AppDynamics, a Cisco company, has been named a Leader in Gartner’s 2018 Magic Quadrant for Application Performance Monitoring Suites for the sixth year in a row.
In addition to being identified as a Leader, the company also placed the highest among 15 vendors on the ability to execute axis. AppDynamics says this recognition emphasizes AppDynamics’ deep understanding of what companies need to be successful as they reshape their businesses to meet consumer expectations for sophisticated, always-on services. And it also reflects Cisco’s support in accelerating AppDynamics’ time to market and ability to address the market on a global scale
“Transformation waits for no one. All businesses are a part of a hyper-competitive, global race to deliver the fastest possible service, best experiences and most value to consumers. The bar for excellence rapidly rises with every new software iteration,” said Bhaskar Sunkara, CTO, AppDynamics. “To win, modern businesses need the freedom to scale and evolve without constraints from application complexities and with the intelligence to back game-time decisions. AppDynamics is designed to deliver performances that exceed expectations in a digital-first world and free businesses to think bigger about what they can accomplish through technology.”
Businesses continue to face growing pains as they attempt to keep pace with consumers’ appetites for instant gratification at every touchpoint. What’s more, the proliferation of devices and distributed technologies have brought more unknowns to what’s actually driving business success and what’s causing damage to consumer relationships. Meeting customer expectations in this unknown frontier is forcing enterprises to reexamine how they deliver innovation.
AppDynamics’ banner year of innovations were dedicated to helping customers achieve more clarity, confidence and agility to solve these challenges and invigorate their edge in the industry. These include:
- Next Generation ofBusinessiQ: Simplifies Complex Business Problems to Power Data-driven Decisions– Given the inseparability between application success and business success, AppDynamics unleashed major innovations to Business iQ with a focus creating a single visual of customer experiences the way they actually unfold across any device. With a correlated view of business and technology performance, companies can shape their digital experiences to match the real-time needs and expectations of their customers.
- Perspica Technologies: Machine Learning Speeds Up Transformation of Data into Real-time Insights– The trillions of metrics across human-to-machine and machine-to-machine interactions have accelerated in volume and variety over the past year. To tackle the humanly impossible task of drawing insights from this data, AppDynamics will accelerate its machine learning capabilities with onboarding of Perspica’s team and technology that hold the domain-expertise needed to quickly turn data into business-aware insights.
- IoT & Network Monitoring: Provides Full Visibility from End-User Interactions on Connected Devices to Microservices Performance Across Multiple Clouds – As connected devices continue to spread and new applications use next generation architectures (e.g. microservices, containers and multi-cloud), the ability to glean insights into these dispersed environments is paramount to achieving exceptional experiences. With this in mind, AppDynamics launched full IoT and network visibility capabilities that map and correlate metrics that illuminate the entire user journey and network layer.
- Developer Toolkit: Improves App Team Collaboration with Development Lifecycle Transparency– With modern consumers setting the agenda for the way businesses evolve, continuous quality and performance have become directly responsible for brand loyalty and company success. To empower the teams at the heart of ensuring unbroken, flawless experiences, AppDynamics launched a suite of tools for unmatched visibility in the development lifecycle and flexibility required for DevOps environments.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
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 ...