Managed Service for Prometheus with Lee Yanco and Ashish Kumar

Описание

Hosts Carter Morgan and Anthony Bushong are in the studio this week! We’re talking about Prometheus with guests Lee Yanco and Ashish Kumar and learning about the build process for Google Cloud’s Managed Service for Prometheus and how Home Depot uses this tool to power their business. To begin with, Lee helps us understand what Managed Service for Prometheus is. Prometheus, a popular monitoring solution for Kubernetes, lets you know that your project is up and running and in the event of a failure, Prometheus lets you know what happened. But as Kubernetes projects scale and spread across the globe, Prometheus becomes a challenge to manage, and that’s where Google Cloud’s Managed Service for Prometheus comes in. Lee describes why Prometheus is so great for Kubernetes, and Ashish talks about CNCF’s involvement helps open source tools integrate easily. With the help of Monarch, Google’s Managed Service stands above the competition, and Lee explains what Monarch is and how it works with Prometheus to benefit users. Ashish talks about Home Depot’s use of Google Cloud and the Managed Service for Prometheus, and how Home Depot’s multiple data centers make data monitoring both trickier and more important. With Google Cloud, Home Depot is able to easily ensure everything is healthy and running across data centers, around the world, at an immense scale. He describes how Home Depot uses Managed Service for Prometheus in each of these data center environments from the point of view of a developer and talks about how easy Prometheus and the Managed Service are to integrate and use. Lee and Ashish wrap up the show with a look at how Home Depot and Google have worked together to create and adjust tools for increased efficiency. In the future, tighter integration into the rest of Google Cloud’s suite of products is the focus. Lee Yanco Lee Yanco is the Product Management lead for Google Cloud Managed Service for Prometheus. He also works on Monarch, Google’s planet-scale in-memory time series database, and on Cloud Monitoring’s K