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New Relic Releases APM 360

New Relic launched New Relic APM 360, providing application performance monitoring (APM) that goes beyond incident troubleshooting insights for select experts to daily performance, security, and development insights for all engineers.

APM 360 correlates all essential telemetry data across the application stack and development cycle, such as deployment changes, key transactions, service-level objects (SLOs), logs, infrastructure, errors, security, debugging, and more. Now all engineers, regardless of their role and level of experience, can understand the upstream and downstream impact of issues, discover emerging trends, and ultimately move from traditional monitoring to regular application maintenance and checks with the right insights to prevent potential issues. APM 360 helps all engineering teams across the organization gain a shared understanding of system health and close instrumentation gaps, driving platform adoption and increased data flow into the New Relic platform.

"New Relic pioneered application monitoring over a decade ago, and we have continuously innovated to meet the growing needs of our customers," said New Relic Chief Product Officer Manav Khurana. "We introduced our all-in-one observability platform, offering a way to get all data across logs, infrastructure, and vulnerability management in context with single platform pricing. This has laid the foundation for us to redefine the APM landscape once again. New Relic APM 360 represents a pivotal moment in application performance monitoring where we have made it easy for engineers to make APM a simple daily practice."

APM 360 gives engineers a holistic view of application health and performance with at-a-glance health monitoring and full app lifecycle insights in a single place. It also debugs workflows and provides automated dependency visualization to improve customer experiences, with easy access to the following daily insights:

- Deployment changes: View all deployments and change events without switching tools or screens.

- User experience signals: Track customer-impacting transactions and see synthetics checks right in APM.

- Correlated service levels: Monitor SLO budgets and risks directly from inside the APM view.

- Full-stack performance: At-a-glance view of services, infras, logs, issues, and more to drive daily insights.

- Unified security view: No-instrumentation access to application vulnerabilities from APM agent or third-party sources for a full view of continuous runtime software composition analysis (SCA) alongside APM telemetry.

- Code-level debugging: Drill down to access stack-traces, errors, metrics, and logs in the context of code.

- Data recommendations: Discover and rectify uninstrumented services, missing alerts, and vulnerabilities.

- Generative AI assistance: Coming soon, use New Relic Grok (now in early access) to ask any questions in natural language.

New Relic APM 360 is now available free to all New Relic users.

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 ...

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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 ...

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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.

New Relic Releases APM 360

New Relic launched New Relic APM 360, providing application performance monitoring (APM) that goes beyond incident troubleshooting insights for select experts to daily performance, security, and development insights for all engineers.

APM 360 correlates all essential telemetry data across the application stack and development cycle, such as deployment changes, key transactions, service-level objects (SLOs), logs, infrastructure, errors, security, debugging, and more. Now all engineers, regardless of their role and level of experience, can understand the upstream and downstream impact of issues, discover emerging trends, and ultimately move from traditional monitoring to regular application maintenance and checks with the right insights to prevent potential issues. APM 360 helps all engineering teams across the organization gain a shared understanding of system health and close instrumentation gaps, driving platform adoption and increased data flow into the New Relic platform.

"New Relic pioneered application monitoring over a decade ago, and we have continuously innovated to meet the growing needs of our customers," said New Relic Chief Product Officer Manav Khurana. "We introduced our all-in-one observability platform, offering a way to get all data across logs, infrastructure, and vulnerability management in context with single platform pricing. This has laid the foundation for us to redefine the APM landscape once again. New Relic APM 360 represents a pivotal moment in application performance monitoring where we have made it easy for engineers to make APM a simple daily practice."

APM 360 gives engineers a holistic view of application health and performance with at-a-glance health monitoring and full app lifecycle insights in a single place. It also debugs workflows and provides automated dependency visualization to improve customer experiences, with easy access to the following daily insights:

- Deployment changes: View all deployments and change events without switching tools or screens.

- User experience signals: Track customer-impacting transactions and see synthetics checks right in APM.

- Correlated service levels: Monitor SLO budgets and risks directly from inside the APM view.

- Full-stack performance: At-a-glance view of services, infras, logs, issues, and more to drive daily insights.

- Unified security view: No-instrumentation access to application vulnerabilities from APM agent or third-party sources for a full view of continuous runtime software composition analysis (SCA) alongside APM telemetry.

- Code-level debugging: Drill down to access stack-traces, errors, metrics, and logs in the context of code.

- Data recommendations: Discover and rectify uninstrumented services, missing alerts, and vulnerabilities.

- Generative AI assistance: Coming soon, use New Relic Grok (now in early access) to ask any questions in natural language.

New Relic APM 360 is now available free to all New Relic users.

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.