Cisco announced a series of new solutions - enriched by business context - on the Cisco Observability Platform, to help customers deliver secure and performant user and application experience.
- Digital Experience Monitoring (DEM) for greater visibility and insight into user behavior: With application experience expectations at an all-time high, technologists can now leverage new Digital Experience Monitoring (DEM) capabilities for both hybrid and cloud environments. The new DEM application includes Real User Monitoring (RUM) and Session Replay modules for deep insights into browser and mobile applications performance and efficient resolution of session-level issues. In addition, integrations with Cisco ThousandEyes and Cisco Accedian empower applications and network teams with the insights into service delivery required to identify whether the root cause of impacted digital experience is the application, network or cloud infrastructure.
- Observability for Kubernetes workloads, powered by extended Berkeley Packet Filters (eBPF) technology: Cisco offers observability for Kubernetes workloads on the Cisco Observability Platform, using the powerful, lightweight Linux kernel utility, extended Berkeley Packet Filters (eBPF). Operating at the kernel level allows operators access to granular visibility into network activity, resource utilization, application dependencies and misconfigurations impacting network performance, without the need for multiple tools, cross-team collaboration and manual dependency mapping.
- Unified Observability Experience for increased application insights: Cisco is delivering a unified experience across its observability portfolio, with new capabilities across Cisco AppDynamics and the Cisco Observability Platform. Using a single account and shared context, the unified observability experience arms operators with capabilities including Log Analytics, to search with context and improved log storage; and Core Web Vitals, providing front-end application owners the golden signals to keep their web pages from being de-ranked for poor user experience.
- Natural Language Interface, powered by Generative AI: As part of Cisco's continued expansion in innovations powered by Generative AI, the Cisco Observability Platform now offers a natural language interface for troubleshooting. Operators can use conversational dialogues instead of a structured query language to perform common tasks during troubleshooting, thereby increasing productivity.
"These latest innovations further boost the core capabilities of the Cisco Observability Platform, empowering our customers with better visibility, insights and actions across domains than ever before," said Ronak Desai, Senior Vice President and General Manager, Cisco AppDynamics and Full-Stack Observability. "Cisco is uniquely positioned to deliver all the benefits of observability in a unified platform to support our customers' digital ecosystems."
In addition, Cisco is announcing:
- Cisco AIOps for Cisco Full-Stack Observability for actionable insights that improve IT operations: The new Cisco AIOps application simplifies real-time business health monitoring and significantly reduces noise from events and alerts to automate IT processes and keep operations teams productive and responsive. The application unifies data from Cisco AppDynamics, Cisco ThousandEyes, Cisco DNA Center, VMWare, Zabbix and ServiceNow (ITSM, ITOM and CMDB). It is uniquely positioned having been built on the Cisco Observability Platform, which supports logs in addition to alerts, events and metrics. It also provides dynamic thresholds-based alerting on metrics and events and multiple anomaly-detection approaches.
- Data Security Posture Management (DSPM) Observability: The introduction of Data Security Posture Management (DSPM) Observability to Cisco's Business Risk Observability solution delivers real-time and automated data discovery, classification, policy definition and compliance visibility for sensitive data, in addition to visualizing and prioritizing attack surface.
- New Partner Modules: Continuing the momentum of creating an observability ecosystem with its global partners across categories including AIOps, MLOps, networking, infrastructure observability and business insights, Cisco unveiled a series of new partner modules on the Cisco Observability Platform:
Aporia – Machine Learning Monitoring.
CloudFabrix – Asset Intelligence, Operational Intelligence and Infrastructure Observability.
Komodor – Kubernetes Change Management.
Perform IT – AS400 Monitoring and I4Cube business performance.
SoftServe – Operational Intelligence for Oilfields.
Availability:
Digital Experience Monitoring (DEM) application with Browser Real-User Monitoring (Generally Available)
Mobile Real-User Monitoring (Pre-Announce), and Session Replay (Generally Available) capabilities.
Integration with Cisco Accedian (Pre-Announce)
Integration with Cisco ThousandEyes (Pre-Announce)
Observability for Kubernetes workloads powered by eBPF (Generally Available)
Unified Observability Experience – Log Analytics (Generally Available) and Core Web Vitals (Pre-Announce)
GenAI-driven Natural Language Interface (Generally Available)
Cisco AIOps for Cisco Full-Stack Observability (Generally Available)
Data Security Posture Management (DSPM) Observability (Pre-Announce)
Partner Modules on the Cisco Observability Platform (Generally Available)
The Latest
Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...
Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...
Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...
If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...
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 ...