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HP Unveils New IT Operations Management Solutions Built Around Big Data Analytics

HP unveiled a full range of new IT Operations Management solutions built around big data analytics. These solutions are designed to help organizations automate and optimize their applications and infrastructure technology, resulting in exceptional customer experiences, faster time to market, and greater cost efficiencies.

The new HP solutions leverage HP Haven’s unique analytic assets, HP IDOL and HP Vertica, to connect to and understand vast troves of business data, machine data, and unstructured human information. By analyzing and acting on this data together, organizations can align their IT operations to business and customer demands, in real-time.

Businesses today must adapt to serve customers who expect a seamless, personalized, and enjoyable experience across a company’s mobile, web, device applications, and physical properties. To keep pace, organizations have embraced new computing models, such as cloud, and new development approaches, like agile and DevOps. These changes have introduced more change, more complexity, more security risks, and more opportunities for failure across an organizations’ enterprise IT landscape.

The new HP IT Operations Management software suite is based on the premise that the solution to these challenges resides in the data. When harnessed in a connected, intelligent manner, businesses can automate the rollout of new applications at high velocity, predict system outages before they occur, manage deployments in a secure and compliant way, and even gauge customer response and experience for applications in real-time.

The HP IT Operations Management suite leverages this ‘Connected Intelligence’ from HP Haven to transform IT operations, and includes several new and updated solutions:

- HP AppPulse Mobile – this innovative tool allows businesses to instrument, monitor, and analyze user experiences on mobile apps. A SaaS offering that measures Android and iOs apps, this tool uses HP Vertica real-time analytics to deliver recommendations and a “FunDex” that is designed to help developers score perfect 5 star ratings on their mobile apps.

- HP Codar – a brand new offering from HP, Codar allows DevOps teams to easily and efficiently move applications from development into pre-production and full production. HP Codar also integrates with many well-known provisioning engines, including Chef, Puppet, and HP Cloud Service Automation.

- HP Operations Analytics – this powerful solution leverages HP Vertica real-time analytics to predict outages and identify root causes of issues across the full application stack and throughout the data center. By running all data through HP Operations Analytics, including log files, machine and business data, global IT organizations can identify and correct potential business issues before they occur.

- HP Propel – this module serves as “the front door to IT” by dramatically simplifying the process for procuring and setting up IT services for employees. HP Propel allows multiple internal IT suppliers to easily integrate, including service desks, cloud provisioning, equipment ordering, and online back office services, and leverages contextual information and sentiment designed to ensure users receive the best possible customer experience.

- HP Service Anywhere – this SaaS based solution leverages HP Haven analytics to provide powerful tools like hot topics analysis and change analytics. These capabilities help service desk employees predict where issues are arising before they become critical and gives consumers an engaging, self-sufficient service experience. HP IDOL monitors and clusters emerging sentiment among users, and HP Vertica tracks machine and log data providing a complete view of operational performance

“HP is powering a new breed of enlightened enterprises that are applying big data analytics, automation, and connected intelligence to create and deliver IT at high speed and with precision, delighting internal stakeholders and external customers alike,” said Ajay Singh, SVP and GM, IT Operations Management, at HP. “No other provider possesses the deep analytic assets, full and connected portfolio, and proven track record for helping businesses drive such IT transformations.”

The HP IT Operations Management software solutions listed in this news advisory are generally available now.

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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 ...

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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 ...

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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.

HP Unveils New IT Operations Management Solutions Built Around Big Data Analytics

HP unveiled a full range of new IT Operations Management solutions built around big data analytics. These solutions are designed to help organizations automate and optimize their applications and infrastructure technology, resulting in exceptional customer experiences, faster time to market, and greater cost efficiencies.

The new HP solutions leverage HP Haven’s unique analytic assets, HP IDOL and HP Vertica, to connect to and understand vast troves of business data, machine data, and unstructured human information. By analyzing and acting on this data together, organizations can align their IT operations to business and customer demands, in real-time.

Businesses today must adapt to serve customers who expect a seamless, personalized, and enjoyable experience across a company’s mobile, web, device applications, and physical properties. To keep pace, organizations have embraced new computing models, such as cloud, and new development approaches, like agile and DevOps. These changes have introduced more change, more complexity, more security risks, and more opportunities for failure across an organizations’ enterprise IT landscape.

The new HP IT Operations Management software suite is based on the premise that the solution to these challenges resides in the data. When harnessed in a connected, intelligent manner, businesses can automate the rollout of new applications at high velocity, predict system outages before they occur, manage deployments in a secure and compliant way, and even gauge customer response and experience for applications in real-time.

The HP IT Operations Management suite leverages this ‘Connected Intelligence’ from HP Haven to transform IT operations, and includes several new and updated solutions:

- HP AppPulse Mobile – this innovative tool allows businesses to instrument, monitor, and analyze user experiences on mobile apps. A SaaS offering that measures Android and iOs apps, this tool uses HP Vertica real-time analytics to deliver recommendations and a “FunDex” that is designed to help developers score perfect 5 star ratings on their mobile apps.

- HP Codar – a brand new offering from HP, Codar allows DevOps teams to easily and efficiently move applications from development into pre-production and full production. HP Codar also integrates with many well-known provisioning engines, including Chef, Puppet, and HP Cloud Service Automation.

- HP Operations Analytics – this powerful solution leverages HP Vertica real-time analytics to predict outages and identify root causes of issues across the full application stack and throughout the data center. By running all data through HP Operations Analytics, including log files, machine and business data, global IT organizations can identify and correct potential business issues before they occur.

- HP Propel – this module serves as “the front door to IT” by dramatically simplifying the process for procuring and setting up IT services for employees. HP Propel allows multiple internal IT suppliers to easily integrate, including service desks, cloud provisioning, equipment ordering, and online back office services, and leverages contextual information and sentiment designed to ensure users receive the best possible customer experience.

- HP Service Anywhere – this SaaS based solution leverages HP Haven analytics to provide powerful tools like hot topics analysis and change analytics. These capabilities help service desk employees predict where issues are arising before they become critical and gives consumers an engaging, self-sufficient service experience. HP IDOL monitors and clusters emerging sentiment among users, and HP Vertica tracks machine and log data providing a complete view of operational performance

“HP is powering a new breed of enlightened enterprises that are applying big data analytics, automation, and connected intelligence to create and deliver IT at high speed and with precision, delighting internal stakeholders and external customers alike,” said Ajay Singh, SVP and GM, IT Operations Management, at HP. “No other provider possesses the deep analytic assets, full and connected portfolio, and proven track record for helping businesses drive such IT transformations.”

The HP IT Operations Management software solutions listed in this news advisory are generally available now.

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.