New Relic Adds Native Kubernetes Support to Observability Platform
At the Kubecon + CloudNativeCon Europe conference, New Relic announced today it is now providing native Kubernetes support for OpenTelemetry and Prometheus-instrumented hosts.
Greg Ouillon, CTO for Europe, Middle East and Africa (EMEA) at New Relic, said IT teams can now instrument Kubernetes clusters and hosts using the OpenTelemetry collector and Prometheus Node Exporter in a single step.
This capability supersedes a more cumbersome approach that New Relic had been using to collect data via OpenTelemetry agent software that is being advanced under the auspices of the Cloud Native Computing Foundation (CNCF). Now that data manifests itself directly within the New Relic dashboard, noted Ouillon.
That capability makes it simpler to render topology maps to, for example, understand how the performance of an application is in real time affecting infrastructure and vice versa as an application is being deployed, he added.
New Relic supports both OpenTelemetry and a set of open source agents that it originally built to collect data. Those latter agents are still needed to, for example, collect telemetry data from applications and databases alongside infrastructure, noted Ouillon.
The company also previously donated to the CNCF an open source Pixie observability platform it acquired that makes use of extended Berkeley Packet Filtering (eBPF) to collect observability data.
Regardless of the approach to observing and monitoring cloud-native application environments, the amount of data that needs to be analyzed compounds as each additional microservice is created. New Relic recently added a live archives capability that, in addition to providing instant access to historical logs for up to seven years, eliminates the need to rehydrate, reload, re-index or move data. The overall goal is to reduce the toil that many DevOps teams encounter today when managing telemetry data.
Ultimately, existing DevOps teams should be able to manage highly distributed application environments without having to hire and retain a small army of additional software engineers. The issue is that, in many cases, the size of the overall codebase is increasing rapidly as developers take advantage of various generative AI tools to help them write code faster. Hopefully, advances in AI will arrive soon enough to enable DevOps teams to cope with all that code before DevOps teams are inevitably overwhelmed.
In the meantime, as more organizations realize how dependent business has become on IT, the types of individuals within an organization looking to access observability platforms continue to increase. The challenge is finding ways to present different personas within an organization with insights that surface in ways they can readily comprehend. Many of those end users, for example, are not especially interested in every IT metric that might be collected.
Ultimately, increased observability should help significantly close the historical divide that has existed between IT and the rest of the business. The challenge, as always, is finding a way to justify the investment needed to provide deeper levels of visibility into complex IT environments at a time when many IT teams already have no shortage of tools for monitoring pre-determined metrics.
