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Splunk Launches New Observability Cloud

Splunk announced the new Splunk Observability Cloud, the full-stack, analytics-powered and enterprise-grade Observability solution.

With the Splunk Observability Cloud, IT and DevOps teams can get all their answers in a unified interface with metrics, traces and logs - all data collected in real-time, without sampling and at any scale.

“With the shift to cloud, IT and DevOps teams are now wrestling with more operational complexity that is compounded by too many existing monitoring tools that have blind spots, siloed data and disjointed workflows,” said Sendur Sellakumar, CPO, Splunk. “The Splunk Observability Cloud helps IT and DevOps teams conquer complexity and accelerate cloud transformation for their organizations.”

The Splunk Observability Cloud brings together the world’s best-in-class solutions for infrastructure monitoring, application performance management, real user monitoring, synthetic monitoring, log investigation and incident response. Splunk Log Observer, Splunk Real User Monitoring (RUM), and the new Splunk Synthetic Monitoring - products that give IT and DevOps teams unmatched, end-to-end visibility, are now generally available.

The full Splunk Observability Cloud includes Splunk Infrastructure Monitoring, Splunk APM, Splunk RUM, Splunk Synthetic Monitoring, Splunk Log Observer, and Splunk On-Call. Backed by Splunk’s - NoSample full-fidelity data ingestion, real-time streaming analytics and massive scalability, Splunk Observability Cloud delivers unprecedented capabilities for monitoring, troubleshooting and resolution of business-critical incidents.

Built for DevOps users and use cases, Splunk Log Observer brings the power of Splunk logging to SREs, DevOps engineers and developers that need a troubleshooting-oriented logging experience. Splunk RUM provides the fastest troubleshooting and most comprehensive view of web browser performance. Together, Splunk APM and Splunk RUM provide end-to-end full-fidelity visibility across the entire user transaction. Splunk Synthetic Monitoring is a new solution powered by the technology from the acquisition of Rigor, and is now integrated across most Splunk products. This synthetic monitoring solution improves uptime and performance of APIs, service endpoints, business transactions, and user flows.

“Until now, the tools that IT and DevOps teams rely on to monitor and manage applications and infrastructure have been disconnected, often separated into two or three different platforms,” said Spiros Xanthos, VP of Product Management, Observability and IT Operations, Splunk. “The Splunk Observability Cloud brings all the needed Observability solutions together in a unified interface designed to help customers gain a comprehensive view across all their data and operate at enterprise scale.”

The Splunk Observability Cloud is optimized and designed to consume and manage OpenTelemetry data at scale enabling customers to unlock their data through open source standards. Splunk Observability Cloud is OpenTelemetry-native allowing customers to unify data ingestion without vendor lock-in and reduce resource consumption with the lightweight, open-source OpenTelemetry instrumentation.

As data volume and organizational complexities increase, Splunk wants to keep pricing simple and this bundle is designed to do that. With the new Splunk Observability Cloud, Splunk is integrating these capabilities under one clear host-based pricing metric directly tied to the value IT and DevOps teams may gain.

In addition to the Splunk Observability Cloud, Splunk has created cloud technology bundles specific to IT and Security teams.

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Splunk Launches New Observability Cloud

Splunk announced the new Splunk Observability Cloud, the full-stack, analytics-powered and enterprise-grade Observability solution.

With the Splunk Observability Cloud, IT and DevOps teams can get all their answers in a unified interface with metrics, traces and logs - all data collected in real-time, without sampling and at any scale.

“With the shift to cloud, IT and DevOps teams are now wrestling with more operational complexity that is compounded by too many existing monitoring tools that have blind spots, siloed data and disjointed workflows,” said Sendur Sellakumar, CPO, Splunk. “The Splunk Observability Cloud helps IT and DevOps teams conquer complexity and accelerate cloud transformation for their organizations.”

The Splunk Observability Cloud brings together the world’s best-in-class solutions for infrastructure monitoring, application performance management, real user monitoring, synthetic monitoring, log investigation and incident response. Splunk Log Observer, Splunk Real User Monitoring (RUM), and the new Splunk Synthetic Monitoring - products that give IT and DevOps teams unmatched, end-to-end visibility, are now generally available.

The full Splunk Observability Cloud includes Splunk Infrastructure Monitoring, Splunk APM, Splunk RUM, Splunk Synthetic Monitoring, Splunk Log Observer, and Splunk On-Call. Backed by Splunk’s - NoSample full-fidelity data ingestion, real-time streaming analytics and massive scalability, Splunk Observability Cloud delivers unprecedented capabilities for monitoring, troubleshooting and resolution of business-critical incidents.

Built for DevOps users and use cases, Splunk Log Observer brings the power of Splunk logging to SREs, DevOps engineers and developers that need a troubleshooting-oriented logging experience. Splunk RUM provides the fastest troubleshooting and most comprehensive view of web browser performance. Together, Splunk APM and Splunk RUM provide end-to-end full-fidelity visibility across the entire user transaction. Splunk Synthetic Monitoring is a new solution powered by the technology from the acquisition of Rigor, and is now integrated across most Splunk products. This synthetic monitoring solution improves uptime and performance of APIs, service endpoints, business transactions, and user flows.

“Until now, the tools that IT and DevOps teams rely on to monitor and manage applications and infrastructure have been disconnected, often separated into two or three different platforms,” said Spiros Xanthos, VP of Product Management, Observability and IT Operations, Splunk. “The Splunk Observability Cloud brings all the needed Observability solutions together in a unified interface designed to help customers gain a comprehensive view across all their data and operate at enterprise scale.”

The Splunk Observability Cloud is optimized and designed to consume and manage OpenTelemetry data at scale enabling customers to unlock their data through open source standards. Splunk Observability Cloud is OpenTelemetry-native allowing customers to unify data ingestion without vendor lock-in and reduce resource consumption with the lightweight, open-source OpenTelemetry instrumentation.

As data volume and organizational complexities increase, Splunk wants to keep pricing simple and this bundle is designed to do that. With the new Splunk Observability Cloud, Splunk is integrating these capabilities under one clear host-based pricing metric directly tied to the value IT and DevOps teams may gain.

In addition to the Splunk Observability Cloud, Splunk has created cloud technology bundles specific to IT and Security teams.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...