Skip to main content

Manage the Performance of Virtual Environments Using Dynamic Alerts

Karthik Ramachandran

As we know, virtual environments consist of many moving pieces and are generally complex to setup. Typically, IT environments, depending on the size of the organization, can have several hundred VMs down to a handful of VMs. For such virtual infrastructure deployments, it helps to monitor the performance of VM and VM usage. It's also equally important to ensure the health of your virtual appliances are always in check and to immediately know when something goes wrong.

What you really don't want is to have alerts paging you 24/7, especially when they're not critical situations. Alert management can be a subtle, but dangerous activity. Additionally, manually setting alert thresholds can be an extremely time consuming task. Alternatively, using static thresholds that don't reflect real performance problems often result in alert storms, where administrators stop watching alerts carefully. This is where the "dangerous" part comes in and often true critical alerts can be lost in the noise and missed. As a result, intelligent, dynamic alerting can be critical for both staff efficiency and system reliability.

False Alerts: Reasons Why You Get Them and How to Avoid Them

Here are a few examples why your virtual environment may trigger alerts more frequently than normal:

■ Events that frequently occur, such as resource consumption can trigger alerts more often than most other virtual components.

■ You can get "spam" alerts from VMs or hosts that are no longer in use or that have been discharged.

■ Not properly tuning threshold levels can lead to a sudden spike in alerts.

Having intelligent alerting processes help ensure irrelevant alerts are not generated. This gives virtual admins time to look at "real" alerts and fix them. Here's what you can do to avoid alerting errors:

■ Set up alerts for specific VMs that you think are really going to impact your users or your business.

■ Leverage dynamic thresholds based on historical baseline trends whenever possible to set more realistic thresholds for your clusters, hosts, VMs, and datastore.

■ Establish well-defined threshold settings—this way you can optimize the kind of alerts you receive during the day and ensure that you're not bothered after work hours.

■ Set the right dependencies to significantly lower the amount of alerts you receive.

■ Forward specific alerts to the defined teams, since they understand the severity of the alert and can fix it right away.

Determine What to Monitor and Why

Most admins have to monitor hundreds of virtual appliances, which means you're probably dealing with plenty of alerts. Under these circumstances you'll have to determine a few things:

■ Go over each host to see if all VMs under the host must be monitored or if only a few critical VMs need to be monitored for alerts.

■ Talk to your business groups or users and understand what the impact will be. This will give you a sense of how many VMs and datastores have to be setup for alerts. They may have mission critical applications running inside them, which may affect business performance.

Statistical Thresholds: A Better Way to Set Baseline Values for your Virtual Environment

Normally, you would have to monitor the performance of hosts, VMs, and datastores for several weeks in order to know what the ideal or optimum baseline is to set warning and critical thresholds. However, integrated virtualization management tools can automatically calculate performance of clusters, hosts, VMs, and datastores and determine the baseline values.

IStatistical thresholds allow you to look at the following processes:

■ Applying thresholds to clusters, hosts, VMs, and datastores.

■ Understanding baseline statistics using standard deviation calculation for day and night system performance.

■ Gaining statistical insights into performance metrics and how they vary over time. Look at how stats are collected for higher and lower threshold values for individual VMs and hosts.

■ Calculating thresholds from historical performance data saves time in adjusting thresholds and provides more intelligent alerts.

■ Setting the right threshold values using the built-in baseline calculator. This calculates and applies the recommended threshold values for warning and critical stages for clusters, hosts, VMs, and datastores.

While this won't completely eliminate "spam" alerts, it will quickly let you get to a much smaller set for the administrator to deal with. In turn, it will let them spend more time and attention on striking that balance between monitoring your VM usage and hypervisor performance, and setting the right threshold values.

Karthik Ramachandran is Product Marketing Specialist at SolarWinds.

Hot Topics

The Latest

Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026. Part 2 covers data and data platforms ...

Manage the Performance of Virtual Environments Using Dynamic Alerts

Karthik Ramachandran

As we know, virtual environments consist of many moving pieces and are generally complex to setup. Typically, IT environments, depending on the size of the organization, can have several hundred VMs down to a handful of VMs. For such virtual infrastructure deployments, it helps to monitor the performance of VM and VM usage. It's also equally important to ensure the health of your virtual appliances are always in check and to immediately know when something goes wrong.

What you really don't want is to have alerts paging you 24/7, especially when they're not critical situations. Alert management can be a subtle, but dangerous activity. Additionally, manually setting alert thresholds can be an extremely time consuming task. Alternatively, using static thresholds that don't reflect real performance problems often result in alert storms, where administrators stop watching alerts carefully. This is where the "dangerous" part comes in and often true critical alerts can be lost in the noise and missed. As a result, intelligent, dynamic alerting can be critical for both staff efficiency and system reliability.

False Alerts: Reasons Why You Get Them and How to Avoid Them

Here are a few examples why your virtual environment may trigger alerts more frequently than normal:

■ Events that frequently occur, such as resource consumption can trigger alerts more often than most other virtual components.

■ You can get "spam" alerts from VMs or hosts that are no longer in use or that have been discharged.

■ Not properly tuning threshold levels can lead to a sudden spike in alerts.

Having intelligent alerting processes help ensure irrelevant alerts are not generated. This gives virtual admins time to look at "real" alerts and fix them. Here's what you can do to avoid alerting errors:

■ Set up alerts for specific VMs that you think are really going to impact your users or your business.

■ Leverage dynamic thresholds based on historical baseline trends whenever possible to set more realistic thresholds for your clusters, hosts, VMs, and datastore.

■ Establish well-defined threshold settings—this way you can optimize the kind of alerts you receive during the day and ensure that you're not bothered after work hours.

■ Set the right dependencies to significantly lower the amount of alerts you receive.

■ Forward specific alerts to the defined teams, since they understand the severity of the alert and can fix it right away.

Determine What to Monitor and Why

Most admins have to monitor hundreds of virtual appliances, which means you're probably dealing with plenty of alerts. Under these circumstances you'll have to determine a few things:

■ Go over each host to see if all VMs under the host must be monitored or if only a few critical VMs need to be monitored for alerts.

■ Talk to your business groups or users and understand what the impact will be. This will give you a sense of how many VMs and datastores have to be setup for alerts. They may have mission critical applications running inside them, which may affect business performance.

Statistical Thresholds: A Better Way to Set Baseline Values for your Virtual Environment

Normally, you would have to monitor the performance of hosts, VMs, and datastores for several weeks in order to know what the ideal or optimum baseline is to set warning and critical thresholds. However, integrated virtualization management tools can automatically calculate performance of clusters, hosts, VMs, and datastores and determine the baseline values.

IStatistical thresholds allow you to look at the following processes:

■ Applying thresholds to clusters, hosts, VMs, and datastores.

■ Understanding baseline statistics using standard deviation calculation for day and night system performance.

■ Gaining statistical insights into performance metrics and how they vary over time. Look at how stats are collected for higher and lower threshold values for individual VMs and hosts.

■ Calculating thresholds from historical performance data saves time in adjusting thresholds and provides more intelligent alerts.

■ Setting the right threshold values using the built-in baseline calculator. This calculates and applies the recommended threshold values for warning and critical stages for clusters, hosts, VMs, and datastores.

While this won't completely eliminate "spam" alerts, it will quickly let you get to a much smaller set for the administrator to deal with. In turn, it will let them spend more time and attention on striking that balance between monitoring your VM usage and hypervisor performance, and setting the right threshold values.

Karthik Ramachandran is Product Marketing Specialist at SolarWinds.

Hot Topics

The Latest

Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026. Part 2 covers data and data platforms ...