Grafana Labs Teams Use Jaeger to Improve Query Performance Up to 10x

Grafana Labs Teams Use Jaeger to Improve Query Performance Up to 10x

  • August 3, 2019
Table of Contents

Grafana Labs Teams Use Jaeger to Improve Query Performance Up to 10x

Grafana Labs works everyday to break traditional data boundaries with metric-visualization tools accessible across entire organizations. It began as a pure open-source project and has since expanded into supported subscription services. The Grafana open-source project is a platform for monitoring and analyzing time series data.

There are also subscription offerings such as the supported Grafana Enterprise version. Grafana Labs’ engineers service more than 150,000 active installations. Users include companies such as PayPal, eBay and Booking.com.

In 2017, Grafana Labs launched Grafana Cloud, a fully managed OpenSaaS metrics platform. The Grafana platform itself isn’t the only component that makes up Grafana Cloud. The mix includes Grafana Labs’ own Metrictank, a Graphite-compatible metrics service available in both an open-source and a hosted version, and Cortex, an open-source, managed version of Prometheus to which Grafana Cloud contributes.

These tools are integrated in subscribers’ Grafana Cloud instances. Grafana Cloud engineers also use them to troubleshoot their own and individual customers’ technical issues. All these components of Grafana Cloud make up a vast, varied and, at times, vexing software system.

Its engineering teams’ existing tools did plenty of heavy lifting observing and monitoring the system. For example, both Cortex and Metrictank process hundreds of simultaneous service requests per second.

Source: medium.com

Share :
comments powered by Disqus

Related Posts

How to run evolution strategies on Google Kubernetes Engine

How to run evolution strategies on Google Kubernetes Engine

Reinforcement learning (RL) has become popular in the machine learning community as more and more people have seen its amazing performance in games, chess and robotics. In previous blog posts we’ve shown you how to run RL algorithms on AI Platform utilizing both Google’s powerful computing infrastructure and intelligently managed training service such as Bayesian hyperparameter optimization. In this blog, we introduce Evolution Strategies (ES) and show how to run ES algorithms on Google Kubernetes Engine (GKE).

Read More
What is the Future of Observability?

What is the Future of Observability?

At KubeCon + CloudNativeCon EU last week, Grafana Labs VP Product Tom Wilkie and Red Hat Software Engineer Frederic Branczyk, gave a keynote presentation about the future of observability and how this trifecta will evolve in 2019 and the years to come.

Read More