Skip to main content

The Top 5 Advantages of SaaS-based APM

Software-as-a-Service (SaaS) has received a lot of success and adoption in the past five years, unfortunately less in application performance management (APM) than other markets. With Cloud computing gaining momentum you're likely to see SaaS APM adoption increase significantly as more applications are deployed to the Cloud.

Here's the top 5 advantages that SaaS-based APM can offer:

1. Time-To-Value

SaaS-based APM can be deployed within your organization in the time it takes you to read this article. Think about that for a second - you get to experience the full benefits of APM in just a few minutes with no interaction from sales people or technical consultants. All you need to do is sign up for an account, take a free trial and evaluate whether APM can meet your needs or solve your problems.

Many cloud providers are now actively partnering with APM vendors to embed agents within the servers they provision for customer applications. I personally know of a company that solved a 6 month production issue within an hour of deploying SaaS-based APM. How about that for ROI and time to value!

2. Cost – licenses, maintenance, administration, hardware

Simply put, subscription-based licenses are cheaper, more flexible and less risk than owning perpetual licenses. Annual maintenance is included in the subscription, as is the cost of managing and supporting the APM infrastructure required to monitor your applications. You don't need to buy hardware to run your APM management server, you also don't need to pay someone to manage it either – you simply deploy your agents and you're all done. There's now no need to sign up to a multi-million dollar 3 year APM ELA agreement with a vendor, you can pay as you go. If the APM software rocks you renew your subscription, if the APM software sucks you go elsewhere.

3. Ease of Use

When a customer signs up for a SaaS account and evaluates APM for the first time, there is no pre-sales or technical consultant sitting next to them to configure or demo the solution. The experience from account registration to application monitoring is a journey taken alone by the customer.

First impressions are everything with SaaS, the learning curve of APM in this context must therefore be faster and easier so the APM solution can sell itself to the customer.

SaaS-based APM solutions are also much younger than traditional on-premise software, meaning the technology, UI design principles, and concepts applied are more superior and interactive for the user. Try comparing the UI of an iPhone with a Nokia phone from 5 years ago and you'll see my point.

First generation APM solutions were typically written for developers by developers. Today the value of APM touches many different user skill sets. It is therefore no surprise that SaaS-based APM can appeal to and be adopted by development, operations and business users.

4. Migrating to the latest Release

When an APM vendor announces a new release of its software with lots of cool features, its normally down to the customers themselves to migrate to the new release. If things go well, they might spend several days or perhaps a few weeks performing the migration. If things go badly they might end up spending several weeks working hand in hand with the vendor to complete the migration.

With SaaS-based APM, the vendors themselves are responsible for the migration. Customers simply login and they get the latest version and features automatically. They get to harness APM innovation as soon as its ready, rather than having to wait weeks or months to find the time to migrate by themselves. If anything goes wrong then the vendor spends the time and money to fix it rather than the customer.

Customers today will typically upgrade their APM software once a year because of the time and effort. With SaaS-based APM, they can receive multiple upgrades and always be on the latest version.

5. Scalability

Enterprises and Cloud providers can manage lots of applications, which can span several thousand servers. It is one thing for a customer to deploy APM across two applications and a hundred servers in their organization. It is another thing to deploy it across fifty applications and a thousand servers.

Scaling APM has never been easy. The more agents you deploy, the more management servers you need to collect, process and manage the data. How quickly can you purchase, provision and maintain the APM management infrastructure when you've got hundreds of applications you want to monitor?

With SaaS-based APM, you let the vendor take care of that for you. I know of a SaaS-based APM user that monitors over 6,000 servers in their organization. Compare that with the largest APM on-premise deployment you know of and you can see why SaaS-based APM is a better scalability option.

So there you have it, five compelling reasons why you should consider SaaS-based APM in your organization. SaaS-based APM isn't for everyone though. I typically see less adoption in financial services customers where data privacy and security controls are much tighter.

ABOUT Stephen Burton

Stephen Burton is Tech Evangelist at AppDynamics, and is also the alter ego of increasingly popular "App Man" character. Steve is responsible for promoting best practice application performance management (APM) for distributed applications running in cloud, virtual and physical environments. Before joining AppDynamics, Steve held senior product management positions at OpTier and Precise, leading innovation and creative solutions to help customers better manage the performance of their applications. Steve has previously worked in pre-sales and also spent many years as a senior developer and application support engineer when his career began at Sapient.

Related Links:

www.appdynamics.com

12 Ways to Gain Faster ROI from APM

Stephen Burton's blog: Will Your Web Applications Suffer the Tweet of Death?

