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New Relic Enhances Kubernetes Observability

New Relic announced a series of product innovations and enhancements to help millions of engineers take a daily, data-driven approach to Kubernetes observability.

New Relic re-architected its Kubernetes integration to reduce the overhead associated with monitoring Kubernetes environments with an improved memory footprint, flexible scraping intervals, and more.

In addition, New Relic announced plugin support for Pixie, an open source observability tool for Kubernetes, to give New Relic users unlimited access to the latest Pixie innovation directly inside the New Relic platform. These innovations are included as an essential part of the all-in-one New Relic observability platform that allows engineers to get 3X+ more value than the competition.

According to industry data from the Cloud Native Computing Foundation (CNCF) and New Relic, container and Kubernetes adoption is mainstream, with 93% of organizations around the world using or planning to use containers in production, and 96% of organizations using or evaluating Kubernetes. As organizations accelerate their adoption of Kubernetes, the right monitoring architecture needs to be in place to minimize the consumption of access resources. Monitoring tools, with non-optimized agents and DaemonSet architectures, consume excessive cluster resources, adding unnecessary overhead and expense. Separately, as companies grow their Kubernetes footprints in many clusters, many choose to use solutions such as Rancher to manage their growing landscape. Without the ability to monitor external control planes, these organizations miss important performance signals. New Relic’s latest innovations — the Kubernetes integration and Pixie plugin — fill this gap by giving every engineer access to Kubernetes observability right from the New Relic UI.

“Kubernetes provides incredibly powerful tooling for running workloads. Its configurability, extensibility, and expressiveness give us more power than ever to structure, optimize, and scale our applications.,” said Zain Asgar, New Relic GVP & Product GM, Pixie Co-founder, and CNCF Governing Board member. “New Relic and Pixie have a joint mission to be developer-first, which means first class support for Kubernetes ...”

Kubernetes integration updates:

- Reduced memory footprint: Avoid data duplication while scraping kube-state-metrics (KSM) and control plane components to reduce memory consumption by 80% in big clusters.

- Support for control planes: Ensure clusters are maintained in accordance with your security, compliance or governance policies by supporting external control planes like Rancher Kubernetes Engine.

- Flexible scraping intervals: Dial up or dial down data ingest to find the right balance between data granularity and managing data ingest costs.

- Improved troubleshooting: Triage bugs and fix issues quicker with enhanced logs and process cycles.

- Easier configuration: Three individually-configurable components are now available, including support for config files that provide more granular settings.

Pixie plugin framework:

By supporting the Pixie plugin framework, New Relic is unlocking access to Pixie’s capabilities directly inside of the New Relic UI. With this new release, the New Relic Pixie integration is optimized to bring a subset of Pixie data off-cluster into New Relic for long term storage and retention, and as new capabilities are deployed they will be available to engineers using New Relic. With New Relic's Pixie plugin, the company is also giving users access to longer data retention and enterprise-grade alerting directly inside Pixie, so users can be alerted immediately when system performance suffers, and they'll be able to go beyond real-time debugging to analyze performance over longer time horizons.

With these releases, New Relic is activating its commitment to make observability a daily, data-driven habit for every engineer by continuing to invest heavily in the global open source and cloud-native communities. Since 2020, New Relic open sourced more than ten years of agents R&D, acquired Pixie Labs and contributed Pixie as an open source project to CNCF, and launched New Relic Instant Observability. These new enhancements are the continuation of this strategy to dramatically reduce the barrier for engineers to adopt Kubernetes observability.

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New Relic Enhances Kubernetes Observability

New Relic announced a series of product innovations and enhancements to help millions of engineers take a daily, data-driven approach to Kubernetes observability.

New Relic re-architected its Kubernetes integration to reduce the overhead associated with monitoring Kubernetes environments with an improved memory footprint, flexible scraping intervals, and more.

In addition, New Relic announced plugin support for Pixie, an open source observability tool for Kubernetes, to give New Relic users unlimited access to the latest Pixie innovation directly inside the New Relic platform. These innovations are included as an essential part of the all-in-one New Relic observability platform that allows engineers to get 3X+ more value than the competition.

According to industry data from the Cloud Native Computing Foundation (CNCF) and New Relic, container and Kubernetes adoption is mainstream, with 93% of organizations around the world using or planning to use containers in production, and 96% of organizations using or evaluating Kubernetes. As organizations accelerate their adoption of Kubernetes, the right monitoring architecture needs to be in place to minimize the consumption of access resources. Monitoring tools, with non-optimized agents and DaemonSet architectures, consume excessive cluster resources, adding unnecessary overhead and expense. Separately, as companies grow their Kubernetes footprints in many clusters, many choose to use solutions such as Rancher to manage their growing landscape. Without the ability to monitor external control planes, these organizations miss important performance signals. New Relic’s latest innovations — the Kubernetes integration and Pixie plugin — fill this gap by giving every engineer access to Kubernetes observability right from the New Relic UI.

“Kubernetes provides incredibly powerful tooling for running workloads. Its configurability, extensibility, and expressiveness give us more power than ever to structure, optimize, and scale our applications.,” said Zain Asgar, New Relic GVP & Product GM, Pixie Co-founder, and CNCF Governing Board member. “New Relic and Pixie have a joint mission to be developer-first, which means first class support for Kubernetes ...”

Kubernetes integration updates:

- Reduced memory footprint: Avoid data duplication while scraping kube-state-metrics (KSM) and control plane components to reduce memory consumption by 80% in big clusters.

- Support for control planes: Ensure clusters are maintained in accordance with your security, compliance or governance policies by supporting external control planes like Rancher Kubernetes Engine.

- Flexible scraping intervals: Dial up or dial down data ingest to find the right balance between data granularity and managing data ingest costs.

- Improved troubleshooting: Triage bugs and fix issues quicker with enhanced logs and process cycles.

- Easier configuration: Three individually-configurable components are now available, including support for config files that provide more granular settings.

Pixie plugin framework:

By supporting the Pixie plugin framework, New Relic is unlocking access to Pixie’s capabilities directly inside of the New Relic UI. With this new release, the New Relic Pixie integration is optimized to bring a subset of Pixie data off-cluster into New Relic for long term storage and retention, and as new capabilities are deployed they will be available to engineers using New Relic. With New Relic's Pixie plugin, the company is also giving users access to longer data retention and enterprise-grade alerting directly inside Pixie, so users can be alerted immediately when system performance suffers, and they'll be able to go beyond real-time debugging to analyze performance over longer time horizons.

With these releases, New Relic is activating its commitment to make observability a daily, data-driven habit for every engineer by continuing to invest heavily in the global open source and cloud-native communities. Since 2020, New Relic open sourced more than ten years of agents R&D, acquired Pixie Labs and contributed Pixie as an open source project to CNCF, and launched New Relic Instant Observability. These new enhancements are the continuation of this strategy to dramatically reduce the barrier for engineers to adopt Kubernetes observability.

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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 ...