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Four New SevOne xStats Adapters Introduced

SevOne announced four new SevOne xStats Adapters for use with Amazon Web Services (AWS), Intelligent Platform Management Interface (IPMI), Arista EO and AppNeta PathView.

SevOne xStats technology incorporates any third-party time-stamped data into the SevOne Performance Monitoring Cluster; that data can be automatically correlated with other metric, flow and log data at scale. With the latest xStats Adapters, SevOne further differentiates itself from other approaches in the market by extending datacenter monitoring with visibility into hybrid-cloud environments and with integrated end-user experience data.

“Today’s hybrid reality means a company’s applications and data are spread across multiple vendors’ environments. While operations teams may not control all the platforms they run on, they still need to monitor the performance of these assets to help the organization meet business, compliance and regulatory needs,” said Jack Sweeney, CEO at SevOne. “SevOne continues to address these challenges with our newest SevOne xStats Adapters, allowing you to see the performance of your entire digital infrastructure—no matter where it is—in a single dashboard.”

Capabilities and features in each adapter include:

AWS — In AWS-based deployments, operations teams have access to the operating systems and applications deployed in the cloud, but have limited visibility when it comes to the underlying compute, network and storage infrastructure needed to gather performance statistics. To help its customers monitor their infrastructure from the datacenter to the hybrid cloud, SevOne offers the SevOne xStats Adapter for use with AWS. This adapter is designed to collect the following metrics from AWS-based environments, including:
- AWS EBS Volume Details
- System Integrity and Failures
- Disk Read/Write Operations
- Network I/O
- CPU Utilization
- Credit Balance/Usage and Estimated Charges for Current Billing Cycle

AppNeta PathView — Understanding how well users are experiencing an infrastructure, whether that service is hosted in a private cloud, IaaS, PaaS or SaaS, is a critical component of a performance monitoring strategy. AppNeta PathView actively tests entire network paths, collecting in-depth end-user experience data across enterprise, cloud and service provider infrastructures. To help monitor end-user experience and correlate it with performance metric, flow and log data, SevOne offers the SevOne xStats Adapter for use with AppNeta PathView. This adapter integrates with AppNeta APIs to enable users to create SevOne dashboards with end-user experience data.

IPMI — Monitoring today's modern datacenters requires a rich understanding of data center infrastructure, spanning network, compute, storage and environmental resources, including a detailed knowledge of per CPU power, temperature, voltage and current utilization. The SevOne xStats™ Adapter for use with IPMI supports more than 200 computer systems vendors, including Cisco, Dell, HP, Intel and NEC. This adapter integrates via the open interfaces of IPMI v1.5 and v2.0 to enable users to create SevOne dashboards with critical environmental and operational metrics from across their compute infrastructure.

Arista EOS — As enterprise and service provider teams move toward more and more virtualized network infrastructure to meet their scalability needs, the methods to gather network performance, CPU, power, temperature and other infrastructure performance data is evolving beyond polling SNMP-based MIBs. To help monitor an Arista EOS-based infrastructure and correlate it with performance metric, flow and log data, SevOne offers the SevOne xStats Adapter for use with Arista EOS. This adapter integrates with the Arista eAPI to enable users to visualize the performance of their Arista EOS-based infrastructure from a single SevOne dashboard.

Along with the latest SevOne xStats Adapters, SevOne has delivered dozens of xStats adapters for customers. SevOne xStats Adapters enable customers to include metrics from any third-party source that provide management functions for components throughout the digital infrastructure, such as network probes, proprietary business applications and element management systems from network equipment vendors.

SevOne offers a number of ways to incorporate third-party data, processing that information with the same analytics applied to out-of-the-box data sources. For custom data sources, just like standard sources, SevOne will automatically establish baselines of normal performance, generate alerts when actual performance deviates from those baselines and feed the data into reporting analytics.

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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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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 ...

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Four New SevOne xStats Adapters Introduced

SevOne announced four new SevOne xStats Adapters for use with Amazon Web Services (AWS), Intelligent Platform Management Interface (IPMI), Arista EO and AppNeta PathView.

SevOne xStats technology incorporates any third-party time-stamped data into the SevOne Performance Monitoring Cluster; that data can be automatically correlated with other metric, flow and log data at scale. With the latest xStats Adapters, SevOne further differentiates itself from other approaches in the market by extending datacenter monitoring with visibility into hybrid-cloud environments and with integrated end-user experience data.

“Today’s hybrid reality means a company’s applications and data are spread across multiple vendors’ environments. While operations teams may not control all the platforms they run on, they still need to monitor the performance of these assets to help the organization meet business, compliance and regulatory needs,” said Jack Sweeney, CEO at SevOne. “SevOne continues to address these challenges with our newest SevOne xStats Adapters, allowing you to see the performance of your entire digital infrastructure—no matter where it is—in a single dashboard.”

Capabilities and features in each adapter include:

AWS — In AWS-based deployments, operations teams have access to the operating systems and applications deployed in the cloud, but have limited visibility when it comes to the underlying compute, network and storage infrastructure needed to gather performance statistics. To help its customers monitor their infrastructure from the datacenter to the hybrid cloud, SevOne offers the SevOne xStats Adapter for use with AWS. This adapter is designed to collect the following metrics from AWS-based environments, including:
- AWS EBS Volume Details
- System Integrity and Failures
- Disk Read/Write Operations
- Network I/O
- CPU Utilization
- Credit Balance/Usage and Estimated Charges for Current Billing Cycle

AppNeta PathView — Understanding how well users are experiencing an infrastructure, whether that service is hosted in a private cloud, IaaS, PaaS or SaaS, is a critical component of a performance monitoring strategy. AppNeta PathView actively tests entire network paths, collecting in-depth end-user experience data across enterprise, cloud and service provider infrastructures. To help monitor end-user experience and correlate it with performance metric, flow and log data, SevOne offers the SevOne xStats Adapter for use with AppNeta PathView. This adapter integrates with AppNeta APIs to enable users to create SevOne dashboards with end-user experience data.

IPMI — Monitoring today's modern datacenters requires a rich understanding of data center infrastructure, spanning network, compute, storage and environmental resources, including a detailed knowledge of per CPU power, temperature, voltage and current utilization. The SevOne xStats™ Adapter for use with IPMI supports more than 200 computer systems vendors, including Cisco, Dell, HP, Intel and NEC. This adapter integrates via the open interfaces of IPMI v1.5 and v2.0 to enable users to create SevOne dashboards with critical environmental and operational metrics from across their compute infrastructure.

Arista EOS — As enterprise and service provider teams move toward more and more virtualized network infrastructure to meet their scalability needs, the methods to gather network performance, CPU, power, temperature and other infrastructure performance data is evolving beyond polling SNMP-based MIBs. To help monitor an Arista EOS-based infrastructure and correlate it with performance metric, flow and log data, SevOne offers the SevOne xStats Adapter for use with Arista EOS. This adapter integrates with the Arista eAPI to enable users to visualize the performance of their Arista EOS-based infrastructure from a single SevOne dashboard.

Along with the latest SevOne xStats Adapters, SevOne has delivered dozens of xStats adapters for customers. SevOne xStats Adapters enable customers to include metrics from any third-party source that provide management functions for components throughout the digital infrastructure, such as network probes, proprietary business applications and element management systems from network equipment vendors.

SevOne offers a number of ways to incorporate third-party data, processing that information with the same analytics applied to out-of-the-box data sources. For custom data sources, just like standard sources, SevOne will automatically establish baselines of normal performance, generate alerts when actual performance deviates from those baselines and feed the data into reporting analytics.

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.