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Evaluating Commercial vs. Open Source APM

Chris Bloom

Choosing an application performance monitoring (APM) solution can be a daunting task. A quick Google search will show popular products, but there's also a long list of less-well-known open source products available, too. So how do you choose the right solution?

The advantages and disadvantages of open source software versus commercial software are part of an age-old debate. Which is better or worse? Which is more or less buggy? Which is faster or slower? And what about documentation and support, and a million other possible differences? The truth is that they have very little to do with whether the software is open source or not.

Cost and Support

Characteristics like support and cost are of course very important, and can vary greatly between the two. The cost of open source may be something you pay to ramp up on the learning curve, and to tweak the software yourself, or pay somebody else to do it for you.

Support of open source can be very good, if the solution becomes popular within the community. On the other hand, a commercial product may have very polished, organized documentation and well-established support. In other words, aside from the quality of the product itself, a big part of the decision to go with open source or not is your preference on when to invest money in the product and how to get support. With open source, you have a lot of flexibility about when and what you spend your money on.
 
With many open source projects there are the completely free options, usually posted on Github as source. There are also commercial components and support provided for a fee from a company supporting the project. This can make getting started reasonably inexpensive if the open source project's functionality satisfies your requirements. As your requirements change and grow, you can develop new functionality yourself, buy components from others, or just wait until somebody else does the work.

One of the biggest benefits of open source from a cost perspective is that once you have something that works for you, you don't have to keep paying for it annually, like you would for a commercial product. On the other hand, paying for a commercial product gives you a well-defined set of features and characteristics that you can count on, and somebody to call and complain to otherwise.

APM Performance: Speed and Scalability

 
Performance is another good example of a software characteristic that cannot be determined by open source or commercial availability. Performance for APM software is defined by speed and scalability, mostly on the back-end. Sure, the front-end UI must be fast, but the real question and challenge for this type of software is how much analysis it can do on network traffic or flow data.

For smaller networks, let's say 100Mbps or less, this is not much of an issue. But when you start to get above that, the overwhelming volume of packets and flows that must be processed every second exceeds the limits of a single thread. This is where you need to consider whether the solution is multi-threaded or not.

And for networks with speeds in the 10Gbps arena and up, even multi-threaded software on a single server is not going to be enough. In this case, the solution needs to scale by distributing the load across several servers, and aggregating the results into a single pane of glass. In my own experience, I have found open source solutions to be more scalable than commercial products, or at least accessible to more people, mainly because of the invention of open source technologies like Hadoop, and the growing number of open source projects that use them.

Commercial Open Source Hybrids

This brings up an important point, though, because commercial products can use open source components as well. These kinds of commercial products are hybrids, and the fact that you can plug open source components into them says something about the architecture and APIs of the product, which is an important point to consider.

As an example, I like to use the open source ELK stack on my company's appliances, allowing disk space to be shared between packets and events. With ELK, which includes the Elasticsearch, Logstash and Kibana components, an appliance can be used to capture and analyze packets while doing double duty as a SIEM for any security events that are generated as a result of analyzing those packets. Similar set-ups in the APM domain are also very plausible.

The Front End

Now let's turn to the front-end. Ideally, the UI is easy to use. This is where commercial products often come out ahead, while the UI for open source projects might not be as polished.

More importantly, the UI has to perform well and be responsive. Nobody wants to wait 10 minutes for their daily dashboard to populate with charts, or 30 minutes to generate a report on last week's performance. This is a tough one to test as well, because it takes time to collect network data for a week, or a month. So no matter which APM software you are evaluating, test it long enough that you're able to analyze long-term reporting performance before making a choice.
 
These are all tough questions and important considerations to keep in mind when choosing an APM solution. While open source is certainly not free of cost, it is also not necessarily more expensive, and commercial software is not necessarily better. Many other characteristics like cost, support, and performance have to be considered in order to make a well-informed decision.

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Evaluating Commercial vs. Open Source APM

Chris Bloom

Choosing an application performance monitoring (APM) solution can be a daunting task. A quick Google search will show popular products, but there's also a long list of less-well-known open source products available, too. So how do you choose the right solution?

The advantages and disadvantages of open source software versus commercial software are part of an age-old debate. Which is better or worse? Which is more or less buggy? Which is faster or slower? And what about documentation and support, and a million other possible differences? The truth is that they have very little to do with whether the software is open source or not.

