Kubernetes Podcast from Google

Unicron, with Daniel Megyesi

Sep 2, 2021

48:32

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Highlights

AI Chapters

Episode notes

Using Big Data for Analytics?

02:03

Cobernat Is Solution - What Are the Things That Are Missing From Equipa Iste?

03:08

How to Deploy Clusters in a Small Environment?

02:16

Introduction

3min

The Monarchy Is a Nice Thing to Have

3min

Open Telemetry - A New Version of Susa

2min

How Did You Come Across Containers and Cloud Native?

4min

Avery Overengineered Solution for an Apral Fool's Jokes

2min

How Does Edivente Handle Centralized Services?

3min

Using Big Data for Analytics?

2min

What Was the Final Nail in the Coffin?

2min

UniCron - The Name Is Just Unicorn

2min

10.

How Do You Collaborate With Others?

2min

11.

Cobernat Is Solution - What Are the Things That Are Missing From Equipa Iste?

3min

12.

Multi Tenant Clusters - What You Need to Know

2min

13.

How to Deploy Clusters in a Small Environment?

2min

14.

Using a Cluster to Deploy Workload Containers?

2min

15.

Using Argoside to Deploy a Tag Dept?

2min

16.

Is It a Hard Sell to Scale Your Business?

2min

17.

How to Build a Machine Learning Platform?

3min

18.

The Future of the Supply of Form?

4min

19.

Building a One to Eight Replica of the Doloreum

4min

Adevinta is an online classified ads company, operating many local brands. Daniel Megyesi is a DevOps engineer at Adevinta and maintainer of their central big data and Machine Learning platform, Unicron. Learn why they wanted to replace Mesos, how they aligned their engineering efforts to do so, and the choices that had to be made to provide an easy experience for their data engineers.

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