If you’re pricing out a cloud server, you’re probably comparing pricing on a certain number of virtual CPUs, or Central Processing Units, as well as RAM and storage, and perhaps network fees. If you were building a gaming PC, you’d be pricing out all of those items, but you’d also be saving a major chunk of money for a graphics card, or GPU. GPUs are naturally intended to handle the processing of digital graphics in visually intensive tasks like gaming or animation.
With the rise of big data analytics and machine learning, however, GPUs are playing an increasingly important part in high performance computing. Cloud providers have started getting in on the game, enabling GPU-accelerated cloud servers with an eye on big data processing and other intensive applications.
Private vs. public cloud is a battle many thought was over years ago, and some recent think pieces seem to confirm that notion, claiming no one can match the economies of scale delivered by hyperscale cloud providers.
But private cloud, or on-premise virtualization, can still be a less expensive option — if you have the staff and capabilities to support it. A recent study from 451 Research describes when the tipping point is in the favor of private cloud and when public cloud has a lower total cost of ownership (TCO), based on utilization of hardware and efficiency of your staff.
Cloud infrastructure is all about providing the right amount of resources for your applications at any given moment. Overprovisioning might be wise for performance-oriented apps, but generally “right-sizing” is the best way to maximize your budget, especially as most IT departments face efficiency and cost struggles.
By being proactive about managing your virtual machine resources and halting underutilized or “zombie” VMs, you can free up those resources either to be decommissioned or reassigned to other uses.
You’ll want to adjust VM size to reclaim overprovisioned VMs, clean up idle or turned-off VMs, and resize VMs that are stretching their current resources beyond acceptable performance. Here’s how to practice active capacity management.
Containers are on the rise, with VMware integrating them into the vSphere platform. What started seemingly as a competitor to virtual machines has proved to be just another tool in the virtualization box available to administrators beyond software testing and development, as enterprises and mid-market companies of all sizes begin to implement containers alongside (and inside) their VMs.
Once you read a bit about the benefits of containerization, you may be curious about trying some out in your environment. But before you start spinning up containers left and right, make sure you’re using the right tool for the job. Containers certainly have their advantages, but there are many applications where a virtual machine will be more effective. Here’s how to decide.
Your business probably has faster internet than your home. If you’re with an enterprise, you almost certainly have some quality broadband. Plugging into the cloud can be a relatively painless process, albeit one that requires careful planning, but without considering your network design and connection speeds, even a simple cloud migration can become time-consuming, expensive, and difficult to manage.
