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Azure Native New Relic Service Available in Microsoft Azure Marketplace

New Relic announced the general availability of the Azure Native New Relic Service in the Microsoft Azure Marketplace, to help enterprises accelerate their cloud migration and multi-cloud initiatives.

Microsoft Azure customers can now subscribe to the New Relic service to collect telemetry data for applications and infrastructure and store that telemetry data in Azure. In addition, Azure customers can allocate their multi-year committed Azure spend to leverage New Relic, making it significantly easier for customers to allocate budget for all-in-one observability. This release builds on more than a decade of innovation between New Relic and Microsoft to give developers the tools they need to build better software.

Azure customers can accelerate their cloud journey with New Relic's all-in-one observability platform directly in Azure. DevOps teams can store their telemetry data in Azure, get started fast with Azure integrations and agents, all in a single pane of glass for monitoring all their workloads to debug, measure, and improve their entire stack.

“Observability is essential in today's modern, multi-cloud world. Whether our customers are running applications on data centers, embracing the public cloud, or running things at the edge, they need observability to take a look across all those systems,” said New Relic CEO Bill Staples.

“Microsoft and New Relic share a strong commitment to providing world-class developer tools that help make developers and our customers successful. This partnership unlocks greater productivity for all engineers with seamless integration between Azure and New Relic’s all-in-one Observability platform,” said Scott Guthrie, Executive VP, Cloud + AI, Microsoft. “Engineers and business leaders alike will benefit from this unique and powerful experience as they embrace New Relic’s data-driven approach to engineering.”

New Relic helps customers accelerate their cloud adoption and multi-cloud journeys by providing a comprehensive view of the entire application stack, including the underlying cloud infrastructure, application code, and user experience, allowing customers to quickly identify and troubleshoot performance issues, optimize multi-cloud resources, and ensure that their applications are running smoothly.

Integration highlights include:

- Store Telemetry in Azure: Subscribed customers will store their telemetry data on Azure to help align with their digital transformation and multi-cloud strategy.

- Native Azure Marketplace Integration: New Relic has collaborated with Microsoft on the engineering effort to deliver natively integrated New Relic observability solutions through the Azure Marketplace.

- Retire Microsoft Azure Consumption Commitment (MACC): Azure customers can retire their MACC by purchasing New Relic from the Azure Marketplace, which simplifies purchasing and contract management.

- Rapid Onboarding: The Azure Native New Relic Service offers rapid onboarding, incorporating an Azure-specific integration and agent installations from the Azure Portal to help customers monitor and optimize the performance of their Azure-hosted applications and infrastructure. The integration enables Azure customers to send consolidated Azure Platform Logs and Azure Monitor metrics directly to New Relic.

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Azure Native New Relic Service Available in Microsoft Azure Marketplace

New Relic announced the general availability of the Azure Native New Relic Service in the Microsoft Azure Marketplace, to help enterprises accelerate their cloud migration and multi-cloud initiatives.

Microsoft Azure customers can now subscribe to the New Relic service to collect telemetry data for applications and infrastructure and store that telemetry data in Azure. In addition, Azure customers can allocate their multi-year committed Azure spend to leverage New Relic, making it significantly easier for customers to allocate budget for all-in-one observability. This release builds on more than a decade of innovation between New Relic and Microsoft to give developers the tools they need to build better software.

Azure customers can accelerate their cloud journey with New Relic's all-in-one observability platform directly in Azure. DevOps teams can store their telemetry data in Azure, get started fast with Azure integrations and agents, all in a single pane of glass for monitoring all their workloads to debug, measure, and improve their entire stack.

“Observability is essential in today's modern, multi-cloud world. Whether our customers are running applications on data centers, embracing the public cloud, or running things at the edge, they need observability to take a look across all those systems,” said New Relic CEO Bill Staples.

“Microsoft and New Relic share a strong commitment to providing world-class developer tools that help make developers and our customers successful. This partnership unlocks greater productivity for all engineers with seamless integration between Azure and New Relic’s all-in-one Observability platform,” said Scott Guthrie, Executive VP, Cloud + AI, Microsoft. “Engineers and business leaders alike will benefit from this unique and powerful experience as they embrace New Relic’s data-driven approach to engineering.”

New Relic helps customers accelerate their cloud adoption and multi-cloud journeys by providing a comprehensive view of the entire application stack, including the underlying cloud infrastructure, application code, and user experience, allowing customers to quickly identify and troubleshoot performance issues, optimize multi-cloud resources, and ensure that their applications are running smoothly.

Integration highlights include:

- Store Telemetry in Azure: Subscribed customers will store their telemetry data on Azure to help align with their digital transformation and multi-cloud strategy.

- Native Azure Marketplace Integration: New Relic has collaborated with Microsoft on the engineering effort to deliver natively integrated New Relic observability solutions through the Azure Marketplace.

- Retire Microsoft Azure Consumption Commitment (MACC): Azure customers can retire their MACC by purchasing New Relic from the Azure Marketplace, which simplifies purchasing and contract management.

- Rapid Onboarding: The Azure Native New Relic Service offers rapid onboarding, incorporating an Azure-specific integration and agent installations from the Azure Portal to help customers monitor and optimize the performance of their Azure-hosted applications and infrastructure. The integration enables Azure customers to send consolidated Azure Platform Logs and Azure Monitor metrics directly to New Relic.

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.