Today we're announcing the release of our new Kubernetes experience to connect Kubernetes application and cluster performance data in a single user interface within application performance monitoring (APM) in New Relic One. This new experience helps you identify and resolve problems within Kubernetes clusters and their associated applications, so you can debug faster and scale infrastructure resources as required.
Why developers need to understand cluster performance
Kubernetes has blurred the lines between application and infrastructure. If you are a developer, your primary focus is on the application and not the cluster's performance, but the cluster's underlying components can have a direct effect on how well your application performs.
Most monitoring tools would silo application data from infrastructure signals. That doesn’t work in Kubernetes environments. This new experience integrates these areas so you can easily understand how K8s infrastructure affects your apps. These UI changes make it easier to view the entire landscape of your telemetry data and work together across teams.
Analyze performance in a single experience
Our Kubernetes experience fills this gap by curating application and cluster performance data in a new UI, helping you build more performant applications. The new experience provides you with the following capabilities directly within APM:
- A single, curated UI that combines APM and Kubernetes cluster performance data, eliminating the need to navigate between APM and infrastructure monitoring in New Relic One to manually correlate data.
- A real-time activity stream that alerts you to Kubernetes events and critical issues.
- One-click logs and side-by-side (selectable) metrics to correlate and investigate performance anomalies.
Correlate performance between apps and clusters
Whether you’re troubleshooting or optimizing performance, the ability to identify all the underlying components and see how they’re performing is critical. Our new APM-Kubernetes experience helps you determine how cluster performance impacts your applications. Because we link the metadata of all of your entities, you’ll see the workloads, deployments, daemonsets, pods, and hosts that your clusters are linked to.
For example, when latency exceeds acceptable limits, you may find that memory utilization is too high and pods are getting killed when they are out of memory (OOM) due to insufficient cluster resources. You’ll see this behavior in the pods and containers summary as well as in the activity stream.
The activity stream helps you understand the relationship between your cluster’s performance and cluster events. As apps are deployed, these important events help you understand how they interrelate to cluster performance, and ultimately, application performance. Additionally, we provide the opportunity for you to filter events so that when problems arise, you can focus on what matters most.
Investigate anomalies faster
Investigating anomalies can be difficult, which is compounded when relevant data is scattered amongst different UIs, or worse, among different tools. That’s why you now have access to all the information you need in one place. In addition to performance metrics that you’d expect, such as CPU, memory, network, and storage, you have access to relevant logs so you can see what’s driving performance changes. We add metadata that links your logs with your related Kubernetes telemetry data, such as errors or cluster performance data, so you can home in on exactly the right data to understand what’s impacting your application’s performance.
And when you want to correlate performance across metrics, use the charts at the bottom of the page. Simply choose between any two metrics in each chart’s dropdown menu to analyze how they’re correlated, including choosing between average, max, and p95. Because these charts are built using NRQL, you can open up these pre-built queries in a separate query builder to go beyond these charts and ask questions about your data.
The following user-selectable metrics are available:
- CPU usage (cores)
- CPU utilization (%)
- CPU throttling (%)
- Memory usage (bytes)
- Memory utilization (%)
- Network received (KBps)
- Network transmitted (KBps)
- Network errors (per second)
- Storage usage (bytes)
- Storage utilization (%)
- Container restart count
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This blog post contains “forward-looking” statements, as that term is defined under the federal securities laws, including but not limited to statements regarding expected features and benefits of New Relic’s Kubernetes experience, including any anticipated benefits, results and future opportunities related thereto. The achievement or success of the matters covered by such forward-looking statements are based on New Relic’s current assumptions, expectations, and beliefs and are subject to substantial risks, uncertainties, assumptions, and changes in circumstances that may cause New Relic’s actual results, performance, or achievements to differ materially from those expressed or implied in any forward-looking statement. Further information on factors that could affect New Relic’s financial and other results and the forward-looking statements in this post is included in the filings New Relic makes with the SEC from time to time, including in New Relic’s most recent Form 10-Q, particularly under the captions “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations.” Copies of these documents may be obtained by visiting New Relic’s Investor Relations website at http://ir.newrelic.com or the SEC’s website at www.sec.gov. New Relic assumes no obligation and does not intend to update these forward-looking statements, except as required by law.