Curated articles, resources, tips and trends from the DevOps World.
Application that are critical for the health of your business can’t be monitored manually. If you’re waiting for users to report errors or drawbacks, you’re effectively outsourcing bug discovery to users. Many of them don’t reports bugs, they eventually just stop using your product.
Building a test automation framework with Selenium is more an art than a technical activity. A lot needs to be considered when building such frameworks. Understanding client expectations for what needs to be delivered is a key aspect in thinking about automation.
This is what another Scrum Master told me after we took turns during a recent training to share a success story about a Development Team. I've heard this many times before.
I’m using Terraform to create an Elastic Beanstalk Java Application for dev and stage environment. This guide is targeted at AWS and Terraform buddies. We’ll walk you through the entire process, step-by-step:
Written by André Gaul and Todd Kaplinger. In the following sections of this article, we are going to guide developers through the process of standing up a Stellar validator node that can join the Stellar Testnet.
First time I found myself setting up a monitoring instance composed of Influxdb, Telegraf and Grafana, my biggest dilemma was how to group the various servers by dividing them by services (Docker, Elasticsearch cluster, Apache servers and so on).
Data scientists have a dynamic role. They need environments that are fast and flexible while upholding their organization’s security and compliance policies. Notebook Virtual Machine (VM), announced in May 2019, resolves these conflicting requirements while simplifying the overall experience for data scientists.
Five years ago when I started tracking media buzz around stateful architectures, I’d see a few articles every month about running stateful containers. That's about when Caitie McCaffrey first shared this awesome presentation about building scalable stateful architectures.
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In this article, I set up a Python script that allows us to calculate the similarity of an indexed field between all the documents of a MongoDB collection. In the process I parallelized the executions on four threads to improve performance. The script is detailed below, I hope it will be useful.
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