Riverbed Technology announced the launch of Riverbed SteelCentral AppInternals 10, an Application Performance Management (APM) solution that helps IT teams take control of application performance in their evolving hybrid IT environments.
SteelCentral AppInternals 10 has been re-designed from the ground up. It can be set up in minutes and its modern, web-based, interactive dashboard can be accessed on computers, tablets, and smartphones – no special skills are required to set up and operate.
SteelCentral AppInternals 10 monitors applications on and off the cloud to provide end-to-end performance visibility and powerful analytics that help IT improve application performance, user experience, and business impact. SteelCentral AppInternals 10 traces every transaction from end-user device or browser to the application backend, while capturing second-by-second system metrics in production environments. These capabilities provide the most accurate perspectives into the end user experience, user demographics, and application performance, along with convenient workflows for root cause analysis. Further, IT can proactively improve performance by analyzing billions of metrics using simple queries to discover bugs and deliver business insights.
SteelCentral AppInternals solves visibility and control challenges to facilitate superior application performance across the hybrid enterprise. It monitors and stores a record of every end-to-end transaction along with its associated system metrics and call trees including parameters, URLs, user information, and remote calls. This ‘big data’ based approach allows IT to quickly and easily reconstruct incidents in great detail, measure impact, and identify and eliminate root causes before users notice. IT is rarely more than two clicks away from an answer when performance issues begin to appear.
SteelCentral AppInternals does not limit IT to preset workflows that encourage fixing problems after major slowdowns or outages. With SteelCentral AppInternals 10, IT can discover anomalies, measure business impact, plan for capacity, and continuously improve performance. On demand analytics, using simple “and”/“or” queries promotes proactive performance improvement and avoids reactive firefighting.
SteelCentral AppInternals 10 integrates with Riverbed SteelCentral Portal, which provides end-to-end performance visibility and analytics across end-users, applications, networks, and infrastructure. This combination provides a complete picture and changes the way IT domain teams work together to resolve performance issues.
“With the launch of the completely redesigned SteelCentral AppInternals 10, along with the recent release of the all new SteelCentral Portal, we are delivering the richest, most comprehensive visibility and diagnostic capabilities to manage application performance across today’s hybrid enterprise,” said Mike Sargent, SVP and GM of SteelCentral at Riverbed. “We’re also breaking the ease-of-use barrier — eliminating the need for a Ph.D. in APM to diagnose issues that quickly impact the business. AppInternals’ combination of comprehensive analytics and ease-of-use is unmatched by any other vendor. Furthermore, through the integration between AppInternals and SteelCentral Portal, we are extending visibility beyond the app into the network to deliver a complete picture of performance. This will fundamentally change the way teams collaborate to address performance issues going forward.”
The Latest
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 ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.