The platform already had anomaly detection and parameter forecasting. VMware added a new tool called AI Genie that automates both using artificial intelligence (AI) and machine learning. This allows more “novice users” to detect and visualize anomalies and explore future trends via a simple user interface — as opposed to using statistics or algorithms, explained Stela Udovicic, senior director of product marketing for Wavefront.
“You do not need to have any knowledge of statistics or algorithm expertise — no math required,” she said. This leads to faster trouble shooting, better application and infrastructure efficiency, and simpler, more intelligent alerting.
In addition to AI Genie, Wavefront added distributed tracing for microservices. Distributed tracing is a tool for monitoring and troubleshooting microservices that allows developers to search trace data. The platform already provided a view into metrics and histograms. Adding distributed tracing support makes Wavefront “the first and only platform for microservices observability that combines a ‘three-dimensional’ view into metrics, histograms, and traces at cloud-scale, over 1 million data points per second,” according to a VMware blog.
Adding trace data provides customers with additional context and better visibility into application performance compared to traditional application performance monitoring tools, Udovicic added. “The combination of metrics, histograms, and traces provides visibility into not only when something is failing, but why it is failing,” she explained.
Both new services are available in beta. AI Genie is set for general availability in mid-December, followed by distributed tracing in mid-January 2019.
VMware bought Wavefront in April 2017 for an undisclosed amount. Customers include Box, Hive, Okta, Doordash, and Lyft, and are primarily cloud-native companies. Since the acquisition, however, VMware has focused on increasing adoption among more traditional enterprises.
VMware also added integrations since purchasing the monitoring startup. It now counts more than 160 integrations. These include pre-packaged dashboards and metrics across technologies ranging from cloud platforms (Amazon Web Services (AWS), Microsoft Azure, and Google Cloud); containers (Kubernetes and Pivotal Container Service); and operating systems (Linux, Microsoft, and VMware).
These integrations are becoming increasingly important as customers look to adopt containers and serverless, Udovicic said, because they provide instant visibility and alerting across services and infrastructure. For example, Wavefront can ingest, analyze, and visualize metrics from 100,000 running containers.