Palo Alto, CA, USA
Sep 5, 2019   |  By Stela Udovicic
Recently, we had the pleasure to talk to Manu Mathew, Senior Manager – Performance Engineering from Secureworks. Manu shared his team’s journey of supporting rapid service growth, some of the monitoring challenges they faced along that journey and how they overcame those challenges. Here’s a recap of Manu’s fascinating story.
Aug 30, 2019   |  By Eran Carmel
Earlier this week, we announced key enhancements to Wavefront’s application observability with support for span logs, context-enriched alerts, and unified status dashboards combining service, application, and the underlying system. In this blog, I will cover the details of Wavefront’s Integrated Application Observability and show you how it empowers SREs and developers to quickly troubleshoot any issue and find the root cause faster.
Aug 29, 2019   |  By Karthik Narayan
We are thrilled to announce the expansion of the Kubernetes observability experience in Wavefront with the next generation release of the Wavefront Collector for Kubernetes. This release has a significant number of changes that give Kubernetes operators, SREs and developers, richer visibility into the health, state, and performance of their Kubernetes environment. In addition, the auto-discovery capability in the Wavefront Collector for Kubernetes can identify and monitor your Kubernetes workloads.
Aug 28, 2019   |  By Gaanesh Kapatralla
Enterprises are increasingly adopting cloud for deploying applications and moving to a subscription-based business model for running their SaaS initiatives. Enterprise observability platforms, like Wavefront, have proven to be well suited for helping Dev, Ops, and centralized observability teams to ensure frictionless application SLAs, feature updates, and ultimately customer satisfaction. All these factors drive the need for accountability and cost management around the usage of Wavefront.
Aug 27, 2019   |  By Gordana Neskovic
With announcement at VMworld 2019 in San Francisco this week, the Wavefront platform is bolstered with many enterprise observability capabilities. Our primary aim is to empower Kubernetes platform operators, SREs, DevOps and developer teams to dramatically reduce MTTD and MTTR, with full-stack views into any issue using analytics from metrics, traces, histograms and span logs. Several new features make it possible to reliably and securely grow your cloud services without worrying about scaling limits on containerized microservices and infrastructure. Here's an overview of what's new!
Sep 14, 2018   |  By Wavefront
Modern highly distributed cloud application architectures require a modern monitoring and analytics approach. Find out why SaaS leaders such as Workday, Intuit, Box, and Groupon are choosing metric analytics to gain real-time insight into the performance of their critical services.
Sep 1, 2018   |  By Wavefront
Managing the performance of distributed cloud applications at scale requires a modern monitoring approach. Should you rely on logs or metrics instrumentation to monitor them? This guide will help you select the best analytics approach for your cloud application stack.
Aug 1, 2018   |  By Wavefront
Containers help you to move faster with application innovation. But they also create monitoring complexity due to their short lifespan, highly dynamic nature, and lean functionality. Read this eBook to get best practices for container monitoring. You will also discover Wavefront's out-of-the-box monitoring suite for Docker, Kubernetes, AWS, and more. Finally, find out how Wavefront customers monitor their containerized applications in production.
Jul 1, 2018   |  By Wavefront
In the dynamic world of public clouds with many services, scaling your cloud-native applications can be challenging. When choosing a monitoring platform for their cloud applications, DevOps and developer teams must look for characteristics that reflect the nature of running code on a public cloud: speed, flexibility, and scalability.
Sep 10, 2019   |  By Wavefront
There are many options for tracing, and various different architectures to implement. Understanding how to interpret and use the tracing data to optimize the application is not well understood by many.
Sep 6, 2019   |  By Wavefront
Clement Pang of VMware with Dejan Deklich and Edgar Nidome of 8×8, chat following their breakout session at VMworld 2019.