Wavefront Automates and Unifies Enterprise Observability for Kubernetes and Applications Running on Multi-Cloud Environments

December 2, 2019 Chhavi Nijhawan

Wavefront by VMware delivers comprehensive observability capabilities that benefit customers greatly. In particular, Wavefront is designed for enterprises needing at-scale Kubernetes observability, benchmarked to monitor 200,000+ containers per cluster in use. Now we’re adding enhancements to further automate observability for Kubernetes and modern cloud-native applications. These enhancements will include one-click instrumentation deployment, faster incident triaging, and enhanced root-cause analysis. This blog provides an overview of the upcoming capabilities and their benefits.

Here is a summary of the benefits for DevOps teams, Site Reliability Engineers (SREs), Kubernetes architects and developers:

  • Accelerated time to value with automated and unified observability for Kubernetes and modern applications
  • Faster incident triaging with Wavefront Alert Viewer
  • Quicker root-cause analysis with Wavefront Java Tracing Agent

Automated and Unified Enterprise Observability for Kubernetes and Applications

Kubernetes Platform Operators, SREs, and DevOps teams often have different siloed monitoring solutions to monitor the application, Kubernetes, and multi-cloud domains. As a result, organizations lack a unified view, resulting in excessive time to troubleshoot issues. To address this complexity in observability, Wavefront introduces automated deployment of Kubernetes and Java Tracing Agent-based application observability.

Here are the benefits of the Wavefront implementation:

  • Automatically deploy Kubernetes and Java Tracing Agent-based application observability with a zero-configuration installation
  • Automate observability of OpensShift environments, full-stack, with Red Hat Certified Wavefront Operator for OpenShift 4
  • Rapidly identify root causes with predefined Wavefront alerts and events for Kubernetes’ operation

Automated Kubernetes and Java Tracing Agent-Based Observability

Wavefront auto-configured, fast, and straightforward deployment enables improved life cycle management of the Wavefront Kubernetes Collector. With a zero-configuration installation, engineers gain instant observability for their Kubernetes environment and auto-discovered workloads. Wavefront Kubernetes observability supports on-prem Pivotal environments and multi-cloud environments after you’ve supplied read-only credentials.

Wavefront discovers your Kubernetes environment on public cloud infrastructure (EKS, AKS, GKE) after you have supplied read-only credentials

The Wavefront Kubernetes Collector automatically discovers Java-based services and instruments them via the Wavefront Java Tracing Agent. This way, engineers instantly get out-of-the-box insights into applications’ health and performance.

Unified observability for Kubernetes and applications results in deeper understanding and faster troubleshooting of Kubernetes environments and the application workloads running on them.

Automated OpenShift Observability

Wavefront continues to expand its observability support for OpenShift and multi-vendor Kubernetes environments. The Red Hat Certified Wavefront Operator for OpenShift 4 will be available in Operator Hub, a public registry for finding Kubernetes Operator baked services. With the Wavefront Operator, developers and OpenShift platform operators will get automated observability across OpenShift environments, including containerized applications, Kubernetes, and underlying infrastructure.

Automated Kubernetes Operational Intelligence

Wavefront gathers detailed information about the operation of the Kubernetes environment. For example, Wavefront informs engineering teams about utilization extremes, SLA violations due to increased latency or error rate per service, excessive pod restarts, and paused or stuck deployments. Additionally, Wavefront auto-configures a set of Kubernetes-related alerts. These alerts enable engineering teams to proactively detect and resolve issues before they can impact production.

Faster Incident Triaging with Wavefront Alert Viewer

As software systems become more complex and the demand for quality and reliability increases, DevOps and SRE teams find themselves overwhelmed and unable to reduce MTTR. To remediate this situation and enable fast incident triaging and resolution, Wavefront will be introducing Wavefront Alert Viewer.

The Wavefront Alert Viewer will be a single landing page for an alert. It will surface related alerts and tags – powered by AI/ML algorithms – thereby accelerating incident detection and resolution. Furthermore, the Wavefront Alert Viewer page will automatically highlight point tags shared by affected time series, giving a clear indication of what might be going wrong. Automated analysis of point tags will enable developers and SREs to instantly spot dependencies across firing alerts, leading to faster incident triaging and reduced service disruption.

