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ExtraHop Partners with Sumo Logic

ExtraHop and Sumo Logic announced a partnership that combines wire data from ExtraHop with Sumo Logic’s scalable machine data analytics platform for insight into enterprise IT infrastructure.

The technology partnership leverages ExtraHop’s Open Data Stream to provide a single, unified view of wire data and machine data within the Sumo Logic cloud analytics service, delivering deep, rich, correlated visibility across all tiers of IT infrastructure. Armed with contextual insights from multiple data sources, enterprise IT teams are empowered to address service issues and security threats quickly and effectively.

The ExtraHop and Sumo Logic integration enables users to send precise, policy-driven events and metrics from the ExtraHop platform to the Sumo Logic platform in real-time via Open Data Stream for multidimensional analysis and correlation with other machine data sources. By coupling wire data from ExtraHop with Sumo Logic’s insight into the IT infrastructure that underlies enterprise applications, IT teams have the visibility they need to investigate and remediate issues affecting performance, availability, and security across infrastructure. Purpose-built for web-scale enterprises, Sumo Logics’s cloud-first platform ingests more than 14 trillion logs daily and dynamically scales as business needs evolve.

With ExtraHop and Sumo Logic, enterprise IT teams can achieve the following:

- Easily determine the slowest stored procedures for applications

- Identify misconfigured DNS servers that are returning errors

- Surface potential security threats by cross-referencing wire data and enterprise application data

- Pinpoint Citrix XenApp servers responsible for slow application launch times along with the users affected and the cause

- Detect anomalies through Sumo Logic and then explore contextual communications in ExtraHop

- Simplify IT operations across the board with best-in-class analytics solutions that are easy to deploy and maintain

“Adding ExtraHop data as a new source into the Sumo Logic service for proactive analysis against other feeds enables IT teams to gain deeper performance, security, and business insights from across IT infrastructure,” said Mark Musselman, Vice President, Strategic Alliances at Sumo Logic. “Sumo Logic’s cloud-native architecture means the service serves as an aggregation point for diverse data sources. The result is an IT team that acts on timely information from within their infrastructure—even information they did not know to ask for. A critical piece to the puzzle lies in Sumo Logic’s Anomaly Detection, a proprietary capability that delivers insight from patterns in data and insights beyond what IT teams themselves know to query.”

“As IT Operations Analytics emerges as an important framework for IT intelligence and business operations, the ability to integrate, analyze, correlate, and view different data sets, especially at scale, is becoming increasingly critical,” said Erik Giesa, senior vice president of Worldwide Marketing and Business Development at ExtraHop. “The partnership between ExtraHop and Sumo Logic is an important example of the insight value, lower costs, and simplicity that can be derived from this type of integration. Analytics performed on both wire and machine data sources offers not only crucial insight into the performance, availability, and security of IT environments, but into important business performance metrics.”

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ExtraHop Partners with Sumo Logic

ExtraHop and Sumo Logic announced a partnership that combines wire data from ExtraHop with Sumo Logic’s scalable machine data analytics platform for insight into enterprise IT infrastructure.

The technology partnership leverages ExtraHop’s Open Data Stream to provide a single, unified view of wire data and machine data within the Sumo Logic cloud analytics service, delivering deep, rich, correlated visibility across all tiers of IT infrastructure. Armed with contextual insights from multiple data sources, enterprise IT teams are empowered to address service issues and security threats quickly and effectively.

The ExtraHop and Sumo Logic integration enables users to send precise, policy-driven events and metrics from the ExtraHop platform to the Sumo Logic platform in real-time via Open Data Stream for multidimensional analysis and correlation with other machine data sources. By coupling wire data from ExtraHop with Sumo Logic’s insight into the IT infrastructure that underlies enterprise applications, IT teams have the visibility they need to investigate and remediate issues affecting performance, availability, and security across infrastructure. Purpose-built for web-scale enterprises, Sumo Logics’s cloud-first platform ingests more than 14 trillion logs daily and dynamically scales as business needs evolve.

With ExtraHop and Sumo Logic, enterprise IT teams can achieve the following:

- Easily determine the slowest stored procedures for applications

- Identify misconfigured DNS servers that are returning errors

- Surface potential security threats by cross-referencing wire data and enterprise application data

- Pinpoint Citrix XenApp servers responsible for slow application launch times along with the users affected and the cause

- Detect anomalies through Sumo Logic and then explore contextual communications in ExtraHop

- Simplify IT operations across the board with best-in-class analytics solutions that are easy to deploy and maintain

“Adding ExtraHop data as a new source into the Sumo Logic service for proactive analysis against other feeds enables IT teams to gain deeper performance, security, and business insights from across IT infrastructure,” said Mark Musselman, Vice President, Strategic Alliances at Sumo Logic. “Sumo Logic’s cloud-native architecture means the service serves as an aggregation point for diverse data sources. The result is an IT team that acts on timely information from within their infrastructure—even information they did not know to ask for. A critical piece to the puzzle lies in Sumo Logic’s Anomaly Detection, a proprietary capability that delivers insight from patterns in data and insights beyond what IT teams themselves know to query.”

“As IT Operations Analytics emerges as an important framework for IT intelligence and business operations, the ability to integrate, analyze, correlate, and view different data sets, especially at scale, is becoming increasingly critical,” said Erik Giesa, senior vice president of Worldwide Marketing and Business Development at ExtraHop. “The partnership between ExtraHop and Sumo Logic is an important example of the insight value, lower costs, and simplicity that can be derived from this type of integration. Analytics performed on both wire and machine data sources offers not only crucial insight into the performance, availability, and security of IT environments, but into important business performance metrics.”

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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 ...

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.