
SL Corporation significantly expands the connectivity and usability of its leading end-to-end application monitoring and data visualization platform, RTView Enterprise Monitor 1.5, with new TIBCO and Oracle solutions and end user customization tools.
RTView Enterprise Monitor is an easy-to-use, easy-to-implement application monitoring solution designed to provide an end-to-end view of the health state for your most business-critical applications and the software and hardware that support them, including middleware, database, virtual machines, host and network.
“SL is committed to delivering a robust application monitoring environment for mission-critical applications” says Tom Lubinski, founder and CEO of SL Corporation. “We work very closely with our customers to ensure that we can meet their requirements with new features and solutions packages for their most important infrastructure components.”
RTView Enterprise Monitor 1.5 includes new solution packages, agents, connectors, and end user tools enabling greater visibility into the extended application and supporting infrastructure.
- TIBCO ActiveMatrix Solution Package offers deeper integration into the TIBCO stack. Complementary to existing TIBCO BusinessWorks and TIBCO EMS solution packages, the ActiveMatrix Monitor automatically correlates applications and services to supporting TIBCO and non-TIBCO infrastructure components for unparalleled visibility into the aggregated health and stability of TIBCO ActiveMatrix applications and services.
- UX Monitor Solution Package provides visibility into the performance of application user interfaces to monitor response times between the front-end and back-end systems so that you can ensure optimum user experience.
- RTView Host Agent allows users to monitor the compute resources on any physical host including CPU, Memory, Network and storage.
- Oracle Enterprise Manager Connector allows RTView Enterprise Monitor to connect to existing deployments of Oracle Enterprise Manager (OEM) and collect performance data for databases and hosts (physical servers) that have been designated as OEM targets.
- Metric Explorer is a new Web-based tool that empowers users to create their own customized view of available metrics, without requiring the more sophisticated tools required by deployers and managers. Now users can self-service their data requirements faster than ever resulting in greater adoption and faster turnaround times.
SL Corporation continues to innovate and bring comprehensive, end-to-end application monitoring tools to market to help support teams monitor system health, minimize downtime, and maximize performance. You can expect to see a lot more innovative offerings from SL Corporate over the next year.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...