The Wavefront Alert Viewer will also list other synchronously firing alerts and events, across the full stack. This includes alerts and events in application services, your Kubernetes platform, and the enterprise multi-cloud. These related alerts and events are then ranked based on correlation, intelligently derived with AI/ML algorithms. SREs and DevOps teams can easily search and filter through this key evidence of an incident’s root cause.

With Wavefront Alert Viewer, customers get the following benefits:

  • Full view of an incident with related alerts and events listed and ranked using AI/ML algorithms
  • Quick assessment of incident impact with the ability to highlight and correlate common point tags

Wavefront Alert Viewer enables faster incident triaging by automatically highlighting related incidents, alerts and point tags

Streaming Real-Time Alerts

Wavefront has introduced support for streaming real-time alerts, enabling customers to alert in seconds. Typical use-cases of real-time alerts include scenarios where engineers are alerting on single time series data and want to kickstart automation scripts as soon as possible.

Real-time alerts are fast, but for cases where you need to aggregate data across different sources, real-time alerts can lead to alert flapping and potential alert storms.

So, it is essential to understand and choose when to enable real-time alerts. Use Wavefront real-time alerts when you need faster automation and the alert is not aggregating data. When you are aggregating data across different hosts or time series, use regular alerts instead.

Out-of-the-Box Application Observability with Wavefront Java Tracing Agent

Wavefront is introducing Wavefront Java Tracing Agent. The Wavefront Java Tracing Agent provides an easy, automated experience for achieving application observability, so busy SRE and DevOps teams can get instant visibility into their application performance without making any code changes. The Wavefront Java Tracing Agent is based on Java Special Agent, which is an open-source tracing agent for Java. The Wavefront Java Tracing Agent automatically instruments 3rd-party libraries in Java, providing out-of-the-box visibility into traces, RED metrics and span logs for Java-based applications.

Out-of-the-box application performance visibility – distributed traces, RED metrics and service maps provided by Wavefront Java Tracing Agent

Wavefront Intelligent Trace Sampling

Wavefront will be adding intelligent trace sampling support. Wavefront Intelligent Trace Sampling will automatically sample traces that are likely to be more informative and discard redundant traces. Furthermore, Wavefront Intelligent Trace Sampling will derive and retain RED metrics for all traces – including metrics of traces that were not retained after sampling, providing 100% visibility into your application traces even after sampling.

This intelligent trace sampling will be performed by the Wavefront service itself, not by the Wavefront proxy or by an instrumented application. Consequently, intelligent trace sampling will not place any additional processing burden on your proxies or applications. Thus, the Wavefront Intelligent Trace Sampling does not add to your total cost of operation (TCO).

With these application observability enhancements, SRE and DevOps teams get the following benefits:

  • Easily achieve application observability without code changes using the Wavefront Java Tracing Agent
  • Get complete trace visibility at scale with the Wavefront Intelligent Trace Sampling

Come See Wavefront in Action at AWS re: Invent

Attending AWS re:Invent? Come stop by at Wavefront booth to see a live demo of all the capabilities mentioned above. At the Wavefront booth, ask us how Wavefront delivers enterprise-ready and automated observability for Kubernetes, OpenShift and applications. With the latest additions, Wavefront will accelerate incident triaging and expedite application root-cause analysis enabling faster troubleshooting across a multicloud, full-stack.

For more details on any of the above-mentioned capabilities or see Wavefront in action, check out our free trial today.

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The post Wavefront Automates and Unifies Enterprise Observability for Kubernetes and Applications Running on Multi-Cloud Environments appeared first on Wavefront by VMware.

About the Author

Chhavi Nijhawan

Chhavi is a Product Line Marketing Manager at Wavefront by VMware. Before Wavefront, she worked at New Relic, SnapLogic and Cisco, where she led product marketing and technical marketing. She has over 10 years of IT industry experience. She is also an AWS certified solutions architect.

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