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Resource Monitoring vs. Application Performance Monitoring (APM)

How Middleware Resource Monitoring is Different from APM
Ted Wilson

Is middleware resource monitoring the same thing as APM? No – but it is highly complementary with APM and organizations generally need both for complex, large-scale application environments that depend on middleware.

End to end resource monitoring is fundamentally different.


We see four general categories in the enterprise monitoring landscape:

1. Low level infrastructure monitoring, often open source or low-cost

2. Domain-specific admin and monitoring tools including database, server, log, and vendor-specific tools

3. Application-aware resource monitoring of infrastructure

4. APM, including transaction tracing and end-user monitoring

APM, and especially transaction monitoring, has its place. It is an important capability for some types of users such as developers who need to understand the behavior of their transactions and how they are performing. It is also very good at identifying code-based problems. If your problems are in the code, then APM can help. But what if the problem is not in the application itself but the infrastructure that supports that application? Most application performance issues are not code-based problems.

Oftentimes, the problems lie in the middleware tiers, servers and other resources. These are equally as important to monitor.

The Complexity of Middleware

Middleware components are usually distributed, clustered and shared across multiple services and applications. Many organizations use middleware provided by multiple vendors across multiple tiers, on-premise, in the cloud, or hybrid. And a single middleware technology, such as TIBCO EMS, requires real-time and historical metric gathering for the EMS Servers, topics, queues, and destinations to really understand performance. An effective monitoring system will also provide information about other interdependencies. Is a problem with pending messages really occurring because of a CPU issue with a VMware host?

This all makes holistic monitoring tricky. So when an application problem lies in a middleware tier, your application support and middleware support teams require specialized tools to proactively identify the problem before the application is affected. If they are relying on end user or transaction monitoring for this type of problem, chances are the middleware components are going to be a black box. APM tools just don’t provide adequate visibility into the middleware.

So before you increase spending on APM tools, be sure you have the middleware tier covered and those support teams have the tools they need to be proactive in resolving the infrastructure level problems.

Ask yourself how you solve the majority of your Sev 1 incidents today. Are you using tools that help you understand the performance of your clustered middleware? Or are you using tools that help you understand your transactions and transaction throughput? The answer may help you in prioritizing your monitoring investments.


Ted Wilson is Chief Operating Officer at SL Corporation.

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Resource Monitoring vs. Application Performance Monitoring (APM)

How Middleware Resource Monitoring is Different from APM
Ted Wilson

Is middleware resource monitoring the same thing as APM? No – but it is highly complementary with APM and organizations generally need both for complex, large-scale application environments that depend on middleware.

End to end resource monitoring is fundamentally different.


We see four general categories in the enterprise monitoring landscape:

1. Low level infrastructure monitoring, often open source or low-cost

2. Domain-specific admin and monitoring tools including database, server, log, and vendor-specific tools

3. Application-aware resource monitoring of infrastructure

4. APM, including transaction tracing and end-user monitoring

APM, and especially transaction monitoring, has its place. It is an important capability for some types of users such as developers who need to understand the behavior of their transactions and how they are performing. It is also very good at identifying code-based problems. If your problems are in the code, then APM can help. But what if the problem is not in the application itself but the infrastructure that supports that application? Most application performance issues are not code-based problems.

Oftentimes, the problems lie in the middleware tiers, servers and other resources. These are equally as important to monitor.

The Complexity of Middleware

Middleware components are usually distributed, clustered and shared across multiple services and applications. Many organizations use middleware provided by multiple vendors across multiple tiers, on-premise, in the cloud, or hybrid. And a single middleware technology, such as TIBCO EMS, requires real-time and historical metric gathering for the EMS Servers, topics, queues, and destinations to really understand performance. An effective monitoring system will also provide information about other interdependencies. Is a problem with pending messages really occurring because of a CPU issue with a VMware host?

This all makes holistic monitoring tricky. So when an application problem lies in a middleware tier, your application support and middleware support teams require specialized tools to proactively identify the problem before the application is affected. If they are relying on end user or transaction monitoring for this type of problem, chances are the middleware components are going to be a black box. APM tools just don’t provide adequate visibility into the middleware.

So before you increase spending on APM tools, be sure you have the middleware tier covered and those support teams have the tools they need to be proactive in resolving the infrastructure level problems.

Ask yourself how you solve the majority of your Sev 1 incidents today. Are you using tools that help you understand the performance of your clustered middleware? Or are you using tools that help you understand your transactions and transaction throughput? The answer may help you in prioritizing your monitoring investments.


Ted Wilson is Chief Operating Officer at SL Corporation.

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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 ...

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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 ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...