Hewlett Packard Enterprise (HPE) has entered into a definitive agreement to acquire OpsRamp, an IT operations management (ITOM) company that monitors, observes, automates and manages IT infrastructure, cloud resources, workloads and applications for hybrid and multi-cloud environments, including the leading hyperscalers.
Integrating OpsRamp’s hybrid digital operations management solution with the HPE GreenLake edge-to-cloud platform – and supporting it with HPE services – will reduce the operational complexity of multi-vendor and multi-cloud IT environments that are in the public cloud, colocations, and on-premises. OpsRamp’s technology – which delivers discovery, monitoring, automation, and event resolution with artificial intelligence for IT operations (AIOps) – provides end-to-end visibility, observability, and control across hybrid and multi-cloud IT environments. These capabilities span multi-vendor computing, networking, and storage, along with cloud resources, containers, virtual machines, and applications.
“Customers today are managing several different cloud environments, with different IT operational models and tools, which dramatically increases the cost and complexity of digital operations management,” said Fidelma Russo, Chief Technology Officer of Hewlett Packard Enterprise. “The combination of OpsRamp and HPE will remove these barriers by providing customers with an integrated edge-to-cloud platform that can more effectively manage and transform multi-vendor and multi-cloud IT estates. This acquisition advances HPE hybrid cloud leadership and expands the reach of the HPE GreenLake platform into IT Operations Management."
HPE GreenLake platform provides customers and partners with a unified hybrid cloud experience and easy access to cloud services. With the addition of OpsRamp’s services, new and existing HPE customers facing increasingly complex multi-vendor IT systems and workloads will be able to more efficiently manage IT investments and remediate incidents faster. Organizations benefit from one platform from which to automate, orchestrate, and operate their hybrid cloud estate.
The OpsRamp capabilities extend the HPE services portfolio – across Advisory, Operational and HPE GreenLake managed services – into delivering end-to-end support for hybrid and multi-cloud IT environments. With this offering, customers can more effectively manage their heterogeneous cloud environments, dramatically reduce their operating expenses and enhance the overall IT experience for users. Capabilities include the consolidation of multi-vendor tools; automating and streamlining manual processes with AIOps; and significantly improving incident remediation with monitoring and observability.
Headquartered in San Jose, California, OpsRamp was part of Hewlett Packard Pathfinder’s venture capital investment in 2020. OpsRamp delivers a hybrid digital operations management platform that supports thousands of customers worldwide to modernize and reduce the cost of their digital operations management.
“The integration of OpsRamp’s hybrid digital operations management solution with the HPE GreenLake platform will provide an unmatched offering for organizations seeking to innovate and thrive in a complex, multi-cloud world. Partners and the channel will also play a pivotal role to advance their as-a-service offerings, as enterprises look for a unified approach to better manage their operations from the edge to the cloud,” said Varma Kunaparaju, CEO of OpsRamp. “We look forward to leveraging the scale and reach of HPE’s global go-to-market engine to deliver our unique offering and are excited for this journey ahead as part of HPE.”
The transaction is expected to close in the third quarter of the HPE 2023 fiscal year, subject to regulatory approvals and other customary closing conditions. OpsRamp’s technology will be integrated with HPE GreenLake platform, available standalone as-a-service, and embedded within HPE’s compute, storage, and networking solutions.
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.