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New Relic One Observability Platform Introduced

New Relic announced the New Relic One Observability Platform, built to help customers create more perfect software.

The company announced advanced platform capabilities, including New Relic Logs, New Relic Traces, New Relic Metrics, and New Relic AI to empower teams with the data they need to move faster and build better digital experiences.

The company also unveiled programmability on the New Relic One Platform, which gives all customers and partners the ability to build entirely new applications on top of New Relic One, enabling them to integrate their best of breed business data and create seamless workflows on the platform to drive real-time actionable insights.

"New Relic One is now the world’s first observability platform that is open, enabling customers to bring in agent-based and open telemetry data so they have no blind spots; connected, allowing customers to see relationships between their systems so they can act more quickly and effectively; and programmable, empowering customers to build entirely new applications on top of New Relic to fuel their business. It’s not a platform unless you can build apps on it," said CEO and Founder Lew Cirne. “I’m so inspired by the creativity and ingenuity I’ve seen from our early-access customers and partners building observability apps on New Relic One. I can’t wait to see what our developer community will unleash for our global customers."

New Relic One was built in response to the needs of companies who are leveraging the power of modern software technologies, including cloud technology and containerization, to quickly build, scale and operate business-critical applications. They require a single observability platform for all their critical data with applied intelligence and automation technologies that can seamlessly fit into their unique business processes so they can optimize their software and deliver better customer experiences.

Empowering customers and partners to quickly and easily build new applications on New Relic One:

- New Relic One allows New Relic’s developer community and customers to easily build and share applications that connect observability data and business data, unlocking opportunities for companies to deliver better digital customer experiences.

- New Relic One makes it easy for developers to go from “idea to application” very quickly. Developers only need to know React.js and GraphQL, two popular Internet languages, to begin coding, and applications can be created in minutes.

- New Relic One programmability is available now for all customers.

Open-source applications for the New Relic developer community:

New Relic worked with a select group of customers and partners to jointly develop an initial set of New Relic One applications. These apps are freely available for New Relic’s developer community to download on Github under an apache license.

Initial New Relic One apps include:

- Cloud Optimize -- Compares size of an organization’s cloud resources to utilization, so companies can save money on their cloud bill.

- Github Integration -- Teams can immediately see what a service does and who's been working on it, so they can troubleshoot faster.

- Site Analyzer -- Forecasts website performance and how improved KPIs, such as traffic and average load times, can drive better customer experiences.

- Status Page -- Consolidates Statuspage.io status pages into a single dashboard, so teams have one place to check on all their key dependencies and diagnose issues quickly.

- Customer Journeys -- Tracks customer cohort progress through the funnel, so teams can better understand how customers are moving towards a purchase decision.

New Relic Logs - Correlate log, application and infrastructure data in a single platform:

- New Relic announced the availability of New Relic Logs, a new log management capability that allows teams to easily manage log data with application and infrastructure data -- while quickly performing ad hoc searches that return queries instantaneously -- all in a single, highly scalable platform.

- Without having to switch tools and lose context, teams can more easily detect and resolve issues faster, often before they impact customers. New Relic Logs eliminates the cost and complexity of managing and maintaining multiple on-premise and legacy log management tools in-house.

- New Relic Logs is now available.

New Relic Traces and New Relic Metrics: New Relic One unifies performance data from any source, whether agent-based or agentless:

- New Relic announced the availability of New Relic Traces and New Relic Metrics, two new products designed to bring more sources of data into the New Relic One Observability Platform. Customers can now easily ingest data from any source -- including Metrics, Events, Logs and Traces -- into the platform.

- New Relic continues to actively contribute to and support several open source communities such as OpenTelemetry, AdoptOpenJDK and CNCF.

- New Relic Traces and New Relic Metrics are now available.

New Relic AI: a comprehensive AIOps and smarter incident response suite:

- New Relic introduced New Relic AI, now in beta, a new intelligent AIOps solution for busy DevOps, SRE and on-call teams that helps them find, troubleshoot, and resolve problems faster. New Relic AI automatically correlates, aggregates and prioritizes incident data, eliminating noise and dramatically cutting MTTR. Initial customers have reported that they have seen a 80+% reduction of alerting noise.

- New Relic AI deeply integrates with customers’ PagerDuty accounts, and delivers critical proactive insights to customers’ Slack channels directly, including intelligent incident context and automatic anomaly detection. Customers have access to critical business information about their production system at their fingertips, all without modifying existing on-call workflows.

The Latest

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 ...

