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The App Hugger's Brief History of Application Recovery - Part II: The APM Era

Kevin McCartney

This is Part II of our recounting of the most common approaches to application recovery since the mid-1990s, along with an overview of the limitations we’ve run across most frequently.

Start with Part I

2009 – Present

APM is Born (“I See the Problem. Now What?”)

WHAT APM DOES:

• From end-user perspective
• Deep monitoring at code level
• More data by which to pinpoint application problems

LIMITATIONS: First generation Application Performance Management (APM) solutions tend to be application-specific and/or platform-specific, so they don’t reflect the typical enterprise—which is very heterogeneous.

In addition, the amounts of data generated by APM software can be overwhelming, coming from so many sources, requiring significant analytics to identify the root cause. This makes APM tools challenging as an operational tool in a run-time environment. Finally, once APM software identifies the problem, it doesn’t give you the tools you need to fix the problem.

2013 – Present

Push-Button Application Recovery (“Welcome to the Application Age”)

WHAT IT DOES:

• Application- and platform-agnostic
• Stateful awareness
• Automatically execute pre-determined steps based on business rules

FEATURES:

• Stateful awareness of the application
• Understanding of the application’s architecture, its components, and related dependencies
• A unique design leveraging the application process component layer
• Secure, policy-driven action

What Do Next Gen Application Management Platforms Look Like?

Next generation Application Management platforms are emerging that address the realistic problems faced by today’s enterprises, which are:

(a) increasingly application-centric (as opposed to hardware- and network-focused)

(b) utilize hundreds of diverse apps and systems

(c) run in heterogeneous environments

Push-Button Application Recovery — enabled by stateful awareness of each application and by leveraging the Application Process Component layer, which is common across all applications — and other new Application Management features have the potential to dramatically speed recovery time and significantly reduce the resources required to recover an application.

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The App Hugger's Brief History of Application Recovery - Part II: The APM Era

Kevin McCartney

This is Part II of our recounting of the most common approaches to application recovery since the mid-1990s, along with an overview of the limitations we’ve run across most frequently.

Start with Part I

2009 – Present

APM is Born (“I See the Problem. Now What?”)

WHAT APM DOES:

• From end-user perspective
• Deep monitoring at code level
• More data by which to pinpoint application problems

LIMITATIONS: First generation Application Performance Management (APM) solutions tend to be application-specific and/or platform-specific, so they don’t reflect the typical enterprise—which is very heterogeneous.

In addition, the amounts of data generated by APM software can be overwhelming, coming from so many sources, requiring significant analytics to identify the root cause. This makes APM tools challenging as an operational tool in a run-time environment. Finally, once APM software identifies the problem, it doesn’t give you the tools you need to fix the problem.

2013 – Present

Push-Button Application Recovery (“Welcome to the Application Age”)

WHAT IT DOES:

• Application- and platform-agnostic
• Stateful awareness
• Automatically execute pre-determined steps based on business rules

FEATURES:

• Stateful awareness of the application
• Understanding of the application’s architecture, its components, and related dependencies
• A unique design leveraging the application process component layer
• Secure, policy-driven action

What Do Next Gen Application Management Platforms Look Like?

Next generation Application Management platforms are emerging that address the realistic problems faced by today’s enterprises, which are:

(a) increasingly application-centric (as opposed to hardware- and network-focused)

(b) utilize hundreds of diverse apps and systems

(c) run in heterogeneous environments

Push-Button Application Recovery — enabled by stateful awareness of each application and by leveraging the Application Process Component layer, which is common across all applications — and other new Application Management features have the potential to dramatically speed recovery time and significantly reduce the resources required to recover an application.

Hot Topics

The Latest

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 4 covers negative impacts of AI ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 3 covers barriers and challenges for AI ...