As you continue your monitoring and observability journey with Wavefront by VMware and more teams in your organization start using the platform, one thing becomes clear; you need the ability to see how the platform is being used. Basically, you need the ability to monitor the monitor. Wavefront comes with a number of internal metrics that track usage of your Wavefront instance and provides you with countless ways to interpret them via the query language.
In this post, I’ll walk you through instrumentation and monitoring of a simple standalone application developed with Spring Boot 2.0. The application is running as a container in Kubernetes. Spring Boot is an open-source Java-based framework used to create microservices. Kubernetes is a popular container orchestration system. See the references at the end of the page to learn more about Spring Boot and Kubernetes.
I recently chatted with Scott Bonebrake, Principal Software Engineer in the Data Engineering and Analytics (DEA) team at Microsoft Yammer. Yammer is a secure enterprise social network internal to an organization, that enables people to connect and engage across their company. We discussed why Yammer chose Wavefront by VMware and how they are using Wavefront to increase their ROI.
Red Hat OpenShift is an open-source, cloud application development platform that enables you to develop, deploy, and manage applications on your cloud infrastructure. We at Wavefront provide enterprise-grade observability and analytics for multiple Kubernetes environments across multiple clouds, now certified for the latest version of OpenShift, Red Hat OpenShift 4.
As a developer, SRE, or operations engineer, you often get incident alerts, and you know it’s just the beginning. Alerts lead to a slew of questions that must be answered in order to triage an issue. The Wavefront Alert Viewer helps you answer these questions quickly by presenting the information you need.
Earlier this year, we released the Wavefront Collector for Kubernetes, supporting all popular flavors of Kubernetes: VMware Enterprise PKS and Tanzu, Pivotal Cloud Foundry, Red Hat OpenShift, Amazon EKS, Google GKE, Azure AKS, and others. With it, we were able to bring an entirely new set of capabilities to help you monitor and manage your Kubernetes deployments at scale, proven to support 200,000+ containers per cluster in use and 1,000s of developers.
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.
Prometheus has become something of a de-facto standard for how to start monitoring Kubernetes. There are good reasons for this: It’s open source, freely available and embraced by the Cloud Native Computing Foundation (CNCF). Also, Prometheus was designed to handle the highly ephemeral nature of Kubernetes workloads. This has propelled Prometheus to a position as the obvious choice for anyone initially wanting to monitor Kubernetes.
Distributed tracing is a critical piece of application observability. But instrumenting your applications with traces is not always easy. Whether you are an SRE or a developer, you need application observability. But you might not prefer to instrument code. That is where the Wavefront Tracing Agent for Java comes in handy, as it provides application observability without needing any code change.
External linking helps engineering teams connect Wavefront to logging tools such as vRealize Log Insight, ELK, or Splunk. For example, when you have received alerts and see them in Wavefront, and then want to investigate them further by drilling down into logs, you can quickly do that using the Wavefront External Links feature.