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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 ...

New Relic One Observability Platform Introduced

New Relic announced the New Relic One Observability Platform, built to help customers create more perfect software.

The company announced advanced platform capabilities, including New Relic Logs, New Relic Traces, New Relic Metrics, and New Relic AI to empower teams with the data they need to move faster and build better digital experiences.

The company also unveiled programmability on the New Relic One Platform, which gives all customers and partners the ability to build entirely new applications on top of New Relic One, enabling them to integrate their best of breed business data and create seamless workflows on the platform to drive real-time actionable insights.

"New Relic One is now the world’s first observability platform that is open, enabling customers to bring in agent-based and open telemetry data so they have no blind spots; connected, allowing customers to see relationships between their systems so they can act more quickly and effectively; and programmable, empowering customers to build entirely new applications on top of New Relic to fuel their business. It’s not a platform unless you can build apps on it," said CEO and Founder Lew Cirne. “I’m so inspired by the creativity and ingenuity I’ve seen from our early-access customers and partners building observability apps on New Relic One. I can’t wait to see what our developer community will unleash for our global customers."

New Relic One was built in response to the needs of companies who are leveraging the power of modern software technologies, including cloud technology and containerization, to quickly build, scale and operate business-critical applications. They require a single observability platform for all their critical data with applied intelligence and automation technologies that can seamlessly fit into their unique business processes so they can optimize their software and deliver better customer experiences.

Empowering customers and partners to quickly and easily build new applications on New Relic One:

- New Relic One allows New Relic’s developer community and customers to easily build and share applications that connect observability data and business data, unlocking opportunities for companies to deliver better digital customer experiences.

- New Relic One makes it easy for developers to go from “idea to application” very quickly. Developers only need to know React.js and GraphQL, two popular Internet languages, to begin coding, and applications can be created in minutes.

- New Relic One programmability is available now for all customers.

Open-source applications for the New Relic developer community:

New Relic worked with a select group of customers and partners to jointly develop an initial set of New Relic One applications. These apps are freely available for New Relic’s developer community to download on Github under an apache license.

Initial New Relic One apps include:

- Cloud Optimize -- Compares size of an organization’s cloud resources to utilization, so companies can save money on their cloud bill.

- Github Integration -- Teams can immediately see what a service does and who's been working on it, so they can troubleshoot faster.

- Site Analyzer -- Forecasts website performance and how improved KPIs, such as traffic and average load times, can drive better customer experiences.

- Status Page -- Consolidates Statuspage.io status pages into a single dashboard, so teams have one place to check on all their key dependencies and diagnose issues quickly.

- Customer Journeys -- Tracks customer cohort progress through the funnel, so teams can better understand how customers are moving towards a purchase decision.

New Relic Logs - Correlate log, application and infrastructure data in a single platform:

- New Relic announced the availability of New Relic Logs, a new log management capability that allows teams to easily manage log data with application and infrastructure data -- while quickly performing ad hoc searches that return queries instantaneously -- all in a single, highly scalable platform.

- Without having to switch tools and lose context, teams can more easily detect and resolve issues faster, often before they impact customers. New Relic Logs eliminates the cost and complexity of managing and maintaining multiple on-premise and legacy log management tools in-house.

- New Relic Logs is now available.

New Relic Traces and New Relic Metrics: New Relic One unifies performance data from any source, whether agent-based or agentless:

- New Relic announced the availability of New Relic Traces and New Relic Metrics, two new products designed to bring more sources of data into the New Relic One Observability Platform. Customers can now easily ingest data from any source -- including Metrics, Events, Logs and Traces -- into the platform.

- New Relic continues to actively contribute to and support several open source communities such as OpenTelemetry, AdoptOpenJDK and CNCF.

- New Relic Traces and New Relic Metrics are now available.

New Relic AI: a comprehensive AIOps and smarter incident response suite:

- New Relic introduced New Relic AI, now in beta, a new intelligent AIOps solution for busy DevOps, SRE and on-call teams that helps them find, troubleshoot, and resolve problems faster. New Relic AI automatically correlates, aggregates and prioritizes incident data, eliminating noise and dramatically cutting MTTR. Initial customers have reported that they have seen a 80+% reduction of alerting noise.

- New Relic AI deeply integrates with customers’ PagerDuty accounts, and delivers critical proactive insights to customers’ Slack channels directly, including intelligent incident context and automatic anomaly detection. Customers have access to critical business information about their production system at their fingertips, all without modifying existing on-call workflows.

The Latest

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 ...