Docker in Production: An Update
The previous article Docker in Production: A History of Failure was quite a hit. After long discussions, hundreds of feedbacks, thousands of comments, meetings with various individuals and major players, more experimentation and more failures, it’s time for an update on the situation. We’ll go over the lessons learned from all the recent interactions and articles, but first, a reminder and a bit o
Google Cloud is 50% cheaper than AWS
Let’s revisit Google and Amazon pricing since the AWS November 2016 Price Reduction. We’ll analyse instance costs, for various workloads and usages. All prices are given in dollars per month (720 hours) for servers located in Europe (eu-west-1). Shared CPU Instances Shared CPU instances give only a bit of CPU. The physical processor is over allocated and shared with many other instances running on
GCE vs AWS in 2016: Why you shouldn’t use Amazon
Foreword This story relates my experience at a typical web startup. We are running hundreds of instances on AWS, and we’ve been doing so for some time, growing at a sustained pace. Our full operation is in the cloud: webservers, databases, micro-services, git, wiki, BI tools, monitoring… That includes everything a typical tech company needs to operate. We have a few switches and a router left in t
Docker in Production: A History of Failure
Introduction My first encounter with docker goes back to early 2015. Docker was experimented with to find out whether it could benefit us. At the time it wasn’t possible to run a container [in the background] and there wasn’t any command to see what was running, debug or ssh into the container. The experiment was quick, Docker was useless and closer to an alpha prototype than a release. Fast forwa
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