Top 3 reasons to automate your virtual machines’ start-stop schedules

A large portion of cloud-based workloads depend on the performance and availability of virtual machines. Responsible, efficient VM management isn’t just important for keeping infrastructures up and running at peak performance; it’s also the key to cost effectiveness.

Why automate virtual machine scheduling?

Many companies use runbooks and scripts to schedule their VMs, but these manual methods are error-prone, time-consuming, and generally inefficient. They also don’t scale, as usage patterns and maintenance needs are unique to each machine.

Automating virtual machine on-off schedules isn’t an industry standard practice yet, but its benefits compared to manual scheduling make it a valuable strategy for better VM administration. In this article, we’ll take a look at the top three reasons to switch from manual scripting to an automated virtual machine scheduling solution:

  • Optimize VM uptime and downtime
  • Save money on cloud costs
  • Free up time for your IT team

1. Optimize virtual machine availability and downtime

For business operations to run smoothly on a day-to-day basis, it’s crucial that virtual machines be available at the right times. Automated starting and stopping of VMs allows immediate availability when resources are needed in an environment. When activity ceases, the machine gets shut down.

Optimal uptime and downtime management can be ensured thanks to the automatic analysis of usage pattern and the real-time analysis of the activity on the virtual machine, to propose a custom start / stop schedule and avoid unexpected shutdowns.

Constantly optimizing your virtual machines’ schedules is a smart cloud management tactic that will also have a noticeable impact on your overall costs.

2. Save money on cloud costs

Cloud computing services are billed on a pay-as-you-go basis, meaning you only pay for the resources you actually use. Controlling resource consumption is therefore essential for managing costs.

For virtual machine scheduling, the best practice is to have virtual machines turned on only when there is a need for resources.

With typical virtual machine costs ranging from a few hundred to several thousand dollars a month, automating shutdown schedules can lead to significant savings on your cloud spend.

Even if your main KPI for VM performance is total money spent, it’s also important to factor in the time your teams spend writing, testing, integrating and adapting scripts and schedules.

3. Free up time for your IT team

For virtual machine scheduling, manual operations are time-consuming for teams and error-prone. The higher the number of virtual machines means multiplied actions in terms of maintenance and optimization.

Manually scheduling virtual machines is a process that’s both labor-intensive and error-prone. The more VMs you have, the more time-consuming it becomes to maintain and optimize their usage.

A schedule on one virtual machine is not necessarily applicable on another because its usage pattern may be different. In terms of maintenance, the problem is also recurrent. On huge volumes of VMs, it can be difficult to manage all of these parameters.

A schedule that works for one virtual machine can’t be reused for a different one unless they have the exact same usage patterns. The same applies to maintenance requirements. When you have a large number of VMs to manage, it can be hard to account for all of these varying parameters.

Our experience with VM automation

Here at GSoft, we can attest to this: our organization uses a bunch of virtual machines to accomplish various tasks, and we eventually crossed the scalability threshold in terms of schedule administration and maintenance. Despite having much more pressing matters to attend to, our IT team was stuck spending valuable time on tedious manual scheduling. Our resource requirements outgrew our existing model, and we needed to find something better.

Automating VM schedules seemed like the most logical solution for our scenario: letting a machine take care of the grunt work meant more time for our teams to focus on the important stuff. We developed an algorithm to monitor our virtual machines’ usage patterns and generate custom schedules that immediately adapt to changes in use. Automation negates the need to integrate a script every time a new virtual machine is added: a few minutes of learning is all it takes to create and apply a schedule that’s tailored to future use.

The easiest way to automate your VM schedules

There are a few ways you can go about implementing automated scheduling for your virtual machines. Several existing third-party solutions offer a better user experience than PowerShell and the Azure Portal, but most are only able to produce static schedules. This makes integration faster and more fluid, but it doesn’t quite solve the core problem: static schedules don’t scale, so they require just as much maintenance as manually generated ones.

Our new tool, Snoozit, approaches the problem in a completely different way. It uses machine learning to analyze virtual machines’ historic usage patterns and predict when the next period of activity will occur. It monitors VM activity in real time and shuts down inactive machines until the AI determines it’s time to turn them back on. The result: virtual machines are always available when they’re needed. And in the end, that’s all that matters.

This also means that there are no schedules to configure. Simply activate the Autopilot feature on one or more virtual machines, and let Snoozit automatically start and stop them as needed. Set it and forget it, letting Snoozit make sure that you're better performing on your VM administration and saving as much as possible on your cloud costs.

We're quite happy with the solution and we invite you to try it now for free to see for yourself. Leverage the power of artificial intelligence to get all of the value with non-manual work to set it up. We're always looking for feedback so be sure to let us know what you think and if it's been as useful for you that it has been for us.