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APM - The "A" Dimension

Vikas Aggarwal

As more applications migrate to the evolving private and public cloud infrastructure, and permeate through the sprawling distributed “new” IT environment, the Gartner published “five dimensions” of Application Performance Monitoring become essential requirements for any APM monitoring platform.

Being able to capture end-user experience, topology, deep dive monitoring of components and analytics will enable IT operations to isolate APM performance issues, reduce the MTTR for application services, and ultimately higher user satisfaction.

With the arrival and rapid adoption of Virtualization and Cloud infrastructure, reduction in costs for "incremental units" of computing power, the ability to more easily flex up and down as needed, and the lack of restrictions imposed by the traditional models, are all key drivers to migrate applications to this distributed cloud infrastructure.

However, with these benefits comes the added burden of high administration overhead from managing a virally sprawling and dynamic IT environment.

As the number of discrete virtual servers, components and resident applications explodes, performance monitoring and intelligent analytical needs to make rapid decisions will be critical for IT operations. Manually intensive legacy point monitoring tools will not be able to keep up in a dynamic and complex environment where applications can move in almost real time across the underlying IT infrastructure.

Of course, the better approach would be to utilize and adopt the APM “A” dimension – Automation in the monitoring platform to reduce the burden from routine administrative tasks for application monitoring. Implementing the right systems and processes and finding a monitoring solution which uses a good degree of automation is essential to gain back the efficiency lost from the increased complexity of distributed application infrastructure.

Automation in the area of monitoring will ensure consistency in performance monitoring and benchmarking, enabling IT Operations to make better and proactive decisions for application performance. As JP Garbani at Forrester said recently, gaining the right level of productivity in IT operations will come from using better tools, and specifically, automation.

Vikas Aggarwal is CEO of Zyrion.

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APM - The "A" Dimension

Vikas Aggarwal

As more applications migrate to the evolving private and public cloud infrastructure, and permeate through the sprawling distributed “new” IT environment, the Gartner published “five dimensions” of Application Performance Monitoring become essential requirements for any APM monitoring platform.

Being able to capture end-user experience, topology, deep dive monitoring of components and analytics will enable IT operations to isolate APM performance issues, reduce the MTTR for application services, and ultimately higher user satisfaction.

With the arrival and rapid adoption of Virtualization and Cloud infrastructure, reduction in costs for "incremental units" of computing power, the ability to more easily flex up and down as needed, and the lack of restrictions imposed by the traditional models, are all key drivers to migrate applications to this distributed cloud infrastructure.

However, with these benefits comes the added burden of high administration overhead from managing a virally sprawling and dynamic IT environment.

As the number of discrete virtual servers, components and resident applications explodes, performance monitoring and intelligent analytical needs to make rapid decisions will be critical for IT operations. Manually intensive legacy point monitoring tools will not be able to keep up in a dynamic and complex environment where applications can move in almost real time across the underlying IT infrastructure.

Of course, the better approach would be to utilize and adopt the APM “A” dimension – Automation in the monitoring platform to reduce the burden from routine administrative tasks for application monitoring. Implementing the right systems and processes and finding a monitoring solution which uses a good degree of automation is essential to gain back the efficiency lost from the increased complexity of distributed application infrastructure.

Automation in the area of monitoring will ensure consistency in performance monitoring and benchmarking, enabling IT Operations to make better and proactive decisions for application performance. As JP Garbani at Forrester said recently, gaining the right level of productivity in IT operations will come from using better tools, and specifically, automation.

Vikas Aggarwal is CEO of Zyrion.

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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 ...

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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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