
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
Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...
Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...
When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...
If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...
Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...
AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...
Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...
Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...
Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...
In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...