Skip to main content

Gartner Releases 2014 Magic Quadrant for APM

Gartner released the 2014 Magic Quadrant for Application Performance Monitoring report, by Research VPs Jonah Kowall and Will Cappelli.

The report noted an increased importance in the software-as-a-service (SaaS) delivery method for Application Performance Management (APM) capabilities: “Users are growing ever more convinced that there is little or no functional or performance loss when consuming APM through a SaaS delivery mode. In fact, security and operations issues can often be reduced or eliminated by consuming SaaS technologies. At the same time, the advantages of a zero-management platform and reduced maintenance and continuous feature evolution are becoming ever more salient in a ‘do more for less’ and DevOps-influenced IT environment.”

The report predicts, "By 2017 50% of application performance monitoring (APM) deployments that fulfill all five dimensions of functionality will be primarily SaaS, up from under 20% today."

The five dimensions of functionality include:

■ End-user experience monitoring (EUM)

■ Application topology discovery and visualization

■ User-defined transaction profiling

■ Application component deep dive

■ IT Operations Analytics (ITOA)

In the report, Gartner also noted key shifts in the functional emphasis of solutions in the changing APM market this year. “First, driven by the increasing significance of mobile application endpoints and dynamic Web technology, EUM is becoming even more important than it currently is to enterprises,” states the report.

"Second, the 2013 argument between an approach to application performance analytics that would couple ITOA functionality tightly to an APM portfolio and one that envisioned APM as one discipline that used a domain-independent ITOA platform, among others, will be decided in favor of the latter approach."

Evaluation criteria for "completeness of vision" included market understanding, marketing strategy, sales strategy, product strategy, business model, vertical and industry strategy, innovation, and geographic strategy. Criteria for "ability to execute" included product, overall viability, sales execution and pricing, market responsiveness and record, marketing execution, customer experience, and operations. Gartner positions each vendor on two axes — Completeness of Vision and Ability to Execute — which lands them in a particular Quadrant. Those who demonstrate market understanding on both axes are placed in the top right "Leaders" quadrant. In this report, AppDynamics, Compuware (now Dynatrace) and New Relic, were placed in the Leaders quadrant. The other vendors featured in the report include AppNeta, BMC, CA Technologies, HP, IBM, ManageEngine, Microsoft, Riverbed Technology and SmartBear.

“The Gartner Magic Quadrant is a particularly credible metric because of the meticulous methodology they follow in researching the marketplace," says Jyoti Bansal, AppDynamics founder and CEO. "Gartner’s APM analysts interview hundreds of customers who are APM users. The Magic Quadrant report reflects the feedback from these actual users, as well as other evaluation criteria and the expertise of Gartner’s analysts, and is widely used and trusted by APM buyers.”

Several links to the report are available below.

The Latest

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 ...

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

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 ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

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 ...

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 ...

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 ...

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 ...

Gartner Releases 2014 Magic Quadrant for APM

Gartner released the 2014 Magic Quadrant for Application Performance Monitoring report, by Research VPs Jonah Kowall and Will Cappelli.

The report noted an increased importance in the software-as-a-service (SaaS) delivery method for Application Performance Management (APM) capabilities: “Users are growing ever more convinced that there is little or no functional or performance loss when consuming APM through a SaaS delivery mode. In fact, security and operations issues can often be reduced or eliminated by consuming SaaS technologies. At the same time, the advantages of a zero-management platform and reduced maintenance and continuous feature evolution are becoming ever more salient in a ‘do more for less’ and DevOps-influenced IT environment.”

The report predicts, "By 2017 50% of application performance monitoring (APM) deployments that fulfill all five dimensions of functionality will be primarily SaaS, up from under 20% today."

The five dimensions of functionality include:

■ End-user experience monitoring (EUM)

■ Application topology discovery and visualization

■ User-defined transaction profiling

■ Application component deep dive

■ IT Operations Analytics (ITOA)

In the report, Gartner also noted key shifts in the functional emphasis of solutions in the changing APM market this year. “First, driven by the increasing significance of mobile application endpoints and dynamic Web technology, EUM is becoming even more important than it currently is to enterprises,” states the report.

"Second, the 2013 argument between an approach to application performance analytics that would couple ITOA functionality tightly to an APM portfolio and one that envisioned APM as one discipline that used a domain-independent ITOA platform, among others, will be decided in favor of the latter approach."

Evaluation criteria for "completeness of vision" included market understanding, marketing strategy, sales strategy, product strategy, business model, vertical and industry strategy, innovation, and geographic strategy. Criteria for "ability to execute" included product, overall viability, sales execution and pricing, market responsiveness and record, marketing execution, customer experience, and operations. Gartner positions each vendor on two axes — Completeness of Vision and Ability to Execute — which lands them in a particular Quadrant. Those who demonstrate market understanding on both axes are placed in the top right "Leaders" quadrant. In this report, AppDynamics, Compuware (now Dynatrace) and New Relic, were placed in the Leaders quadrant. The other vendors featured in the report include AppNeta, BMC, CA Technologies, HP, IBM, ManageEngine, Microsoft, Riverbed Technology and SmartBear.

“The Gartner Magic Quadrant is a particularly credible metric because of the meticulous methodology they follow in researching the marketplace," says Jyoti Bansal, AppDynamics founder and CEO. "Gartner’s APM analysts interview hundreds of customers who are APM users. The Magic Quadrant report reflects the feedback from these actual users, as well as other evaluation criteria and the expertise of Gartner’s analysts, and is widely used and trusted by APM buyers.”

Several links to the report are available below.

The Latest

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 ...

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

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 ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

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 ...

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 ...

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 ...

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 ...