Dynatrace launched Dynatrace OneAgent Operator, a set of specialized processes that run on each monitored host to collect business and performance metrics.
As one of the first Red Hat partners to integrate the Operator Framework SDK into its platform, platform administrators will be able to automate the management, updates, and roll-out of its OneAgent in their Red Hat OpenShift Container Platform environments.
By leveraging Dynatrace OneAgent, customers will be able to automatically control the roll out of OneAgent to specific nodes, deploy it on tainted nodes and perform upgrades as soon as soon as they’re available.
Red Hat’s Operator Framework is an open source project that provides developer and runtime Kubernetes tools, accelerating development of an Operator – a method of packaging, deploying and managing a Kubernetes application. With this announcement, Dynatrace joins Red Hat and its partners, to enable automated management of Red Hat OpenShift.
“The Dynatrace OneAgent automates the monitoring of highly-scalable applications for our customers’ unique application stacks, regardless of the services and processes that are running,” said Franz Karlsberger, Global Head of Strategic Technology Alliances and Ecosystems, Dynatrace. "By automating the tasks involved in keeping Dynatrace OneAgent at its peak performance, we’re taking another step toward our vision of fully autonomous IT.”
“With the power of Kubernetes Operators, ISVs within the Red Hat ecosystem, like Dynatrace – which is specifically purpose-built for cloud monitoring – can automate their services at scale in a Red Hat OpenShift environment,” said Chris Morgan, Global Technical Director, OpenShift Ecosystem, Red Hat. “Operators are designed to enable OpenShift to not only be a priority deployment target for ISV solutions, but a catalyst to empower those solutions to operate on OpenShift as they would on the public cloud in terms of maintainability, flexibility, and upgradeability.”
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 ...