seeing. First and foremost, security — ensuring a large-scaled multi-tenant environment is secure and that customers are isolated from each other (both from data compromisation as well as resource sharing, ie reducing noisy neighbor impacts) is a must.
Second, density and physical resource utilization – ensuring that physical resources are being fully utilized, in a cost-effective manner to meet the performance requirements of customers workloads and application.
Q4. Lastly, cognitive technology like AI, ML, and DL has rapidly entered the enterprise technology space in the form of algorithms, bots, RPA, etc. So how is this new trend impacting the status quo of VMs and its existence?
Al Sene: VMs are foundational for AI, ML, and DL technologies and allow for more flexibility in provisioning, utilizing and deploying onto the underlying hardware. This is a major driving force in the democratization of AI/ML as virtualized environments are now available in the cloud in a pay-per-use model and lowering the entry costs.
VMs are also continuing to become lighter in weight, more secure, highly scalable allowing for secure virtualized environments that enable large-scaled workloads and applications such as AI/ML/DL. The continued abstraction of the infrastructure lifts significant burdens from developers, allowing them to focus further up the stack and on their applications.