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Optimizing Applications in VMware Still Problematic, Time-Consuming and Inaccurate

Jerry Melnick

While VMware presents many opportunities for organizations of all sizes, it is not without its own challenges. As more companies begin to adopt this technology, IT pros are tasked to protect and ensure the efficiency of their business-critical applications that live in these virtual environments. A recent survey conducted by SIOS Technology aimed to understand the challenges IT teams of small and medium enterprises. The results of the survey showed that IT teams are struggling to optimize VMware infrastructures, experiencing issues around managing multiple tools and resolving issues quickly and with accuracy.

IT Teams Use Multiple Tools to Identify Problems in VMware Environments

Of the 518 IT pros surveyed, 78 percent indicated they are using multiple tools — including application monitoring, reporting, and infrastructure analytics solutions — to identify the root cause of application performance issues in VMware. This method of uncovering issues in silos isn't sustainable for IT pros who are under pressure to quickly identify and resolve issues. Whether it's a small team that has to bounce between multiple IT-related tasks in a day, or a larger team that has to come together to communicate and understand issues, having to review metrics from multiple tools is proving to be ineffective. To increase efficiencies in managing virtual environments, IT teams should seek solutions that provide a holistic view of their virtual environment.

Guesswork Involved in Resolving Application Performance Issues

The results of the survey indicated that uncovering the root cause of performance issues remains a mystery to IT teams. Of those surveyed, only 20 percent of IT pros stated that they believe their strategy to resolve application performance issues in VMware are 100 percent accurate. Furthermore, 7 percent of respondents would categorize the strategies used to identify and resolve issues as an "educated guess." Across the board, it's rare for IT teams to have confidence around their approaches to resolving application performance issues in virtual infrastructures.

IT Teams Waste Time and Resources When Solving Application Performance Issues

Ensuring that virtual environments are optimized is taking a toll on IT team time and resources. Although respondents stated they are using multiple tools, it seems they are not effective in empowering IT teams to resolve issues fast. More than half of the IT pros surveyed stated that they face application performance issues every month, and 44 percent indicated that it can take three hours or more to solve these problems. These issues cause significant interruptions, which is especially problematic for smaller IT teams who are being pulled in many directions. For larger IT groups, having to pull in multiple disciplines to come to a resolution ends up draining time.

How to Overcome These Challenges

The survey results reveal that when it comes to leveraging VMware for business critical applications, there are many obstacles for IT teams in ensuring these systems are running effectively. Modern IT analytics solutions that use machine learning to provide accurate recommendations can drastically reduce the time and effort that companies are spending on delivering critical application services, by focusing on knowledge discovery versus reporting metrics.

Jerry Melnick is President and CEO of SIOS Technology.

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Optimizing Applications in VMware Still Problematic, Time-Consuming and Inaccurate

Jerry Melnick

While VMware presents many opportunities for organizations of all sizes, it is not without its own challenges. As more companies begin to adopt this technology, IT pros are tasked to protect and ensure the efficiency of their business-critical applications that live in these virtual environments. A recent survey conducted by SIOS Technology aimed to understand the challenges IT teams of small and medium enterprises. The results of the survey showed that IT teams are struggling to optimize VMware infrastructures, experiencing issues around managing multiple tools and resolving issues quickly and with accuracy.

IT Teams Use Multiple Tools to Identify Problems in VMware Environments

Of the 518 IT pros surveyed, 78 percent indicated they are using multiple tools — including application monitoring, reporting, and infrastructure analytics solutions — to identify the root cause of application performance issues in VMware. This method of uncovering issues in silos isn't sustainable for IT pros who are under pressure to quickly identify and resolve issues. Whether it's a small team that has to bounce between multiple IT-related tasks in a day, or a larger team that has to come together to communicate and understand issues, having to review metrics from multiple tools is proving to be ineffective. To increase efficiencies in managing virtual environments, IT teams should seek solutions that provide a holistic view of their virtual environment.

Guesswork Involved in Resolving Application Performance Issues

The results of the survey indicated that uncovering the root cause of performance issues remains a mystery to IT teams. Of those surveyed, only 20 percent of IT pros stated that they believe their strategy to resolve application performance issues in VMware are 100 percent accurate. Furthermore, 7 percent of respondents would categorize the strategies used to identify and resolve issues as an "educated guess." Across the board, it's rare for IT teams to have confidence around their approaches to resolving application performance issues in virtual infrastructures.

IT Teams Waste Time and Resources When Solving Application Performance Issues

Ensuring that virtual environments are optimized is taking a toll on IT team time and resources. Although respondents stated they are using multiple tools, it seems they are not effective in empowering IT teams to resolve issues fast. More than half of the IT pros surveyed stated that they face application performance issues every month, and 44 percent indicated that it can take three hours or more to solve these problems. These issues cause significant interruptions, which is especially problematic for smaller IT teams who are being pulled in many directions. For larger IT groups, having to pull in multiple disciplines to come to a resolution ends up draining time.

How to Overcome These Challenges

The survey results reveal that when it comes to leveraging VMware for business critical applications, there are many obstacles for IT teams in ensuring these systems are running effectively. Modern IT analytics solutions that use machine learning to provide accurate recommendations can drastically reduce the time and effort that companies are spending on delivering critical application services, by focusing on knowledge discovery versus reporting metrics.

Jerry Melnick is President and CEO of SIOS Technology.

Hot Topics

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...