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OpsCruise Observability Platform Certified on Red Hat Openshift

OpsCruise's Kubernetes and Cloud Service observability platform is certified to run on the Red Hat OpenShift Kubernetes platform.

This further supports the company’s observability platform in enabling organizations with enhanced performance while optimizing use of resources and cost.

Red Hat OpenShift is a cloud-native application platform that can help enterprise organizations build a more stable, security-focused Kubernetes environment with extended security and development workflow capabilities.

With OpsCruise running on Red Hat OpenShift, organizations can gain deeper visibility into every layer of their Red Hat OpenShift environments in order to reduce troubleshooting time and more confidently resolve performance issues. OpsCruise is an open cloud-native observability platform that enables Ops and App teams to troubleshoot all of their application components in context with configurations, connections, metrics, logs, traces and changes.

Beyond traditional telemetry, OpsCruise adds a unique eBPF-based flow feature that builds real-time topology, and a novel TracePath technology that makes distributed tracing usable by infrastructure and operations teams. By bringing everything into one place, app teams do not have to swivel across multiple tools from CI/CD, Kubectl tools and monitoring tools to understand and analyze the state of their applications.

In addition, to address temporal blindspots such as those from auto-scaling, OpsCruise provides a time travel feature that retains snapshots of the past so DevOps can look back in time to visualize changes that are often the source of problems.

“Red Hat OpenShift is supported by a robust partner ecosystem, extending the power of cloud-native application development and open source innovation across the hybrid cloud. With the OpsCruise observability platform certified to run on Red Hat OpenShift, customers can experience added security capabilities to further bolster their Kubernetes workflows and achieve real business results,” said Mark Longwell, director, Hybrid Platforms Business Unit, Red Hat.

OpsCruise on Red Hat OpenShift can be installed on-premises and in the cloud with Azure Red Hat OpenShift or Red Hat OpenShift Service on AWS. OpsCruise supports all of these options, so customers can now leverage OpsCruise observability anywhere they use Red Hat OpenShift. With instantaneous full-stack visibility and ability to detect and isolate problems with OpsCruise, DevOps teams can now more quickly identify sources of problems such as application SLO breaches caused by hard to find long chain dependencies on a failed service resulting from an incorrect Kubernetes configuration.

“Like Red Hat, OpsCruise has many large complex enterprise customers, so certifying our observability platform on Red Hat OpenShift was a no-brainer, " said Scott Fulton, Co-Founder & CEO of OpsCruise. “We look forward to continued collaboration with Red Hat to serve customers together.”

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OpsCruise Observability Platform Certified on Red Hat Openshift

OpsCruise's Kubernetes and Cloud Service observability platform is certified to run on the Red Hat OpenShift Kubernetes platform.

This further supports the company’s observability platform in enabling organizations with enhanced performance while optimizing use of resources and cost.

Red Hat OpenShift is a cloud-native application platform that can help enterprise organizations build a more stable, security-focused Kubernetes environment with extended security and development workflow capabilities.

With OpsCruise running on Red Hat OpenShift, organizations can gain deeper visibility into every layer of their Red Hat OpenShift environments in order to reduce troubleshooting time and more confidently resolve performance issues. OpsCruise is an open cloud-native observability platform that enables Ops and App teams to troubleshoot all of their application components in context with configurations, connections, metrics, logs, traces and changes.

Beyond traditional telemetry, OpsCruise adds a unique eBPF-based flow feature that builds real-time topology, and a novel TracePath technology that makes distributed tracing usable by infrastructure and operations teams. By bringing everything into one place, app teams do not have to swivel across multiple tools from CI/CD, Kubectl tools and monitoring tools to understand and analyze the state of their applications.

In addition, to address temporal blindspots such as those from auto-scaling, OpsCruise provides a time travel feature that retains snapshots of the past so DevOps can look back in time to visualize changes that are often the source of problems.

“Red Hat OpenShift is supported by a robust partner ecosystem, extending the power of cloud-native application development and open source innovation across the hybrid cloud. With the OpsCruise observability platform certified to run on Red Hat OpenShift, customers can experience added security capabilities to further bolster their Kubernetes workflows and achieve real business results,” said Mark Longwell, director, Hybrid Platforms Business Unit, Red Hat.

OpsCruise on Red Hat OpenShift can be installed on-premises and in the cloud with Azure Red Hat OpenShift or Red Hat OpenShift Service on AWS. OpsCruise supports all of these options, so customers can now leverage OpsCruise observability anywhere they use Red Hat OpenShift. With instantaneous full-stack visibility and ability to detect and isolate problems with OpsCruise, DevOps teams can now more quickly identify sources of problems such as application SLO breaches caused by hard to find long chain dependencies on a failed service resulting from an incorrect Kubernetes configuration.

“Like Red Hat, OpsCruise has many large complex enterprise customers, so certifying our observability platform on Red Hat OpenShift was a no-brainer, " said Scott Fulton, Co-Founder & CEO of OpsCruise. “We look forward to continued collaboration with Red Hat to serve customers together.”

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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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...