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New Relic Launches Add-On for Amazon EKS

New Relic announced expanded support for Amazon Elastic Kubernetes Service (Amazon EKS), with an add-on for Amazon EKS Blueprints that automates and standardizes how engineers add observability instrumentation to software deployed on Kubernetes.

The new add-on deploys New Relic’s Kubernetes observability components — including infrastructure agents, Kube events, logging, auto-telemetry with Pixie, and New Relic’s Prometheus OpenMetrics integration — using code directly within Amazon EKS, reducing the need for observability expertise or the need to manually instrument clusters. Once deployed, New Relic’s Kubernetes solution allows teams to analyze application and cluster performance in a single, curated user interface (UI), and auto-telemetry with Pixie gives teams continuous profiling to understand where code is running slow or consuming valuable cluster resources.

Kubernetes environments’ distributed and ephemeral nature make it very complex to troubleshoot. The complexity increases in pre-production environments, where engineers are less likely to add monitoring instrumentation. Without observability, engineers are blind to the performance of their clusters and the applications that run on them, resulting in degraded software performance and downtime. New Relic’s add-on for Amazon EKS Blueprints solves this challenge by automating Kubernetes observability to save developer time and standardizing observability best practices across all their deployments.

"Today's news follows a long-standing strategic collaboration agreement with Amazon Web Services to bring New Relic’s data-driven observability to millions of engineers and developers globally,” said Alex Kroman, Senior VP and Product GM at New Relic. "New Relic continues to invest in supporting AWS technologies that our customers depend on to achieve faster, lower-risk migrations with more compelling business outcomes."

Features and benefits include:

- Automate adding observability components in Amazon EKS clusters

- Standardize on observability best practices in all Kubernetes deployments

- Optimize performance with cluster-wide observability, dashboarding, and alerting

New Relic’s add-on for Amazon EKS Blueprints is generally available. All existing customers of New Relic—an all-in-one observability platform with a secure telemetry cloud, powerful full-stack analysis tools, and predictable consumption pricing -- can access this new capability without any additional cost as part of their New Relic account. New customers can sign up and start using the experience for free, no credit card needed.

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New Relic Launches Add-On for Amazon EKS

New Relic announced expanded support for Amazon Elastic Kubernetes Service (Amazon EKS), with an add-on for Amazon EKS Blueprints that automates and standardizes how engineers add observability instrumentation to software deployed on Kubernetes.

The new add-on deploys New Relic’s Kubernetes observability components — including infrastructure agents, Kube events, logging, auto-telemetry with Pixie, and New Relic’s Prometheus OpenMetrics integration — using code directly within Amazon EKS, reducing the need for observability expertise or the need to manually instrument clusters. Once deployed, New Relic’s Kubernetes solution allows teams to analyze application and cluster performance in a single, curated user interface (UI), and auto-telemetry with Pixie gives teams continuous profiling to understand where code is running slow or consuming valuable cluster resources.

Kubernetes environments’ distributed and ephemeral nature make it very complex to troubleshoot. The complexity increases in pre-production environments, where engineers are less likely to add monitoring instrumentation. Without observability, engineers are blind to the performance of their clusters and the applications that run on them, resulting in degraded software performance and downtime. New Relic’s add-on for Amazon EKS Blueprints solves this challenge by automating Kubernetes observability to save developer time and standardizing observability best practices across all their deployments.

"Today's news follows a long-standing strategic collaboration agreement with Amazon Web Services to bring New Relic’s data-driven observability to millions of engineers and developers globally,” said Alex Kroman, Senior VP and Product GM at New Relic. "New Relic continues to invest in supporting AWS technologies that our customers depend on to achieve faster, lower-risk migrations with more compelling business outcomes."

Features and benefits include:

- Automate adding observability components in Amazon EKS clusters

- Standardize on observability best practices in all Kubernetes deployments

- Optimize performance with cluster-wide observability, dashboarding, and alerting

New Relic’s add-on for Amazon EKS Blueprints is generally available. All existing customers of New Relic—an all-in-one observability platform with a secure telemetry cloud, powerful full-stack analysis tools, and predictable consumption pricing -- can access this new capability without any additional cost as part of their New Relic account. New customers can sign up and start using the experience for free, no credit card needed.

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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 ...