5 Capabilities of Systems Management Software

The Factors to Consider When Evaluating Systems Management Software Vendors

The following are 5 factors to consider when evaluating systems management software vendors:

1. Dynamic and Complex Applications

Applications are becoming dynamic and complicated. Can your monitoring and performance software handle them? Historically, it has been fairly easy to monitor applications. Today, applications are increasingly componentized and are being abstracted from the underlying hardware platforms with the prevalence of virtualization technologies such as VMware, Hyper-V, AIX LPARs, and Solaris zones. It is now incumbent on systems management vendors to understand these virtualization technologies in great detail and how they impact application monitoring and performance. Systems management and application monitoring tools should make application monitoring easier, not more complicated.

Systems management tools should understand both application performance and availability as well as application transaction monitoring, to give a true end-user point of view. Together, these give a clearer picture of application and service delivery. However, your software must go deeper and provide the ability to monitor all the bits and pieces of infrastructure that play a role in the application delivery. This includes deep metrics on hardware, multiple platforms, physical infrastructure, and even dynamic environments.

2. Heterogeneous and Changing Environments

Heterogeneous platforms (Virtual, Physical and even Cloud) are the new normal. Most mid-enterprise IT departments are dealing with hardware platforms of many vintages and architectures. Virtualization and cloud computing add further complexity to the mix. When evaluating systems management software, companies must ensure they are capable of monitoring heterogeneous platforms and ever-changing environments.

The key is to have everything in your “Single Pane of Glass” IT Dashboard. This includes all your physical, virtual, and even cloud applications and infrastructure. For example, ensure your systems management software deeply monitors all your in-house physical systems (including IBM POWER, Solaris SPARC, and x86) all the way down to the resource level. The same dashboard must give access to your virtual environment as well, including deep metrics on VM guests to optimize performance and help identify instance contention. Lastly, your tool must be able to monitor cloud application and platforms from within the cloud and link that data back into your “Single Pane of Glass” IT dashboard.

3. Future Proofing

Are you future proofing? What about new technologies? Virtualization was and continues to be a big disruptor in technology, yet it took vendors years to understand how to effectively monitor virtual environments. With the advent of cloud and its adoption, a very similar problem is occurring again.

As technologies change, make sure your systems management tool is ready to grow with you. Safeguard your company by choosing a vendor that is progressive and is diversity-friendly. There will always be diversity in IT environments and platforms, so pick a vendor that thrives across many different IT environments. Don’t get stuck with software that only monitors and manages one platform.

4. Fast Deployment

Can you quickly evaluate and deploy? Time to deploy is critical for every IT manager. Companies want the ability to evaluate software and deploy at their own pace without having to rely on a full-time administrator to install and support the new software. Is the solution you’re evaluating going to save time and costs associated with deploying new software?

5. Try Before You Buy

Trial, trial and trial – before you talk to salespeople. Don’t get caught being sold through fancy demos, vapor-ware, and PowerPoint’s. Trial the tool. See what it does and how it acts in the environment. If the trial is complicated, frustrating, and doesn’t do what you want, don’t expect the purchased tool to be any better. Make sure the systems management tool is the right fit for your environment, and fully trial the software before getting too far in the buying process.

Try before you buy. You won’t buy a car without a test drive, so get behind the wheel and take the software for a rip around the track!

About Alex Bewley

Alex Bewley, CTO of uptime software, co-founded the company in 2000 and has been instrumental in the development of their up.time software product. Bewley is a computer scientist with a B.Sc.H in Computer Science from Queen’s University.

Related Links:

www.uptimesoftware.com

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5 Capabilities of Systems Management Software

The Factors to Consider When Evaluating Systems Management Software Vendors

The following are 5 factors to consider when evaluating systems management software vendors:

1. Dynamic and Complex Applications

Applications are becoming dynamic and complicated. Can your monitoring and performance software handle them? Historically, it has been fairly easy to monitor applications. Today, applications are increasingly componentized and are being abstracted from the underlying hardware platforms with the prevalence of virtualization technologies such as VMware, Hyper-V, AIX LPARs, and Solaris zones. It is now incumbent on systems management vendors to understand these virtualization technologies in great detail and how they impact application monitoring and performance. Systems management and application monitoring tools should make application monitoring easier, not more complicated.

Systems management tools should understand both application performance and availability as well as application transaction monitoring, to give a true end-user point of view. Together, these give a clearer picture of application and service delivery. However, your software must go deeper and provide the ability to monitor all the bits and pieces of infrastructure that play a role in the application delivery. This includes deep metrics on hardware, multiple platforms, physical infrastructure, and even dynamic environments.

2. Heterogeneous and Changing Environments

Heterogeneous platforms (Virtual, Physical and even Cloud) are the new normal. Most mid-enterprise IT departments are dealing with hardware platforms of many vintages and architectures. Virtualization and cloud computing add further complexity to the mix. When evaluating systems management software, companies must ensure they are capable of monitoring heterogeneous platforms and ever-changing environments.

The key is to have everything in your “Single Pane of Glass” IT Dashboard. This includes all your physical, virtual, and even cloud applications and infrastructure. For example, ensure your systems management software deeply monitors all your in-house physical systems (including IBM POWER, Solaris SPARC, and x86) all the way down to the resource level. The same dashboard must give access to your virtual environment as well, including deep metrics on VM guests to optimize performance and help identify instance contention. Lastly, your tool must be able to monitor cloud application and platforms from within the cloud and link that data back into your “Single Pane of Glass” IT dashboard.

3. Future Proofing

Are you future proofing? What about new technologies? Virtualization was and continues to be a big disruptor in technology, yet it took vendors years to understand how to effectively monitor virtual environments. With the advent of cloud and its adoption, a very similar problem is occurring again.

As technologies change, make sure your systems management tool is ready to grow with you. Safeguard your company by choosing a vendor that is progressive and is diversity-friendly. There will always be diversity in IT environments and platforms, so pick a vendor that thrives across many different IT environments. Don’t get stuck with software that only monitors and manages one platform.

4. Fast Deployment

Can you quickly evaluate and deploy? Time to deploy is critical for every IT manager. Companies want the ability to evaluate software and deploy at their own pace without having to rely on a full-time administrator to install and support the new software. Is the solution you’re evaluating going to save time and costs associated with deploying new software?

5. Try Before You Buy

Trial, trial and trial – before you talk to salespeople. Don’t get caught being sold through fancy demos, vapor-ware, and PowerPoint’s. Trial the tool. See what it does and how it acts in the environment. If the trial is complicated, frustrating, and doesn’t do what you want, don’t expect the purchased tool to be any better. Make sure the systems management tool is the right fit for your environment, and fully trial the software before getting too far in the buying process.

Try before you buy. You won’t buy a car without a test drive, so get behind the wheel and take the software for a rip around the track!

About Alex Bewley

Alex Bewley, CTO of uptime software, co-founded the company in 2000 and has been instrumental in the development of their up.time software product. Bewley is a computer scientist with a B.Sc.H in Computer Science from Queen’s University.

Related Links:

www.uptimesoftware.com

Hot Topics

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

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The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

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The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

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AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.