Cloud teams are busy. In fact, Virtana’s recently published State of Hybrid Cloud and FinOps survey found that 44% of respondents have deployed more than half of their workloads in a public cloud, and 88% have deployed more than one-quarter of their workloads in a public cloud. That’s a lot of migration, optimization, and management on the cloud team’s plate; and it’s not just for right now but for the foreseeable future. We wanted to know what specific pressures they are dealing with, so we asked them to rate—on a scale of 1 (low) to 5 (high)—the impact of a variety of issues on their teams. It turns out that the vast majority are facing all of these challenges, ranking them a 4 or 5:
- The shift to remote working: 82%
- Rapidly changing business needs: 81%
- Surges in cloud utilization and costs: 81%
- Increased demand for public cloud services: 78%
- Increased performance issues: 77%
While there is some overlap across these challenges—for example, the shift to remote working could be driving some of the utilization surges leading to certain performance challenges—these are distinct issues that create unsustainable pressure and must be addressed sooner rather than later. Let’s take a look at each one in turn.
The shift to remote working
It’s amazing how quickly digital transformation can happen when it’s literally a matter of keeping the lights on in a business. That’s exactly what happened in the early days of the pandemic when work-from-home became universal pretty much overnight. Thanks to the cloud, this was far less disruptive than it might have been in the past. Not that it was easy—some organizations had to scramble. For example, call centers with an on-premises phone system had to quickly pivot to a cloud-based one to avoid leaving their customers in the lurch. Healthcare practitioners that hadn’t yet dipped their toes in the telemedicine waters were forced to dive in headfirst. Slow performance of back-office applications when accessed remotely, which was tolerated when it was an infrequent need, suddenly had to be addressed to match in-office speeds. The examples go on and on.
The degree and rate of change that cloud teams were managing intensified, and if they didn’t have a good handle on their workloads to begin with—their dependencies, characteristics, and performance—the increased velocity of digital transformation happening all at once made it impossible. Now that we’re on the other side of the pandemic and people start heading back into the office, hybrid approaches will continue to be important, but some of the early pivots that had to happen fast—and may have required difficult trade-offs in the process—may need to be revisited and adjusted for the long term. Some companies might even consider whether to pull certain workloads back on premises.
The solution here is precision observability that provides clear visibility into what’s happening across a hybrid infrastructure, delivered via AIOps, machine learning, and data-driven analytics to help organizations keep up with the vast scope and the accelerated rate of change.
Rapidly changing business needs
The pandemic was not, of course, the only driver for adaptability. Agility has been a watchword for years and the desire to increase organizational responsiveness is one of the main reasons that enterprises adopted cloud computing in the first place. The pace of change—be it from new technology, disruptive competitors, customer expectations, or most likely a combination of all the above—is relentless. Technology is now at the core of just about everything a business does, including revenue-generating products and services, customer service and support, sales and marketing, operations, and back-office functions. This elevates the strategic importance of IT, which in turn intensifies the pressure on that team to meet ambitious business goals under dynamic conditions.
AIOps- and ML-enabled precision observability is key here, too, empowering the organization to adapt quickly to changing conditions and minimize the potential for mistakes that can have a harmful impact on the business. For example, this new found agility means performance degradation that impedes the customer experience or wasted spend that eats into funds available for other strategic investments can become things of the past. Additionally, because of the strategic nature of the applications and workloads, IT must be able to collaborate with non-technical leaders. This means the cloud team needs dashboards and reporting that enable them to understand their cloud investment from a business perspective with visibility into trends and usage by individual cost centers.
Surges in cloud utilization and costs
The revenue numbers from the two dominant cloud service providers (CSPs) are evidence of utilization and cost upticks. AWS’ year-over-year revenue grew 32% in Q1 2021, accelerating from 28% in Q4 2020, and Azure reported a 50% year-over-year increase in the March quarter (source). Certainly, the shift to remote working has been a major factor over the past year. For cloud teams within an enterprise, increased utilization and the associated costs happen for a variety of reasons and may even be positive signs, if for example it was the result of growing customer demand.
While the conditions driving the higher utilization may be out of IT’s control, it is the cloud team’s responsibility to manage the impact of surges on performance, cost, and organizational risk. This requires the ability to quickly identify meaningful changes, get automated rightsizing recommendations, and adjust accordingly so workloads remain optimized. They also need to be able to perform what-if analyses to tune sizing based on the organization’s specific risk tolerances.
Increased demand for public cloud services
CSPs are under the same pressure to innovate as any other business, which means an ever-increasing array of offerings. There are cloud business process services, cloud application infrastructure services, cloud application services, cloud management and security services, cloud system infrastructure services, desktop-as-a-service, and others. As more and more facets of the business are migrated to the public cloud, the cloud team must navigate the options to select the optimal workload configuration.
With thousands of options, and new ones emerging all the time, teams need to be able to quickly adjust to changes in CSP offerings as they evolve. But this is a complex and confusing effort, and one that simply can’t be performed manually. Effective cloud resource planning requires automated recommendations and real-time data collection and analytics to identify optimal configurations, as well as the ability to conduct what-if analyses in varied scenarios.
Increased performance issues
Everything changes over time—usage shifts, workloads drift, conditions evolve—and application performance can degrade as a result. Just like there’s no one-size-fits all approach to rightsizing your cloud configurations when you migrate your workload, there’s no single answer to how to keep those workloads performing optimally over time. Your tolerance for performance variation will depend on the application itself. If it requires extremely high transaction speeds, for example a stock trade transaction, even the smallest slowdown can have a big impact on results. If a backup process that runs in the middle of the night takes an hour longer to complete, however, you probably won’t even notice the difference.
To keep performance at appropriate levels over time, the first thing you need is a way to find out about impending issues before they have a deleterious effect. In other words, user complaints should not be the means of notification you rely on—you need real-time data collection and analytics. Further, your alerting mechanism should allow you to set different thresholds for applications based on your tolerance, such as a very narrow band for a transactional application but a wide one for a backup. Once you know performance is becoming, or will become, a problem, you need to make the appropriate adjustments. Here, too, automated recommendations will help you identify new optimal configuration options, and what-if analysis in varied scenarios enables you to evaluate those options and make the best selection for your needs.
Get a better night’s sleep with Virtana Optimize
Change is inevitable—it’s one of the reasons why companies move to hybrid cloud in the first place—but if it’s not properly managed, it will create headaches for your cloud team. With Virtana Optimize, you can take control of your hybrid cloud infrastructure. By optimizing your capacity and cost in real time on an ongoing basis, you can stay rightsized, even as conditions and options change. Request a free trial today!
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Jon Cyr
VP of Product Management, Virtana
