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Keep Your Application Monitoring Out of the Dark Ages

The right blend of APM and microservices can bring your organization into the enlightened age
Matthew Dubie

Let's go back in time. Think of when your applications used to run from a single server and when the monolithic enterprise management software approach was more than enough to effectively monitor them. I know those days may have been just 10 years ago, but given the fast pace of the tech industry, those are officially our dark ages.

Now, let's fast-forward to the present application economy in which your customers are demanding higher quality applications faster than ever before. To meet these new expectations, the infrastructure of the application has evolved; inevitably becoming more sophisticated and ultimately more complex.

The complexity begins with the microservices architecture, which is the way many of today's enterprise applications are built. Microservices compartmentalize the application by function. Each function within the application architecture focuses on performing a small, specific process and communicates with other functions using APIs. This differs from the traditional service-oriented architecture (SOA), in that SOAs work to integrate multiple applications that function independently to perform a service.

Why Complicate Things?

The more an app can do, the better. Customers expect more than ever of enterprise applications — they want them to perform like consumer apps do — which results in an added pressure on organizations to be agile. Microservices do just that. By dividing application functions across the architecture, developers are better able to resolve issues and make adjustments more quickly — without having to redeploy the entire application.

Just as with the architecture, the monolithic approach of application monitoring that used to work is no longer sufficient. Microservices are more granular than SOAs and introduce a variety of new monitoring challenges that require an application monitoring approach better able to manage the more sophisticated application environment.

The four main challenges microservices present to application monitoring are complexity, change, resiliency and scale. These new intricacies make it difficult for application monitoring solutions to pinpoint the source where application issues arise, monitor environments at the rate in which they change, triage alerts, and scale the large amounts of data.

Your Apps Are Your Business

Microservices provide the functionality end users are looking for in their applications and your application monitoring solutions need to keep those applications up and running – and performing as customers demand.

But, the old approach to application monitoring just isn't working. It's time to forget about the dark ages; success in the application economy starts with providing your customers with a superior application experience. Is your application performance management approach enlightened?

Matthew Dubie is a Marketing Associate at CA Technologies.

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Keep Your Application Monitoring Out of the Dark Ages

The right blend of APM and microservices can bring your organization into the enlightened age
Matthew Dubie

Let's go back in time. Think of when your applications used to run from a single server and when the monolithic enterprise management software approach was more than enough to effectively monitor them. I know those days may have been just 10 years ago, but given the fast pace of the tech industry, those are officially our dark ages.

Now, let's fast-forward to the present application economy in which your customers are demanding higher quality applications faster than ever before. To meet these new expectations, the infrastructure of the application has evolved; inevitably becoming more sophisticated and ultimately more complex.

The complexity begins with the microservices architecture, which is the way many of today's enterprise applications are built. Microservices compartmentalize the application by function. Each function within the application architecture focuses on performing a small, specific process and communicates with other functions using APIs. This differs from the traditional service-oriented architecture (SOA), in that SOAs work to integrate multiple applications that function independently to perform a service.

Why Complicate Things?

The more an app can do, the better. Customers expect more than ever of enterprise applications — they want them to perform like consumer apps do — which results in an added pressure on organizations to be agile. Microservices do just that. By dividing application functions across the architecture, developers are better able to resolve issues and make adjustments more quickly — without having to redeploy the entire application.

Just as with the architecture, the monolithic approach of application monitoring that used to work is no longer sufficient. Microservices are more granular than SOAs and introduce a variety of new monitoring challenges that require an application monitoring approach better able to manage the more sophisticated application environment.

The four main challenges microservices present to application monitoring are complexity, change, resiliency and scale. These new intricacies make it difficult for application monitoring solutions to pinpoint the source where application issues arise, monitor environments at the rate in which they change, triage alerts, and scale the large amounts of data.

Your Apps Are Your Business

Microservices provide the functionality end users are looking for in their applications and your application monitoring solutions need to keep those applications up and running – and performing as customers demand.

But, the old approach to application monitoring just isn't working. It's time to forget about the dark ages; success in the application economy starts with providing your customers with a superior application experience. Is your application performance management approach enlightened?

Matthew Dubie is a Marketing Associate at CA Technologies.

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 ...

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