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Gartner Publishes New Report: Critical Capabilities for Application Performance Monitoring

Gartner has published a new APM report, Critical Capabilities for Application Performance Monitoring, authored by Cameron Haight, Will Cappelli and Federico De Silva.

The report, a companion document to the Gartner Magic Quadrant for APM which evaluates APM suite capabilities across five usage scenarios, is designed to assist IT planners as they look to support mission-critical e-commerce and other services. Those use cases identified by Gartner consist of Application Support, Application Development, IT Operations, Application Owner or LOB, and DevOps Release.

Fifteen vendor products were chosen and evaluated for each capability and scored on a five-point scale. The capabilities assessed for each use case included business analysis, service monitoring, anomaly detection, distributed profiling, application debugging, and workload planning.

The report covers several APMdigest sponsors, including:

■ AppDynamics

■ CA Technologies

■ Dynatrace

■ Nastel Technologies

■ New Relic

“We’re thrilled with AppDynamics’ first place ranking in Gartner’s recent ‘Critical Capabilities’ report,” said AppDynamics President and CEO David Wadhwani. “It’s critical that enterprises have an effective and unified application performance monitoring, troubleshooting and analytics solution in place — our AppDynamics Application Intelligence Platform is an essential pillar for driving digital transformation forward. We believe Gartner’s research further solidifies AppDynamics’ leadership across the board, by being named a Leader in the Magic Quadrant for Application Performance Monitoring Suites and in the use cases paramount for ensuring successful business outcomes.”

In addition, the report covers AppNeta, BMC Software, Dell, Hewlett Packard Enterprise, IBM, JenniferSoft, ManageEngine, Microsoft, Riverbed Technology and Tingyun.

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Gartner Publishes New Report: Critical Capabilities for Application Performance Monitoring

Gartner has published a new APM report, Critical Capabilities for Application Performance Monitoring, authored by Cameron Haight, Will Cappelli and Federico De Silva.

The report, a companion document to the Gartner Magic Quadrant for APM which evaluates APM suite capabilities across five usage scenarios, is designed to assist IT planners as they look to support mission-critical e-commerce and other services. Those use cases identified by Gartner consist of Application Support, Application Development, IT Operations, Application Owner or LOB, and DevOps Release.

Fifteen vendor products were chosen and evaluated for each capability and scored on a five-point scale. The capabilities assessed for each use case included business analysis, service monitoring, anomaly detection, distributed profiling, application debugging, and workload planning.

The report covers several APMdigest sponsors, including:

■ AppDynamics

■ CA Technologies

■ Dynatrace

■ Nastel Technologies

■ New Relic

“We’re thrilled with AppDynamics’ first place ranking in Gartner’s recent ‘Critical Capabilities’ report,” said AppDynamics President and CEO David Wadhwani. “It’s critical that enterprises have an effective and unified application performance monitoring, troubleshooting and analytics solution in place — our AppDynamics Application Intelligence Platform is an essential pillar for driving digital transformation forward. We believe Gartner’s research further solidifies AppDynamics’ leadership across the board, by being named a Leader in the Magic Quadrant for Application Performance Monitoring Suites and in the use cases paramount for ensuring successful business outcomes.”

In addition, the report covers AppNeta, BMC Software, Dell, Hewlett Packard Enterprise, IBM, JenniferSoft, ManageEngine, Microsoft, Riverbed Technology and Tingyun.

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Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

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 ...

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