Skip to main content

New Relic Introduces Kubernetes Cluster Explorer

New Relic introduced the Kubernetes cluster explorer, a new way for DevOps teams to understand the health and performance of their complex Kubernetes environments.

New Relic’s Kubernetes cluster explorer allows teams to drill down into application and infrastructure metrics side-by-side in a rich, curated UI that simplifies complex environments. As a result, teams can understand dependencies across their entire environment, make better-informed decisions, and resolve errors – faster than ever before.

This announcement extends New Relic’s existing Kubernetes monitoring capabilities by offering a new way for customers to engage with their performance data. New Relic’s Kubernetes cluster explorer provides both a bird’s-eye view of a customer’s entire Kubernetes environment as well as the ability to dive deep into the performance of individual pods and nodes – all in a matter of seconds. Now customers can see not only how their Kubernetes entities are performing, but also how they are impacting their entire environment.

New Relic’s Kubernetes cluster explorer is designed to give software teams an easy way to manage the performance of modern environments.

- Multidimensional views into Kubernetes clusters - New Relic’s Kubernetes cluster explorer provides a unified view into infrastructure, applications, and services across Kubernetes clusters, so customers can inspect a single container, or scale up to explore a deployment of the whole cluster.

- Advanced filtering to quickly find root cause - DevOps teams can easily drill down to the objects they care about – containers, pods, nodes, deployments, namespaces, and labels – and access their application- and infrastructure-metrics to connect the dots between their complex, distributed systems.

- Delivers immediate value - New Relic’s SaaS platform delivers value as soon as the Kubernetes agent is deployed. There is no infrastructure to provision, secure, or run, so DevOps teams can focus on delivering software for their customers, not instrumenting and building their monitoring solution.

- Easy to get started on any cloud or on-prem - New Relic Kubernetes monitoring is compatible with all major cloud platforms as well as on-premise environments so teams can observe their Kubernetes workloads, regardless of where their containers are deployed.

"Today, modern software teams need to detect and resolve problems as quickly as possible. During critical service interruptions, every second counts. New Relic has a long history of instrumenting and visualizing our customers’ business-critical software in new ways so they can take action quickly and reduce their mean-time-to-detect and mean-time-to-resolution. Our new Kubernetes cluster explorer is designed to help our customers connect the dots between their complex, distributed systems faster than previously possible,” said Aaron Johnson, SVP, Product Management, New Relic

New Relic’s Kubernetes cluster explorer will be available in early 2019 for all New Relic customers who have enabled the Kubernetes on-host integration.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

New Relic Introduces Kubernetes Cluster Explorer

New Relic introduced the Kubernetes cluster explorer, a new way for DevOps teams to understand the health and performance of their complex Kubernetes environments.

New Relic’s Kubernetes cluster explorer allows teams to drill down into application and infrastructure metrics side-by-side in a rich, curated UI that simplifies complex environments. As a result, teams can understand dependencies across their entire environment, make better-informed decisions, and resolve errors – faster than ever before.

This announcement extends New Relic’s existing Kubernetes monitoring capabilities by offering a new way for customers to engage with their performance data. New Relic’s Kubernetes cluster explorer provides both a bird’s-eye view of a customer’s entire Kubernetes environment as well as the ability to dive deep into the performance of individual pods and nodes – all in a matter of seconds. Now customers can see not only how their Kubernetes entities are performing, but also how they are impacting their entire environment.

New Relic’s Kubernetes cluster explorer is designed to give software teams an easy way to manage the performance of modern environments.

- Multidimensional views into Kubernetes clusters - New Relic’s Kubernetes cluster explorer provides a unified view into infrastructure, applications, and services across Kubernetes clusters, so customers can inspect a single container, or scale up to explore a deployment of the whole cluster.

- Advanced filtering to quickly find root cause - DevOps teams can easily drill down to the objects they care about – containers, pods, nodes, deployments, namespaces, and labels – and access their application- and infrastructure-metrics to connect the dots between their complex, distributed systems.

- Delivers immediate value - New Relic’s SaaS platform delivers value as soon as the Kubernetes agent is deployed. There is no infrastructure to provision, secure, or run, so DevOps teams can focus on delivering software for their customers, not instrumenting and building their monitoring solution.

- Easy to get started on any cloud or on-prem - New Relic Kubernetes monitoring is compatible with all major cloud platforms as well as on-premise environments so teams can observe their Kubernetes workloads, regardless of where their containers are deployed.

"Today, modern software teams need to detect and resolve problems as quickly as possible. During critical service interruptions, every second counts. New Relic has a long history of instrumenting and visualizing our customers’ business-critical software in new ways so they can take action quickly and reduce their mean-time-to-detect and mean-time-to-resolution. Our new Kubernetes cluster explorer is designed to help our customers connect the dots between their complex, distributed systems faster than previously possible,” said Aaron Johnson, SVP, Product Management, New Relic

New Relic’s Kubernetes cluster explorer will be available in early 2019 for all New Relic customers who have enabled the Kubernetes on-host integration.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...