
AppDynamics announced general market availability of Experience Journey Map — the latest addition to Business iQ, introduced is Cisco Live 2020 — that provides additional functionality to further solidify this feature as a premiere resource for capturing rich, multi-dimensional views of performance across the customer experience.
With Experience Journey Map, deep insight and visibility into your application environment is just a few clicks away, thanks to a comprehensive visual representation of your web or mobile environments. But with this latest round of enhancements, AppDynamics takes that visibility a level deeper, giving you the ability to segment performance data by device, operating system, browser and even geo-location. You can even identify and isolate user sessions that exhibit poor performance for faster, more streamlined troubleshooting.
With these latest enhancements, it’s easier than ever to reveal and eliminate hidden bottlenecks, so you can proactively manage the digital journey and consistently deliver a world-class customer experience.
Experience Journey Map provides an aggregated view of all web or mobile sessions across an application, mapping the most trafficked paths as well as the user experience leading to each step. By delivering visibility across the entire application experience, the functionality enables application owners, IT Ops and developers to identify slower portions of the customer journey, as well as areas where optimization could benefit the most users.
Key Benefits of Experience Journey Map
For application owners:
- Provides a real-time, out-of-box view of the application experience and segmentation at each step of the customer journey across devices, browsers, and geographies — a boon for managing, prioritizing, and maximizing resource investment.
- Identifies the most critical areas of the application, making it easier to collaborate with operations and developers to proactively identify blind spots in monitoring.
For IT operations:
- Enables better prioritization of performance incidents based on the number of users impacted.
- Locates bottlenecks in the customer experience with in-context drill-downs right from within the Experience Journey Map, simplifying deployment of additional resources as traffic increases.
For developers:
- Identifies steps within the customer journey that reveal a higher number of errors, including web page and mobile application errors, to enable faster resolution.
- Fosters collaboration with application owners to optimize areas of the application that greatly enhance the user experience.
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 ...