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Kubernetes Navigator: Real-time Monitoring and AI-Driven Analytics for Kubernetes Environments Now Generally Available

We are excited to announce the general availability of Kubernetes Navigator, a new way for DevOps and SRE teams to understand and manage the performance of containerized applications using an intuitive, out-of-the-box UI that navigates through the entire Kubernetes environment.

In less than five years since its release, Kubernetes has become the “de-facto standard for container orchestration” (Gartner 2019). Several business benefits propel enterprises toward Kubernetes to build, test, deploy, and run modern applications at scale, including operational efficiency, portability across multi-cloud environments, and cost optimization.

However, despite the benefit of Kubernetes, many enterprises encounter challenges as they progress in their journey to cloud-native. According to the latest CNCF survey published in March 2020, complexity and monitoring are the top challenges in Kubernetes adoption. 

Challenges in Monitoring Kubernetes Environments

As Kubernetes environments scale and applications get more distributed, monitoring becomes more challenging. DevOps teams struggle with:

  • Gaining multi-dimensional visibility into the health of the entire Kubernetes environment

  • Detecting performance issues in real-time

  • Correlating interdependencies among Kubernetes components (nodes, pods, containers, and services)

  • Understanding the why behind performance anomalies

  • Switching context while searching through multiple metrics, logs, and events platforms resulting in the higher mean time to resolution.

Grappling with these challenges, SREs and DevOps engineering teams end up spending the bulk of their time answering basic questions regarding the performance of Kubernetes environments. As the complexity and scale increase, so does the effort required to detect and resolve problems. Applying traditional approaches to monitoring in Kubernetes environments doesn’t work. 

Enterprises need a fully-automated approach based on multi-dimensional analysis, combining metrics and granular logs, that leverages AI-driven analytics for actionable recommendations and insights.

Introducing Kubernetes Navigator

Included with SignalFx Infrastructure Monitoring, Kubernetes Navigator is an enterprise-grade and turn-key Kubernetes monitoring solution that provides an easy and intuitive way to understand and manage the performance of Kubernetes environments. Working alongside hundreds of customers, we designed a solution that works for every team—irrespective of their maturity and experience with Kubernetes. Kubernetes Navigator brings immediate value to teams that are starting on their cloud-native journey while also addressing monitoring challenges for the world’s most complex Kubernetes deployments at scale.

“SignalFx provides a real-time view into how all of our AWS cloud services are performing. Most of our applications are now deployed on Amazon EKS. SignalFx Kubernetes Navigator cuts through the complexity that Kubernetes deployments bring while helping us manage the health of Kubernetes clusters and our workloads. Using SignalFx, we’ve improved the speed at which we identify and remediate performance issues—not to mention avoided incidents for our applications deployed in Kubernetes environments.”

Alexandre Bescond, Head of Infrastructure DevOps, BidMotion

With Kubernetes Navigator, your teams can detect, triage, and resolve performance issues faster than ever before. DevOps and SRE teams can successfully navigate the complexity associated with operating Kubernetes at scale by taking advantage of these features:

  • Dynamic Cluster Map: An intuitive way to instantly understand the health of Kubernetes clusters
  • Drill-downs: Faster and effective troubleshooting with quick drill-downs
  • Logs in context: Deep linking to contextual logs to gain granular insights, eliminate context switching and accelerate root cause analysis
  • Kubernetes Analyzer: AI-driven analytics to expedite troubleshooting 

Dynamic Cluster Map

Starting with the bird’s eye view, Kubernetes Navigator enables teams to quickly understand the performance of the entire Kubernetes environment with intuitive and hierarchical navigation. Select, filter, or search for any Kubernetes entity, e.g., node, pod, and container level within seconds. SignalFx automatically discovers Kubernetes components and containerized services to instantly monitor your entire stack. Understand relationships between dynamic Kubernetes components and quickly fix interdependent performance issues.

Drill-Downs

A global, at-a-glance view into the entire Kubernetes environment helps teams understand how the overall system is performing. It is equally important to have a granular, detailed view into individual components as teams narrow down to the source of the problem—drilling down from nodes to pods to containers to workloads. Our streaming architecture enables in-depth analysis with search and filters within seconds at a massive scale.

 

Logs in Context

Seamlessly pivot to logs and get granular visibility into application, Kubernetes, and container logs to correlate performance across the entire stack without any context switching. Visibility into lifecycle events of Kubernetes and API Server Audit logs help you understand and maintain your security and compliance postures.

 

Kubernetes Analyzer

To understand the “why” behind performance anomalies, Kubernetes Navigator leverages AI-driven analytics, which automatically surfaces insights and recommendations to precisely answer, in real-time, what is causing anomalies across the entire Kubernetes cluster – nodes, pods, containers, and workloads. In the example below, Kubernetes Analyzer automatically detects a pattern causing memory pressure on some of the Kubernetes nodes. In this case, a container with an unlimited memory limit ends up consuming all the available memory on these nodes draining other pods scheduled by Kubernetes. This scenario is commonly known as a noisy neighbor issue. Following suggested filters, SRE teams can narrow down to the underlying issue within minutes. Sophisticated algorithms, including Historical Performance Baselines and Sudden Change, detect system-level issues such as a sudden increase in Goroutines or container restarts and alert within seconds. 

 

 

Get Started with Fully Automated Kubernetes Monitoring

Future-proof your observability investment with a proven solution trusted by enterprises for most advanced use cases at a massive scale. Sign up for a free trial of SignalFx and get started quickly with helm based installation, and zero-touch configuration on any Kubernetes distribution – Amazon EKS, Azure AKS, Google GKE, RedHat OpenShift, or self-managed Kubernetes. Join us for our weekly live demo to see SignalFx live in action.

Amit Sharma
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Amit Sharma

Amit Sharma is the Director of Product Marketing at Splunk. He has over twelve years of experience in software development, product management, and product marketing. Before joining Splunk, Amit led product marketing at SignalFx, AppDynamics, and Cisco. He did his MSCE from Arizona State University and an MBA from UC Berkeley Haas School of Business.

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