Cisco unveiled a multi-domain approach that bridges application and infrastructure teams with full-stack visibility and operational insight, allowing both real-time and automated troubleshooting to ensure optimal application performance. A new Kubernetes-based application platform makes it easier for both DevOps and IT to embrace a multicloud world.
New innovations from Cisco:
- Cisco's AppDynamics introduces the AppDynamics Experience Journey Map which automatically displays the most important user experience journeys within mission critical apps. These journeys focus on both business metrics and application experience to give business and app teams a single correlated view across business performance, user experience, and application performance.
- AppDynamics and Cisco Intersight Workload Optimizer now exchange and correlate data to give application and infrastructure teams a shared view of infrastructure dependencies that effect application performance, user experience, and business impact. Using common vocabulary, common tooling and sharing datasets between application and infrastructure health, Cisco enables IT teams to more easily cooperate and focus on what matters most: the business and customers. This industry-first, direct coupling of application insight to infrastructure automation empowers infrastructure teams to keep up with the demands of application-centric businesses in real time, while managing costs and complexity.
- Cisco Intersight Workload Optimizer introduces powerful workload and cost optimization capabilities across hybrid application architectures. Intersight Workload Optimizer takes into consideration performance, cost and compliance constraints. It uses historical and real-time knowledge to proactively flag potential issues as well as list opportunities to lower costs driven by over provisioning. Unlike approaches that start and end with virtualized infrastructure, this solution can pin-point the root cause for application degradation whether it be at the application level, at the VM/container layer or deep within the storage, compute or network hardware.
- Cisco HyperFlex Application Platform delivers an integrated container-as-a-service platform that simplifies provisioning and ongoing operations for Kubernetes across cloud, data center, and edge. This new platform curates open-source tooling, automates routine tasks, and makes it easier for IT and DevOps teams to use Kubernetes in a way that accelerates application innovation across multi-cloud environments. It also supports real-time monitoring and optimization of the complete application to infrastructure stack using AppDynamics and Intersight.
"Applications are now at the heart of every business but managing the IT infrastructure to ensure a positive user experience has never been more complex," said Liz Centoni, SVP and GM, Cloud, Compute and IoT at Cisco. "These new technologies provide full visibility and deep insights into all aspects of infrastructure through the lens of application, simplifying real-time correction and automated predictability to identify and fix issues before they even happen. While some vendors provide visibility into apps or an individual tier of physical or virtual infrastructure, Cisco is the first to bridge all three with insight and proactive optimization up and down the stack. And with the HyperFlex Application Platform we are making Kubernetes, the new defacto standard for app developers, much easier to deploy and manage for both app and infrastructure teams."
Availability:
- AppDynamics Customer Journey Map will be available in 2QCY20
- Cisco Intersight Workload Optimizer will be available in 2QCY20
- HyperFlex Application Platform for Kubernetes will be available for early access in 2QCY20
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 ...