Hot Topics

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

The Top 5 Advantages of SaaS-based APM

Software-as-a-Service (SaaS) has received a lot of success and adoption in the past five years, unfortunately less in application performance management (APM) than other markets. With Cloud computing gaining momentum you're likely to see SaaS APM adoption increase significantly as more applications are deployed to the Cloud.

Here's the top 5 advantages that SaaS-based APM can offer:

1. Time-To-Value

SaaS-based APM can be deployed within your organization in the time it takes you to read this article. Think about that for a second - you get to experience the full benefits of APM in just a few minutes with no interaction from sales people or technical consultants. All you need to do is sign up for an account, take a free trial and evaluate whether APM can meet your needs or solve your problems.

Many cloud providers are now actively partnering with APM vendors to embed agents within the servers they provision for customer applications. I personally know of a company that solved a 6 month production issue within an hour of deploying SaaS-based APM. How about that for ROI and time to value!

2. Cost – licenses, maintenance, administration, hardware

Simply put, subscription-based licenses are cheaper, more flexible and less risk than owning perpetual licenses. Annual maintenance is included in the subscription, as is the cost of managing and supporting the APM infrastructure required to monitor your applications. You don't need to buy hardware to run your APM management server, you also don't need to pay someone to manage it either – you simply deploy your agents and you're all done. There's now no need to sign up to a multi-million dollar 3 year APM ELA agreement with a vendor, you can pay as you go. If the APM software rocks you renew your subscription, if the APM software sucks you go elsewhere.

3. Ease of Use

When a customer signs up for a SaaS account and evaluates APM for the first time, there is no pre-sales or technical consultant sitting next to them to configure or demo the solution. The experience from account registration to application monitoring is a journey taken alone by the customer.

First impressions are everything with SaaS, the learning curve of APM in this context must therefore be faster and easier so the APM solution can sell itself to the customer.

SaaS-based APM solutions are also much younger than traditional on-premise software, meaning the technology, UI design principles, and concepts applied are more superior and interactive for the user. Try comparing the UI of an iPhone with a Nokia phone from 5 years ago and you'll see my point.

First generation APM solutions were typically written for developers by developers. Today the value of APM touches many different user skill sets. It is therefore no surprise that SaaS-based APM can appeal to and be adopted by development, operations and business users.

4. Migrating to the latest Release

When an APM vendor announces a new release of its software with lots of cool features, its normally down to the customers themselves to migrate to the new release. If things go well, they might spend several days or perhaps a few weeks performing the migration. If things go badly they might end up spending several weeks working hand in hand with the vendor to complete the migration.

With SaaS-based APM, the vendors themselves are responsible for the migration. Customers simply login and they get the latest version and features automatically. They get to harness APM innovation as soon as its ready, rather than having to wait weeks or months to find the time to migrate by themselves. If anything goes wrong then the vendor spends the time and money to fix it rather than the customer.

Customers today will typically upgrade their APM software once a year because of the time and effort. With SaaS-based APM, they can receive multiple upgrades and always be on the latest version.

5. Scalability

Enterprises and Cloud providers can manage lots of applications, which can span several thousand servers. It is one thing for a customer to deploy APM across two applications and a hundred servers in their organization. It is another thing to deploy it across fifty applications and a thousand servers.

Scaling APM has never been easy. The more agents you deploy, the more management servers you need to collect, process and manage the data. How quickly can you purchase, provision and maintain the APM management infrastructure when you've got hundreds of applications you want to monitor?

With SaaS-based APM, you let the vendor take care of that for you. I know of a SaaS-based APM user that monitors over 6,000 servers in their organization. Compare that with the largest APM on-premise deployment you know of and you can see why SaaS-based APM is a better scalability option.

So there you have it, five compelling reasons why you should consider SaaS-based APM in your organization. SaaS-based APM isn't for everyone though. I typically see less adoption in financial services customers where data privacy and security controls are much tighter.

ABOUT Stephen Burton

Stephen Burton is Tech Evangelist at AppDynamics, and is also the alter ego of increasingly popular "App Man" character. Steve is responsible for promoting best practice application performance management (APM) for distributed applications running in cloud, virtual and physical environments. Before joining AppDynamics, Steve held senior product management positions at OpTier and Precise, leading innovation and creative solutions to help customers better manage the performance of their applications. Steve has previously worked in pre-sales and also spent many years as a senior developer and application support engineer when his career began at Sapient.

Related Links:

www.appdynamics.com

12 Ways to Gain Faster ROI from APM

Stephen Burton's blog: Will Your Web Applications Suffer the Tweet of Death?

Hot Topics

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...