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Application Performance Monitoring Cheat Sheet

Phee-Lip
BHP

A brief introduction to Applications Performance Monitoring (APM), breaking it down to a few key points:

1. It is different from conventional infrastructure monitoring which primarily captures and reports on hardware performance such as CPU and memory but APM also covers more advanced infra technology, such as containers, etc.

2. APM tells you how the application, which sits on top of the infrastructure, is performing by going deep into the code level and it includes the capability to monitor microservices and different types of programming languages.

3. Recently (actually not so recent) it has expanded to include user experience monitoring which encapsulates capturing of the user journey, reporting of errors and performance of user-triggered activities (click-on-page) as user behavior and experience are becoming more essential.

4. With a huge amount of data being collected, it is only natural that it has become a big data platform for companies to gain insights into their operations and business. Hence the expansion into analytic!

A few important lessons which I have learned over the years:

1. Many organizations are still "stuck" at reporting service availability. This requires a fundamental mindset change as the spotlight is now on application performance and service quality. These are critical aspects of digitization which no companies can afford to neglect.

2. APM can pinpoint the problems but it can't fix them for you. At least not now, perhaps later with AI. It is not a silver bullet and it draws out a very important point that organizations MUST HAVE system/domain expertise to maintain and improve the systems which are the most critical to their business!

3. Not everything is created equally. Hence you don't need a full-fledged APM tool for every system. Focus on the most critical systems. That will not only save you money but enable you to have undivided attention only on those which you care deeply about.

4. It is hard to find the best APM tool in every aspect of its capabilities. You just have to decide what are the most crucial elements for success and find the best solutions for them. You may end up with a couple of tools, hence it will be good to look at how you can gain a cohesive view across these tools to form your master service performance dashboard. Some form of integration may be required.

5. Many organizations have a central monitoring team who have eyes-on monitoring 24x7. This is old school and ineffective. Natural language processing (NLP) is the future with exception-based voice notification and an intelligent contextual query to have a deep understanding of systems health and performance, anytime, anywhere.

APM is a complex topic as it is a multi-faceted discipline. It will continue to evolve, branching into other domains such as service automation (self-healing), service management and deep learning. These areas have been coined as AIOps by Gartner, heavily anchored on AI. Definitely a space to watch out going forward!

Phee-Lip is Principal, APM Practice Lead, at BHP

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Application Performance Monitoring Cheat Sheet

Phee-Lip
BHP

A brief introduction to Applications Performance Monitoring (APM), breaking it down to a few key points:

1. It is different from conventional infrastructure monitoring which primarily captures and reports on hardware performance such as CPU and memory but APM also covers more advanced infra technology, such as containers, etc.

2. APM tells you how the application, which sits on top of the infrastructure, is performing by going deep into the code level and it includes the capability to monitor microservices and different types of programming languages.

3. Recently (actually not so recent) it has expanded to include user experience monitoring which encapsulates capturing of the user journey, reporting of errors and performance of user-triggered activities (click-on-page) as user behavior and experience are becoming more essential.

4. With a huge amount of data being collected, it is only natural that it has become a big data platform for companies to gain insights into their operations and business. Hence the expansion into analytic!

A few important lessons which I have learned over the years:

1. Many organizations are still "stuck" at reporting service availability. This requires a fundamental mindset change as the spotlight is now on application performance and service quality. These are critical aspects of digitization which no companies can afford to neglect.

2. APM can pinpoint the problems but it can't fix them for you. At least not now, perhaps later with AI. It is not a silver bullet and it draws out a very important point that organizations MUST HAVE system/domain expertise to maintain and improve the systems which are the most critical to their business!

3. Not everything is created equally. Hence you don't need a full-fledged APM tool for every system. Focus on the most critical systems. That will not only save you money but enable you to have undivided attention only on those which you care deeply about.

4. It is hard to find the best APM tool in every aspect of its capabilities. You just have to decide what are the most crucial elements for success and find the best solutions for them. You may end up with a couple of tools, hence it will be good to look at how you can gain a cohesive view across these tools to form your master service performance dashboard. Some form of integration may be required.

5. Many organizations have a central monitoring team who have eyes-on monitoring 24x7. This is old school and ineffective. Natural language processing (NLP) is the future with exception-based voice notification and an intelligent contextual query to have a deep understanding of systems health and performance, anytime, anywhere.

APM is a complex topic as it is a multi-faceted discipline. It will continue to evolve, branching into other domains such as service automation (self-healing), service management and deep learning. These areas have been coined as AIOps by Gartner, heavily anchored on AI. Definitely a space to watch out going forward!

Phee-Lip is Principal, APM Practice Lead, at BHP

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The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

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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