Cost and Support

Characteristics like support and cost are of course very important, and can vary greatly between the two. The cost of open source may be something you pay to ramp up on the learning curve, and to tweak the software yourself, or pay somebody else to do it for you.

Support of open source can be very good, if the solution becomes popular within the community. On the other hand, a commercial product may have very polished, organized documentation and well-established support. In other words, aside from the quality of the product itself, a big part of the decision to go with open source or not is your preference on when to invest money in the product and how to get support. With open source, you have a lot of flexibility about when and what you spend your money on.
 
With many open source projects there are the completely free options, usually posted on Github as source. There are also commercial components and support provided for a fee from a company supporting the project. This can make getting started reasonably inexpensive if the open source project's functionality satisfies your requirements. As your requirements change and grow, you can develop new functionality yourself, buy components from others, or just wait until somebody else does the work.

One of the biggest benefits of open source from a cost perspective is that once you have something that works for you, you don't have to keep paying for it annually, like you would for a commercial product. On the other hand, paying for a commercial product gives you a well-defined set of features and characteristics that you can count on, and somebody to call and complain to otherwise.

APM Performance: Speed and Scalability

 
Performance is another good example of a software characteristic that cannot be determined by open source or commercial availability. Performance for APM software is defined by speed and scalability, mostly on the back-end. Sure, the front-end UI must be fast, but the real question and challenge for this type of software is how much analysis it can do on network traffic or flow data.

For smaller networks, let's say 100Mbps or less, this is not much of an issue. But when you start to get above that, the overwhelming volume of packets and flows that must be processed every second exceeds the limits of a single thread. This is where you need to consider whether the solution is multi-threaded or not.

And for networks with speeds in the 10Gbps arena and up, even multi-threaded software on a single server is not going to be enough. In this case, the solution needs to scale by distributing the load across several servers, and aggregating the results into a single pane of glass. In my own experience, I have found open source solutions to be more scalable than commercial products, or at least accessible to more people, mainly because of the invention of open source technologies like Hadoop, and the growing number of open source projects that use them.

Commercial Open Source Hybrids

This brings up an important point, though, because commercial products can use open source components as well. These kinds of commercial products are hybrids, and the fact that you can plug open source components into them says something about the architecture and APIs of the product, which is an important point to consider.

As an example, I like to use the open source ELK stack on my company's appliances, allowing disk space to be shared between packets and events. With ELK, which includes the Elasticsearch, Logstash and Kibana components, an appliance can be used to capture and analyze packets while doing double duty as a SIEM for any security events that are generated as a result of analyzing those packets. Similar set-ups in the APM domain are also very plausible.

The Front End

Now let's turn to the front-end. Ideally, the UI is easy to use. This is where commercial products often come out ahead, while the UI for open source projects might not be as polished.

More importantly, the UI has to perform well and be responsive. Nobody wants to wait 10 minutes for their daily dashboard to populate with charts, or 30 minutes to generate a report on last week's performance. This is a tough one to test as well, because it takes time to collect network data for a week, or a month. So no matter which APM software you are evaluating, test it long enough that you're able to analyze long-term reporting performance before making a choice.
 
These are all tough questions and important considerations to keep in mind when choosing an APM solution. While open source is certainly not free of cost, it is also not necessarily more expensive, and commercial software is not necessarily better. Many other characteristics like cost, support, and performance have to be considered in order to make a well-informed decision.

Hot Topics

The Latest

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...

Despite the frustrations, every engineer we spoke with ultimately affirmed the value and power of OpenTelemetry. The "sucks" moments are often the flip side of its greatest strengths ... Part 2 of this blog covers the powerful advantages and breakthroughs — the "OTel Rocks" moments ...

OpenTelemetry (OTel) arrived with a grand promise: a unified, vendor-neutral standard for observability data (traces, metrics, logs) that would free engineers from vendor lock-in and provide deeper insights into complex systems ... No powerful technology comes without its challenges, and OpenTelemetry is no exception. The engineers we spoke with were frank about the friction points they've encountered ...

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The power of Kubernetes lies in its ability to orchestrate containerized applications with unparalleled efficiency. Yet, this power comes at a cost: the dynamic, distributed, and ephemeral nature of its architecture creates a monitoring challenge akin to tracking a constantly shifting, interconnected network of fleeting entities ... Due to the dynamic and complex nature of Kubernetes, monitoring poses a substantial challenge for DevOps and platform engineers. Here are the primary obstacles ...

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