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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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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...