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Splunk App for New Relic Released

Splunk and New Relic announced a strategic alliance and a new integration to help enterprises improve customer experiences and drive revenues — the Splunk App for New Relic, available today as a preview release on Splunkbase, gives developers and IT operations teams a comprehensive view into both application performance and infrastructure health with seamless sharing of data across both Splunk and New Relic platforms.

The Splunk Platform collects, analyzes and visualizes machine data from all levels of the IT stack, including applications, infrastructure and wire data on the network so organizations can make business-critical decisions tied to troubleshooting, reliability and planning. New Relic’s Digital Intelligence platform collects and traces data from agents inside application code and infrastructure so organizations can make decisions on customer experience, application dependencies and code performance. Both solutions support cloud, hybrid and on-premises data center architectures.

Unifying machine data analytics with application tracing and performance metrics enables IT and business stakeholders to experience a faster time-to-value through visualizing data across both platforms. The Splunk App for New Relic integration enables developers and IT operations teams to quickly identify issues, reduce mean-time-to-resolution (MTTR) and proactively improve customer experiences. The result is improved revenues and expanded resources for engineering teams to drive a faster pace of innovation for their end users.

“Machine data is the fuel for digital transformation and those organizations capitalizing on the opportunity are leading the way in IT by monitoring and troubleshooting application performance, often with both Splunk and New Relic,” said Rick Fitz, SVP of IT Markets, Splunk. “The partnership enables our joint customers to gain value faster, whether their applications run on-premises or on the cloud. The integration breaks down silos within IT teams to be able to fully leverage both data and workflow insights across the platforms to gain deeper insights with fewer steps.”

“New Relic’s agent data provides visibility into the dependencies across customer experience to application code to infrastructure. When combined with machine data from Splunk, our joint customers will be able to troubleshoot and innovate faster,” said Jim Gochee, Chief Product Officer, New Relic. “We have heard from many customers that they want to standardize the tools and streamline the processes they use to run digital businesses, and today we’re making it possible with an all-in-one integration between two market-leading platforms.”

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Splunk App for New Relic Released

Splunk and New Relic announced a strategic alliance and a new integration to help enterprises improve customer experiences and drive revenues — the Splunk App for New Relic, available today as a preview release on Splunkbase, gives developers and IT operations teams a comprehensive view into both application performance and infrastructure health with seamless sharing of data across both Splunk and New Relic platforms.

The Splunk Platform collects, analyzes and visualizes machine data from all levels of the IT stack, including applications, infrastructure and wire data on the network so organizations can make business-critical decisions tied to troubleshooting, reliability and planning. New Relic’s Digital Intelligence platform collects and traces data from agents inside application code and infrastructure so organizations can make decisions on customer experience, application dependencies and code performance. Both solutions support cloud, hybrid and on-premises data center architectures.

Unifying machine data analytics with application tracing and performance metrics enables IT and business stakeholders to experience a faster time-to-value through visualizing data across both platforms. The Splunk App for New Relic integration enables developers and IT operations teams to quickly identify issues, reduce mean-time-to-resolution (MTTR) and proactively improve customer experiences. The result is improved revenues and expanded resources for engineering teams to drive a faster pace of innovation for their end users.

“Machine data is the fuel for digital transformation and those organizations capitalizing on the opportunity are leading the way in IT by monitoring and troubleshooting application performance, often with both Splunk and New Relic,” said Rick Fitz, SVP of IT Markets, Splunk. “The partnership enables our joint customers to gain value faster, whether their applications run on-premises or on the cloud. The integration breaks down silos within IT teams to be able to fully leverage both data and workflow insights across the platforms to gain deeper insights with fewer steps.”

“New Relic’s agent data provides visibility into the dependencies across customer experience to application code to infrastructure. When combined with machine data from Splunk, our joint customers will be able to troubleshoot and innovate faster,” said Jim Gochee, Chief Product Officer, New Relic. “We have heard from many customers that they want to standardize the tools and streamline the processes they use to run digital businesses, and today we’re making it possible with an all-in-one integration between two market-leading platforms.”

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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 ...

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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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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 ...