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Franken-Monitoring - A Case of Too Many Tools

Most Organizations Have 11 or more tools to Manage Application Performance
Kalyan Ramanathan

In a recent interview, an IT operations director told us, “We frankly have too many tools, and many of them weren’t performing to our expectations.”

If you are an enterprise ops leader managing complex applications, you can probably relate to that statement. At AppDynamics, we call this “Franken-monitoring,” a situation characterized by many, usually too many, siloed tools — for application, server, database, end-user client, etc. — that provide varying levels of disparate visibility into IT applications.

The challenges with this approach include:

■ Tools have minimal integration or common context, which makes it near impossible to manage the application or its business transactions.

■ Tools are designed for subject-matter experts, so it’s hard to provide value to the ops team as a whole.

■ Tools have high total cost of ownership, since every tool has to be independently procured, installed and managed, and staff have to be trained in their use.

2015 APM Tools Survey Finds That Tools Are Underutilized and Solving Performance Problems is Still a Massive Challenge

We commissioned analyst firm Enterprise Management Associates (EMA) to get to the bottom of this. In the 2015 APM Tools Survey, EMA found that a majority of surveyed enterprises have 11 or more commercial tools in their arsenal to manage application performance.

Nearly two-thirds of respondents report that it takes at least three hours to determine the root cause of performance issues; one-third report that it takes six or more hours to find the source of an issue.

EMA’s survey indicated that the lack of application-focused solutions appears to contribute to current IT challenges, with IT teams often trying to manage modern, complex applications with siloed tools and primarily manual processes. Just about every user of monitoring tools complains about the challenges of having too many tools without any situational awareness. Current approaches to integrate these tools with solutions like MoM (manager of managers) or CMDB (configuration management database) have for the most part failed, because it is hard to stitch together these disparate solutions from different vendors.

Gartner recently did a survey that pointed exactly to this challenge. The key reasons (besides price) for poor APM adoption were, indeed, the complexity of the tools and poor integration between tools.

Specifically, the EMA study found:

■ Siloed and shelved monitoring tools: 65 percent of the companies surveyed indicated that they own more than 10 different commercial monitoring products. Nearly half also indicated that 50 percent or fewer of their purchased tools are actively being used.

■ Manual resources expended on application support: According to respondents, calls from users are the second-most frequent way IT organizations find out about application-related problems (27 percent cited detection by monitoring centers; 25 percent cited user calls). Line staff, those closest to the problem, report a significantly higher incidence, citing user calls as their first “heads up” 35 percent of the time.

■ Extensive people-hours required to solve a single application problem: IT organizations surveyed indicated that, for those application-related problems escalated beyond Level 1 support, mean time to repair (MTTR) is most often between five and seven hours; in addition, between three and four people are typically required to solve a given problem.

“Based on our findings, the majority of companies are still trying to manage complex applications with a combination of siloed tools, ‘all hands on deck’ interactive marathons, and tribal knowledge,” said Julie Craig, Research Director, Application Management at EMA. “The ability to automatically discover and manage the business transaction topology as the application itself changes is a significant challenge encountered by virtually every IT organization.”

In addition to EMA’s finding that most companies have under-invested in application-specific management tools, the survey also found clear purchasing preferences regarding future APM purchases:

■ Almost 75 percent identified “flexible deployment options” (supporting SaaS, on-premises, and/or hybrid deployments) as either “critical or important” factors for purchasing an APM solution.

■ More than 70 percent identified the “ability to monitor infrastructure as a service (IaaS) public cloud” as either critical or important.

■ When asked about their top “must have” features for an APM product purchase, respondents selected the following:

#1 feature preference: An integrated monitoring platform consolidating application and infrastructure monitoring in one solution

#2 feature preference: Cloud-readiness features necessary to monitor/manage application components hosted in public cloud

#3 feature preference: Support for trending and reporting

The EMA study shows that very few IT organizations have an accurate, comprehensive view of today’s complex application environment, business transactions and their dependencies. Unified Monitoring is a new way to manage applications proactively, by tracing and monitoring transactions from the end user through the entire application and infrastructure environment to help quickly and proactively solve performance issues and ensure excellent user experience. Companies no longer need to waste valuable time and resources on a dozen different tools that will likely just collect dust on the shelf.

EMA Survey Methodology: AppDynamics commissioned EMA to conduct a survey in May 2015 of nearly 300 IT professionals from small, midsized and large companies across both North America and Europe. For the purposes of the study, respondents were filtered to include only those actively involved in enterprise application development/management/delivery at the executive, middle manager, or "hands on" line staff levels.

Kalyan Ramanathan is VP Marketing at AppDynamics.

