Red Hat announced several enhancements to Red Hat Insights, its predictive analytics offering, including integrations for ServiceNow and Slack, as well as expanded monitoring capabilities to identify known threats in Red Hat OpenShift and Red Hat Enterprise Linux.
With the convenience of bringing Insights’ analytics directly into ticketing and workflow systems, customers can use the tools they are already familiar with while more easily adopting analytics into their existing operations. In addition, enhanced threat visibility in foundational technologies such as Red Hat OpenShift and Red Hat Enterprise Linux enables customers to reduce risks in their hybrid cloud operating environments for a more secure IT framework.
Insights provides unified visibility across platforms and services, enabling teams to manage holistically. Bringing Insights directly to service providers like Splunk this summer and now ServiceNow and Slack simplifies the procurement of a validated solution, while integrating Insights into the services that customers already use provides seamless access to results. Bespoke integrations help organizations proactively remediate a variety of potential software security and configuration issues by more quickly putting these alerts in front of decision makers, encouraging remediations before there’s downtime, a cluster failure or a failed upgrade. By extending Insights to service providers, Red Hat aims to reduce friction across IT and business organizations responsible for supporting the systems needed to run the business today while also building the services and applications to fuel growth tomorrow.
In addition to streamlining management across service providers, Red Hat is also enhancing capabilities to better manage and track vulnerabilities in Red Hat OpenShift. Insights’ vulnerability capabilities for Red Hat OpenShift provides a list of OpenShift clusters that are affected by unaddressed Common Vulnerabilities and Exposures (CVEs), enabling triaging and prioritization of critical issues. The service helps keep systems up-and-running, complementing Red Hat’s existing hybrid cloud security portfolio while helping OpenShift users get the most out of their Red Hat subscription.
Red Hat is providing more visibility into potentially active malware running on systems. The Insights malware detection service monitors and assesses Red Hat Enterprise Linux systems for the presence of malware, utilizing over 175 signatures of known Linux malware provided in collaboration with the IBM X-Force Threat Intelligence team. Users can access the list of signatures scanned against their Red Hat Enterprise Linux systems with analysis reports, and view results for individual system scans and aggregated results for all of their Red Hat Enterprise Linux systems. The addition of malware detection enables a multi-layered security approach to further drive infrastructure security and limit potential threats in their operating system.
The ServiceNow integration is available in the ServiceNow Store; the Slack integration is available within Red Hat Insights. The vulnerability capabilities for Red Hat OpenShift and malware for Red Hat Enterprise Linux are both included in Red Hat subscriptions.
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.