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Splunk Launches Observability Suite

Splunk announced the Splunk Observability Suite, the most comprehensive and powerful combination of monitoring, investigation, and troubleshooting solutions designed to help organizations become cloud-ready and accelerate their digital transformation.

The Splunk Observability Suite brings together Splunk’s best-in-class solutions for infrastructure monitoring, application performance monitoring, digital experience monitoring, log investigation and incident response into a single, tightly integrated suite of products. It delivers a unified, consistent experience that leverages industry-leading no sample streaming, full-fidelity ingestion, and sophisticated machine learning capabilities to collect and correlate across all metric, trace and log data in real-time and at any scale. The Observability Suite is designed to help IT and DevOps teams maintain the highest levels of business performance, minimize downtime and deliver world-class digital experiences.

“At Splunk, we believe modern application environments and open, cloud-native technologies will help our customers unlock greater business insights,” said Karthik Rau, VP of Observability, Splunk. “The Splunk Observability Suite makes it easier for organizations to accelerate their cloud migration and application modernization initiatives, and helps them deliver world-class digital experiences better than ever before.”

At the annual user-conference, .conf20, Splunk also announced Splunk Log Observer and Splunk Real User Monitoring. Splunk Log Observer brings the power of Splunk logs to site reliability engineers, DevOps engineers and developers. Entirely cloud-based, it deploys within minutes and offers out-of-the-box integrations with popular cloud and messaging services for fast time-to-value, and provides a point-and-click search for rapid log exploration. As part of the Splunk Observability Suite, Splunk Log Observer works seamlessly with Splunk Infrastructure Monitoring and Splunk Application Monitoring (APM) for context-rich, unified monitoring, troubleshooting and investigation.

Splunk Real User Monitoring extends Splunk’s monitoring capabilities helping organizations understand and optimize the digital experiences and user journeys of their end customers. Splunk Real User Monitoring leverages the same capabilities of Splunk APM with OpenTelemetry-based data collection, NoSample™ full-fidelity data ingestion, real-time streaming architecture, and AI-driven analytics for directed troubleshooting.

Both Splunk Log Observer and Splunk Real User Monitoring are currently available in beta for customers, with general availability coming in the future.

The combination of Splunk Log Observer and Real User Monitoring with the rest of the Splunk Observability Suite that includes Splunk Infrastructure Monitoring, Splunk Application Performance Monitoring, and Splunk On-Call, gives DevOps teams unmatched, end-to-end visibility and pinpointed, early problem detection for their cloud applications, all through a seamless and unified user experience.

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Splunk Launches Observability Suite

Splunk announced the Splunk Observability Suite, the most comprehensive and powerful combination of monitoring, investigation, and troubleshooting solutions designed to help organizations become cloud-ready and accelerate their digital transformation.

The Splunk Observability Suite brings together Splunk’s best-in-class solutions for infrastructure monitoring, application performance monitoring, digital experience monitoring, log investigation and incident response into a single, tightly integrated suite of products. It delivers a unified, consistent experience that leverages industry-leading no sample streaming, full-fidelity ingestion, and sophisticated machine learning capabilities to collect and correlate across all metric, trace and log data in real-time and at any scale. The Observability Suite is designed to help IT and DevOps teams maintain the highest levels of business performance, minimize downtime and deliver world-class digital experiences.

“At Splunk, we believe modern application environments and open, cloud-native technologies will help our customers unlock greater business insights,” said Karthik Rau, VP of Observability, Splunk. “The Splunk Observability Suite makes it easier for organizations to accelerate their cloud migration and application modernization initiatives, and helps them deliver world-class digital experiences better than ever before.”

At the annual user-conference, .conf20, Splunk also announced Splunk Log Observer and Splunk Real User Monitoring. Splunk Log Observer brings the power of Splunk logs to site reliability engineers, DevOps engineers and developers. Entirely cloud-based, it deploys within minutes and offers out-of-the-box integrations with popular cloud and messaging services for fast time-to-value, and provides a point-and-click search for rapid log exploration. As part of the Splunk Observability Suite, Splunk Log Observer works seamlessly with Splunk Infrastructure Monitoring and Splunk Application Monitoring (APM) for context-rich, unified monitoring, troubleshooting and investigation.

Splunk Real User Monitoring extends Splunk’s monitoring capabilities helping organizations understand and optimize the digital experiences and user journeys of their end customers. Splunk Real User Monitoring leverages the same capabilities of Splunk APM with OpenTelemetry-based data collection, NoSample™ full-fidelity data ingestion, real-time streaming architecture, and AI-driven analytics for directed troubleshooting.

Both Splunk Log Observer and Splunk Real User Monitoring are currently available in beta for customers, with general availability coming in the future.

The combination of Splunk Log Observer and Real User Monitoring with the rest of the Splunk Observability Suite that includes Splunk Infrastructure Monitoring, Splunk Application Performance Monitoring, and Splunk On-Call, gives DevOps teams unmatched, end-to-end visibility and pinpointed, early problem detection for their cloud applications, all through a seamless and unified user experience.

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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 ...