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Splunk Enterprise 8.1 Released

Splunk announced the latest enhancements to Splunk Cloud and Splunk Enterprise that will bring data to every decision, question and action across IT, Security and Observability. These new innovations enable customers to accelerate their Cloud transformation with a single, modern data platform.

Splunk Enterprise 8.1 is now generally available, with turbocharged productivity, enhanced insights and streamlined administration.

“The move to the cloud and digital technology has accelerated in the Data Age, and organizations are adapting to new work environments. Cloud solutions are needed for these organizations to scale and adapt,” said Sendur Sellakumar, Chief Product Officer, Splunk. “Splunk’s solutions enable the speed, scale and flexibility with new search and mobile capabilities that help organizations through their cloud transformation and lets them not just succeed but thrive in the Data Age.”

Splunk is making the shift to cloud easier with investments in cloud-native technology and solutions. With Splunk Cloud’s accelerated release schedule, customers can achieve faster time to value with immediate access to the latest features without any impact to service delivery. Splunk makes data onboarding faster and more reliable with new capabilities on the stream, and is also providing more flexibility of choice to customers as they move their workloads to the cloud, the Splunk Operator for Kubernetes, now in Beta, lets customers easily deploy and manage Splunk Enterprise in a Kubernetes infrastructure.

Splunk introduced the Splunk Machine Learning Environment (SMLE), a new solution for advanced analytics, data science, and machine learning, along with updates to Splunk’s foundational technologies. Splunk enables IT, security and observability customers to interact with their data and leverage insights on the go across customer managed and Cloud environments. These updates include:

- Splunk Machine Learning Environment (SMLE) is a new, dedicated solution that makes it easier to build and operationalize machine learning models and algorithms and helps get value from data at scale in Splunk. SMLE simplifies the end-to-end machine learning lifecycle and provides faster time to production with rapid deployment, centralized model management, and automated monitoring at scale. As the volume of data continues to increase, SMLE brings that data into one platform to view insights at optimal speed. SMLE beta is available for customers today.

- The latest version of Splunk Data Stream Processor (DSP) supports customers’ multicloud strategies with its ability to access, process, and route data from and to multiple cloud services, such as Google Cloud Platform and Azure Event Hub. Additionally, Splunk DSP 1.2 enriches event data with lookups and ML functionality, minimizing compute load and making downstream searches more accurate and efficient, unlocking additional value for IT, observability and security teams. Splunk DSP will also be available for the cloud later this year.

- Splunk Connected Experiences updates help customers get their data insights on-the-go, and improve workforce productivity from anywhere. Splunk Augmented Reality introduces the new remote collaboration feature that allows users in two different places to collaborate and interact in an environment through a shared experience. Splunk TV now allows users to centrally control multiple TVs without having to be connected to the same network, and Splunk TV is now available on both Android™ TV and Fire® TV in addition to the App Store on Apple TV®. Splunk Virtual Reality is also now generally available, and the 3D experience enables customers to find data they need by visually comparing data at scale and simplifying trend analysis.

Additionally, Splunk is expanding data access and helping customers succeed in a cloud-first world by strengthening its strategic partnership with Google Cloud. The partnership enables faster innovation with on-demand scaling and flexibility in choosing how to consume cloud-native Splunk Cloud services. Splunk Cloud on Google Cloud is now generally available after concluding a strong limited availability release, offering customers end-to-end visibility across Google Cloud, multicloud and hybrid environments.

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 ...

Splunk Enterprise 8.1 Released

Splunk announced the latest enhancements to Splunk Cloud and Splunk Enterprise that will bring data to every decision, question and action across IT, Security and Observability. These new innovations enable customers to accelerate their Cloud transformation with a single, modern data platform.

Splunk Enterprise 8.1 is now generally available, with turbocharged productivity, enhanced insights and streamlined administration.

“The move to the cloud and digital technology has accelerated in the Data Age, and organizations are adapting to new work environments. Cloud solutions are needed for these organizations to scale and adapt,” said Sendur Sellakumar, Chief Product Officer, Splunk. “Splunk’s solutions enable the speed, scale and flexibility with new search and mobile capabilities that help organizations through their cloud transformation and lets them not just succeed but thrive in the Data Age.”

Splunk is making the shift to cloud easier with investments in cloud-native technology and solutions. With Splunk Cloud’s accelerated release schedule, customers can achieve faster time to value with immediate access to the latest features without any impact to service delivery. Splunk makes data onboarding faster and more reliable with new capabilities on the stream, and is also providing more flexibility of choice to customers as they move their workloads to the cloud, the Splunk Operator for Kubernetes, now in Beta, lets customers easily deploy and manage Splunk Enterprise in a Kubernetes infrastructure.

Splunk introduced the Splunk Machine Learning Environment (SMLE), a new solution for advanced analytics, data science, and machine learning, along with updates to Splunk’s foundational technologies. Splunk enables IT, security and observability customers to interact with their data and leverage insights on the go across customer managed and Cloud environments. These updates include:

- Splunk Machine Learning Environment (SMLE) is a new, dedicated solution that makes it easier to build and operationalize machine learning models and algorithms and helps get value from data at scale in Splunk. SMLE simplifies the end-to-end machine learning lifecycle and provides faster time to production with rapid deployment, centralized model management, and automated monitoring at scale. As the volume of data continues to increase, SMLE brings that data into one platform to view insights at optimal speed. SMLE beta is available for customers today.

- The latest version of Splunk Data Stream Processor (DSP) supports customers’ multicloud strategies with its ability to access, process, and route data from and to multiple cloud services, such as Google Cloud Platform and Azure Event Hub. Additionally, Splunk DSP 1.2 enriches event data with lookups and ML functionality, minimizing compute load and making downstream searches more accurate and efficient, unlocking additional value for IT, observability and security teams. Splunk DSP will also be available for the cloud later this year.

- Splunk Connected Experiences updates help customers get their data insights on-the-go, and improve workforce productivity from anywhere. Splunk Augmented Reality introduces the new remote collaboration feature that allows users in two different places to collaborate and interact in an environment through a shared experience. Splunk TV now allows users to centrally control multiple TVs without having to be connected to the same network, and Splunk TV is now available on both Android™ TV and Fire® TV in addition to the App Store on Apple TV®. Splunk Virtual Reality is also now generally available, and the 3D experience enables customers to find data they need by visually comparing data at scale and simplifying trend analysis.

Additionally, Splunk is expanding data access and helping customers succeed in a cloud-first world by strengthening its strategic partnership with Google Cloud. The partnership enables faster innovation with on-demand scaling and flexibility in choosing how to consume cloud-native Splunk Cloud services. Splunk Cloud on Google Cloud is now generally available after concluding a strong limited availability release, offering customers end-to-end visibility across Google Cloud, multicloud and hybrid environments.

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 ...