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Franken-Monitoring - A Case of Too Many Tools

Most Organizations Have 11 or more tools to Manage Application Performance
Kalyan Ramanathan

In a recent interview, an IT operations director told us, “We frankly have too many tools, and many of them weren’t performing to our expectations.”

If you are an enterprise ops leader managing complex applications, you can probably relate to that statement. At AppDynamics, we call this “Franken-monitoring,” a situation characterized by many, usually too many, siloed tools — for application, server, database, end-user client, etc. — that provide varying levels of disparate visibility into IT applications.

The challenges with this approach include:

■ Tools have minimal integration or common context, which makes it near impossible to manage the application or its business transactions.

■ Tools are designed for subject-matter experts, so it’s hard to provide value to the ops team as a whole.

■ Tools have high total cost of ownership, since every tool has to be independently procured, installed and managed, and staff have to be trained in their use.

2015 APM Tools Survey Finds That Tools Are Underutilized and Solving Performance Problems is Still a Massive Challenge

We commissioned analyst firm Enterprise Management Associates (EMA) to get to the bottom of this. In the 2015 APM Tools Survey, EMA found that a majority of surveyed enterprises have 11 or more commercial tools in their arsenal to manage application performance.

Nearly two-thirds of respondents report that it takes at least three hours to determine the root cause of performance issues; one-third report that it takes six or more hours to find the source of an issue.

EMA’s survey indicated that the lack of application-focused solutions appears to contribute to current IT challenges, with IT teams often trying to manage modern, complex applications with siloed tools and primarily manual processes. Just about every user of monitoring tools complains about the challenges of having too many tools without any situational awareness. Current approaches to integrate these tools with solutions like MoM (manager of managers) or CMDB (configuration management database) have for the most part failed, because it is hard to stitch together these disparate solutions from different vendors.

Gartner recently did a survey that pointed exactly to this challenge. The key reasons (besides price) for poor APM adoption were, indeed, the complexity of the tools and poor integration between tools.

Specifically, the EMA study found:

■ Siloed and shelved monitoring tools: 65 percent of the companies surveyed indicated that they own more than 10 different commercial monitoring products. Nearly half also indicated that 50 percent or fewer of their purchased tools are actively being used.

■ Manual resources expended on application support: According to respondents, calls from users are the second-most frequent way IT organizations find out about application-related problems (27 percent cited detection by monitoring centers; 25 percent cited user calls). Line staff, those closest to the problem, report a significantly higher incidence, citing user calls as their first “heads up” 35 percent of the time.

■ Extensive people-hours required to solve a single application problem: IT organizations surveyed indicated that, for those application-related problems escalated beyond Level 1 support, mean time to repair (MTTR) is most often between five and seven hours; in addition, between three and four people are typically required to solve a given problem.

“Based on our findings, the majority of companies are still trying to manage complex applications with a combination of siloed tools, ‘all hands on deck’ interactive marathons, and tribal knowledge,” said Julie Craig, Research Director, Application Management at EMA. “The ability to automatically discover and manage the business transaction topology as the application itself changes is a significant challenge encountered by virtually every IT organization.”

In addition to EMA’s finding that most companies have under-invested in application-specific management tools, the survey also found clear purchasing preferences regarding future APM purchases:

■ Almost 75 percent identified “flexible deployment options” (supporting SaaS, on-premises, and/or hybrid deployments) as either “critical or important” factors for purchasing an APM solution.

■ More than 70 percent identified the “ability to monitor infrastructure as a service (IaaS) public cloud” as either critical or important.

■ When asked about their top “must have” features for an APM product purchase, respondents selected the following:

#1 feature preference: An integrated monitoring platform consolidating application and infrastructure monitoring in one solution

#2 feature preference: Cloud-readiness features necessary to monitor/manage application components hosted in public cloud

#3 feature preference: Support for trending and reporting

The EMA study shows that very few IT organizations have an accurate, comprehensive view of today’s complex application environment, business transactions and their dependencies. Unified Monitoring is a new way to manage applications proactively, by tracing and monitoring transactions from the end user through the entire application and infrastructure environment to help quickly and proactively solve performance issues and ensure excellent user experience. Companies no longer need to waste valuable time and resources on a dozen different tools that will likely just collect dust on the shelf.

EMA Survey Methodology: AppDynamics commissioned EMA to conduct a survey in May 2015 of nearly 300 IT professionals from small, midsized and large companies across both North America and Europe. For the purposes of the study, respondents were filtered to include only those actively involved in enterprise application development/management/delivery at the executive, middle manager, or "hands on" line staff levels.

Kalyan Ramanathan is VP Marketing at AppDynamics.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.