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Understand What You're Paying For: How to Evaluate Software

Dirk Paessler

The technology landscape is littered with confusing terminology. Some of this comes from vendors chasing popular buzzwords, other times it's the fault of a 30,000-foot view approach to different categories.

The term "monitoring," for example, can mean any number of things, and while more specified terms like application performance monitoring, network performance monitoring, or infrastructure monitoring are supposed to narrow it down, there is often overlap and confusion into what is supposed to go where. This is common across many IT categories, especially once we involve major buzzwords like cloud or software-defined.

Compounding the confusion is the changing nature of software sales, maintenance and operation, with the addition of new delivery models, licensing models and service-level agreements. An IT administrator may have simple goals in mind, but they will have to navigate an increasingly complex world to accomplish them. With that in mind, here are several key areas to focus on when evaluating your next IT purchase.

Licensing

Purchasing software may seem like a simple task, but there are often unexpected hurdles, the first of which is licensing and payment models. The growth of the "as a service" model has displaced many traditional "pay upfront" models, but it's important to understand whether the software purchased is all-inclusive.

Many products on the market are made up of various components, for which numerous modules and add-ons are available. It is difficult to determine just what will actually be necessary in terms of additional software before you buy, and what's worse, there is often little clarity offered on behalf of the seller. Before you buy, be sure to understand exactly what is needed in a product feature set, and match that up with associated costs to do a true price evaluation.

Evaluation and Testing

In a perfect world, every software can be evaluated and tested with a full-featured trial version. That may not always be the case, and that needs to be considered when making any purchase. IT administrators need easy access to trials, technical papers, data sheets and other information, along with dedicated assistance from the vendor should they run into any problems during evaluation. That's a must, and if vendors don't offer it, that should stand out as a red flag.

During the evaluation phase, it's also important to take note of the implementation process. If there are numerous problems with installing and configuring a trial version of the software, it can almost be guaranteed that the full version will be even more difficult.

Implementation and Usability

Ideally, the evaluation phase is a good indicator of how successful implementation will be. Still, it's key to fully comprehend all the challenges that can come from a complete implementation, many of which can undermine the functionality of the product. In the network monitoring world, this is often where the delivery model of the software comes in, with SaaS models often having different outcomes than appliance models in terms of installation and configuration. Implementations that aren't lightweight and automatic create more opportunities for something to go wrong, and problems may not be immediately apparent.

Usability itself is difficult to vet, as one can't understand the full value of any software until they use it. Here, it's important to trust peer networks and dive into case studies and customer references. The media can play a valuable role here as well, including news outlets that still publish reviews.

Ultimately, software that goes unused is a massive loss in terms of both money and potential technical gains. Keeping these issues in mind can ensure a smooth and simple software acquisition process, one that will enable IT to be successful with the right tools at their side.

Dirk Paessler is CEO and Founder of Paessler AG.

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Understand What You're Paying For: How to Evaluate Software

Dirk Paessler

The technology landscape is littered with confusing terminology. Some of this comes from vendors chasing popular buzzwords, other times it's the fault of a 30,000-foot view approach to different categories.

The term "monitoring," for example, can mean any number of things, and while more specified terms like application performance monitoring, network performance monitoring, or infrastructure monitoring are supposed to narrow it down, there is often overlap and confusion into what is supposed to go where. This is common across many IT categories, especially once we involve major buzzwords like cloud or software-defined.

Compounding the confusion is the changing nature of software sales, maintenance and operation, with the addition of new delivery models, licensing models and service-level agreements. An IT administrator may have simple goals in mind, but they will have to navigate an increasingly complex world to accomplish them. With that in mind, here are several key areas to focus on when evaluating your next IT purchase.

Licensing

Purchasing software may seem like a simple task, but there are often unexpected hurdles, the first of which is licensing and payment models. The growth of the "as a service" model has displaced many traditional "pay upfront" models, but it's important to understand whether the software purchased is all-inclusive.

Many products on the market are made up of various components, for which numerous modules and add-ons are available. It is difficult to determine just what will actually be necessary in terms of additional software before you buy, and what's worse, there is often little clarity offered on behalf of the seller. Before you buy, be sure to understand exactly what is needed in a product feature set, and match that up with associated costs to do a true price evaluation.

Evaluation and Testing

In a perfect world, every software can be evaluated and tested with a full-featured trial version. That may not always be the case, and that needs to be considered when making any purchase. IT administrators need easy access to trials, technical papers, data sheets and other information, along with dedicated assistance from the vendor should they run into any problems during evaluation. That's a must, and if vendors don't offer it, that should stand out as a red flag.

During the evaluation phase, it's also important to take note of the implementation process. If there are numerous problems with installing and configuring a trial version of the software, it can almost be guaranteed that the full version will be even more difficult.

Implementation and Usability

Ideally, the evaluation phase is a good indicator of how successful implementation will be. Still, it's key to fully comprehend all the challenges that can come from a complete implementation, many of which can undermine the functionality of the product. In the network monitoring world, this is often where the delivery model of the software comes in, with SaaS models often having different outcomes than appliance models in terms of installation and configuration. Implementations that aren't lightweight and automatic create more opportunities for something to go wrong, and problems may not be immediately apparent.

Usability itself is difficult to vet, as one can't understand the full value of any software until they use it. Here, it's important to trust peer networks and dive into case studies and customer references. The media can play a valuable role here as well, including news outlets that still publish reviews.

Ultimately, software that goes unused is a massive loss in terms of both money and potential technical gains. Keeping these issues in mind can ensure a smooth and simple software acquisition process, one that will enable IT to be successful with the right tools at their side.

Dirk Paessler is CEO and Founder of Paessler AG.

The Latest

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...