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.

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Beyond Traditional Autoscaling: The Future of Kubernetes in AI Infrastructure

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI Drives Surge in Data Budgets

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned Architecture Causes Service Disruptions, High Operational Costs and Security Challenges

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

How GenAI Can Save Time for the NetOps Team

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

Will AI Solve the Growing Data Divide?

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Top Concerns for Tech Decision Makers

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

Gartner: Top Trends Shaping the Future of Cloud

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

The Great SaaS Hangover (and the Cure Nobody Is Talking About)

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

OpenShift Monitoring: 5 Things You Need to Keep an Eye on

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...