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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.

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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

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...